NHS Digital Data Release Register - reformatted

King's College London projects

287 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).


🚩 King's College London was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. King's College London may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.

Standard versus Accelerated initiation of Renal Replacement Therapy in Acute Kidney Injury(STARRT-AKI): UK arm of a multi-centre randomized controlled trial — DARS-NIC-280606-N9Z7W

Opt outs honoured: Anonymised - ICO Code Compliant, Yes (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-01-31 — 2025-01-30 2022.05 — 2022.08.

Access method: One-Off

Data-controller type: GUY'S AND ST THOMAS' NHS FOUNDATION TRUST, KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Critical Care
  6. Hospital Episode Statistics Outpatients

Outputs:

The data requested aims to allow the accurate estimation of the impact of the timing of initiation of renal replacement therapy on resource use and costs of caring for patients with acute kidney injury. This data aims to be combined with individual patient data collected on outcomes (primarily mortality) for patients in the trial and observational data. The study team plan to analyse these data with the hope to address the cost-effectiveness of accelerated initiation of renal replacement therapy in an NHS setting over the period of the trial. Data is planned to also be used to estimate cost parameters for a decision model which aims to be used to extrapolate costs and outcomes over patients’ lifetimes and allow a lifetime analysis. The international trial ended in 2020 and the trial results have been published. This analysis aims to help contextualise the findings within a NHS setting and support decision making that is relevant to the UK context.

As a result of the data processing the study team intend to create various reports, submissions to peer reviewed journals, presentations, and representation at conferences.

The data processing aims to allow estimation of the mean costs of care for patients in the accelerated and standard initiation of RRT arms of the trial. In addition, it aims to allow estimation of the mean costs of specific episodes of care, such as the index admission to critical care, as a function of patient characteristics including age and Sequential Organ Failure Assessment (SOFA) score. These mean costs aim to be reported, alongside quantification of uncertainty in the cost estimates. They hope to also inform the economic analysis of accelerated initiation of RRT. That analysis is planned to consist of a trial-based analysis utilising the observed data and a model-based evaluation in which costs and outcomes are extrapolated over patient lifetimes.

The study team intends to publish the mean costs described above and the evaluation results supported by those costs in a report to the Human Tissue Authority (HTA). These also hope to form the basis of journal articles and conference presentations. The study team intend to target appropriate peer reviewed journals and conferences with relevant clinical audiences. Finally, the simulation model aims to be made available to the main trial team in Canada to allow customization and application to different jurisdictions by researchers considered appropriate. The UK study team and the Canadian study team will attempt to ensure that the value of the model in informing decision-making is maximised by ensuring that those who are given access are able and intend to apply and adapt the model appropriately.

No record level individual patient data will be published in any outputs. All data will be aggregate data with small number suppression applied in accordance with the HES Analysis guide. Primarily, the data derived from HES data will be the costs associated with accelerated and standard initiation of RRT. The study team intend to report the mean costs of key episodes of care such as the index admission, and the relationship with patient characteristics. The study team also intend to report data relating to outcomes such as mortality.

The study team intend to publish regular progress reports on the analysis of the trial on the STARRT-AKI website. Once the study team have completed the analysis, their primary dissemination strategy hopes to consist of publication in appropriate high impact journals alongside submission of a detailed report of the full findings of the study to the NIHR. In addition, the study team aims to seek to disseminate findings at appropriate international conferences, for instance the annual congress of the Intensive Care Society (ICS) UK, the annual International Symposium on Intensive Care & Emergency Medicine (ISICEM), the annual congress of the European Society of Intensive Care (ESICM) and UK Kidney Week of the Renal Association.

The study team expect to keep trial participants informed of publications. Where possible they will ensure publications are open access to maximise accessibility. The modelling work they aim to undertake, which will utilise data from HES for estimation of some parameters, aims to be made available to the wider international trial investigators to support adaptation and application to different jurisdictions.

The study team intend to communicate trial progress in the UK through NIHR networks, Intensive Care Unit (ICU ) and Renal networks and via the newsletters of the Kidney Patient Association, Kidney Care UK, the Biomedical Research Centre at Guys and St Thomas’ NHS Foundation Trust and "Think Kidneys" (a national programme supported by NHS England).

After completion of the trial, the results aim to be reported in accordance with the Consolidated Standards of Reporting Trials (CONSORT) guidelines. The findings are expected to be presented to collaborators / investigators, and subsequently at national and international meetings, for instance the annual congress of the Intensive Care Society (ICS) UK, the annual International Symposium on Intensive Care & Emergency Medicine (ISICEM), the annual congress of the European Society of Intensive Care (ESICM), UK Kidney Week of the Renal Association and the annual meeting of the American Society of Nephrology. The study team anticipate publishing the main trial results in a major high impact journal. The Health economic evaluation is expected to be published with this report, or in a separate detailed paper. These publications aim to supplement the final report published in the NIHR Health Technology Assessment (HTA ) journal.

With the help of Personal and Public Involvement (PPIs), a lay person’s summary is intended to be sent to relevant local and national patient support and liaison groups and charities. One of the co-applicants of the HTA grant is acting as PPI for this study. In addition, the study team is working closely with members of Guy’s Hospital Kidney Patient Association and ICUsteps, a charity supporting ICU survivors, who have previously helped with the conduct of the STARRT AKI trial in the UK. The study team aim to seek their input regarding dissemination of the study results. A report is also expected to be sent to the INVOLVE registry (an open-access database which registers research health care projects involving members of the public as partners in the research process). This ensures full transparency of the results and is recommended by research authorities.

Following peer reviewed publication, the key findings are intended to be posted on institutional websites available to the general public and communicated through press releases to ensure dissemination to research participants, patients and the broader public (e.g., through scientific reports, conference presentations and renal charity newsletters). In addition, the study team aim to work with professional societies and ensure that the conclusions are included in their official guidelines, including the AKI guideline by the Renal Association UK, recommendations by Kidney Disease Improving Global Outcomes (KDIGO) and the AKI guideline by the European Society of Intensive Care Medicine. Furthermore, the original HTA application was supported by National Institute for Health and Care Excellence (NICE ). It is very likely that the results of this analysis will also be incorporated in future NICE guidance.

As part of the analysis the study team aim to construct a simulation model to capture the longer-term impacts of the renal replacement therapy, and in particular, the impact of the timing of renal replacement therapy. The model is intended to allow evaluation of the cost-effectiveness of accelerated initiation of renal replacement therapy to inform decision making. The model will be primarily intended to inform decision making in the UK. However, the study team aim to make the model available to other investigators within the international trial who may wish to adapt the model to local settings. Along with the PI of the international trial the study team will consider the suitability of any requests to use the model. The study team aim to supply the model to any group they think will use the model appropriately to help inform decision making in their jurisdiction. The study team aim to annotate the model and provide documentation to help researchers adapt the model to their settings and they hope to provide advice to them to support adaptation and application of the model. The economic evaluation is funded by the NIHR with an expectation that the findings will be made freely available to inform decision making in the UK and beyond. The funders have no specific requirements regarding access or ownership of data.

The study team plan to have their analysis completed by January 2023. The study team expect to commence drafting of publications shortly after. The study team aim to submit the first draft of the final report to the NIHR in 2023. The study team aim to submit a draft manuscript of the findings of the economic evaluation to a high impact, peer reviewed open access journal in 2023, including The Journal of the American Medical Association (JAMA), Clinical Journal of the American Society of Nephrology (CJASN) and Intensive Care Medicine.

Processing:

METHODOLOGY
The study team plan to apply for two drops of data: Drop 1 covers data until the end of 2020/21; whilst Drop 2 data covers data until 7th May 2022 (end of follow-up for patients in the trial).

Study participants were recruited at different NHS hospitals. The individual teams at these sites collected clinical data and kept them on their secure hospital servers. The teams then sent relevant information, including the NHS Number to the lead clinical research team at Guy’s & St Thomas' Hospital (within Guy's & St Thomas’ NHS Foundation Trust). This allowed the team at Guy’s & St Thomas' Hospital to contact potential study participants and conduct follow up interviews. The study team at Guy’s and St Thomas’s Hospital holds the NHS numbers of all participating patients on a secure hospital server. They allocate a pseudo-ID to all patients.

1. Guy’s and St Thomas’s Hospital (within Guy's & St Thomas’ NHS Foundation Trust) will send NHS Digital, via Secure Electronic File Transfer Service (SEFT), a cohort file containing the NHS Number, Date of Birth and Study ID number for the patients in the trial and the observational study in one cohort file of approximately 500 participants.

2. NHS Digital will apply National Data Out Out and remove those records which are registered.

3. NHS Digital will link the remaining cohort to HES CC, A&E (ECDS), APC, OP and Civil Registration (Deaths) datasets and extract record level data.

4. NHS Digital will remove all identifiers, leaving only the Study ID, from the data extracts.

5. The record level pseudonymised data extracts will be sent to Kings College London via the NHS Digital Secure Electronic File Transfer system (SEFT)

The data will be accessed only by approved study researchers who are substantive employees at King’s College London. The data will be cleaned to remove any entries that appear to be erroneous or duplicates. Inpatient episodes will be linked, where appropriate, to construct continuous inpatient spells. A HRG code (The code of the Healthcare Resource Group under which an activity is grouped) will be assigned to each relevant episode or spell. The HRG code will form the basis of the assignment of a cost for the episode based on the relevant reimbursement tariff. Data on secondary care costs will be combined with data on primary care costs elicited from patients completing a bespoke cost questionnaire.

The study team are also applying to ICNARC to request data held by them on critical care received by patients in the trial and observational study. They are also applying to the Renal Registry to access data on renal replacement therapy for patients in the trial and observational groups. Data is captured in the Renal Registry when patients commence long term renal replacement therapy, an event which will happen for some of our patients. The study team would expect HES data to capture these events and provide data to allow determination of the hospital reimbursement. The data from ICNARC and the Renal Registry will serve as confirmatory source and to identify missing data in HES.

The study team are planning to link ICNARC and the Renal Registry data to the NHS Digital pseudonymised record level data using participant study ID numbers. The study team expect the data in this limited dataset to reflect HES data on dialysis for end stage renal failure. The study team would expect this data to provide additional detail on treatments received over and above that available from the HES data. However, the nature of the data is broadly the same as the data in HES. The study team will ensure that all data processing, linkage, and analysis is undertaken within the Safe Haven provided by AIMES Management Services Limited. The study team will not be using any publicly available data on patients. There will be no attempt to re-identify individuals. At no point do King's College London have access to the identifiers. At no point do Guy’s and St Thomas’s Hospital (NHS Foundation Trust) have access to NHS Digital pseudonymised record-level data. Linkage to ICNARC and the Renal Registry data is undertaken using the Pseudo study ID. The spreadsheet linking the pseudo-ID to the NHS number will only be stored at Guy’s and St Thomas’s Hospital (NHS Foundation Trust).

Data from patients on quality of life will be obtained using a brief questionnaire on health-related quality of life, alongside mortality data from the trial and observational study, and from the Civil Registrations (Deaths) data set, will be used to calculate the number of quality adjusted life-years (QALYs) gained by each patient. These data will be combined with data on costs to determine the incremental cost-effectiveness ratio (ICER) for accelerated initiation of RRT compared to standard initiation. The data will be bootstrapped* to quantify uncertainty in estimates of cost-effectiveness which will be reported as the cost-effectiveness acceptability curve (CEAC)**.

*Bootstrapping is a non-parametric technique which is commonly used to estimate the distribution of ICER from patients included in a clinical trial. Random samples of the same size as the original sample are drawn with replacement from the data source. The statistic of interest is calculated from each of these resamples, and these estimates are stored and collated to build up an empirical distribution for the statistic, for which measures of central tendency (mean cost and mean QALYs) and spread (confidence intervals) are obtained.

**Cost-effectiveness acceptability curve (CEAC) is a graph summarising the impact of uncertainty on the result of an economic evaluation, frequently expressed as an ICER in relation to possible values of the cost-effectiveness threshold. The graph plots a range of cost-effectiveness thresholds on the horizontal axis against the probability that the intervention will be cost-effective at that threshold on the vertical axis. It can usually be drawn directly from the (stored) results of a probabilistic sensitivity analysis. The CEAC helps the decision-maker to understand the uncertainty associated with making a particular decision to approve or reject a new heath technology.

DATA ACCESS
NHS Digital data will be stored on a server hosted on behalf of KCL by AIMES Management Service Ltd at their main server site in Liverpool. AIMES Management Service Ltd owns and manages the sever which will store the data. AIMES Management Service Ltd will facilitate access to the data by researchers using remote desktop access. AIMES Management Service Ltd personnel will not have access to the data. King’ College London’s clinical trials unit has contracted with AIMES Management Service Ltd to provide secure storage for sensitive data that is compliant with NHS security requirements.

All data analysis will be undertaken by substantive employees of King’s College London who are members of the King’s Health Economics group.

All analysis will be overseen by a senior researcher in King’s Health Economics who has had training in the processing and analysis of trial data according to the Standard Operating Procedures of King’s Clinical Trials Unit. All researchers accessing the data will be required to complete annual Data Security Awareness training. At no point will record-level NHS Digital data be processed by Guys and St Thomas’ NHS Foundation Trust.

The AIMES Management Service Ltd Trustworthy Research Environment (TRE) - also called the Safe Haven - boasts a separate analytics zone and data provisioning zone. The data provisioning zone is made up of Database Server, File Server and secure file transfer protocol Server and this zone is connected to the N3 Network, which is where the Patient Data is ingested. The analytics zone is where the file server, publishing server and the virtual desktop infrastructure (VDI) instances sit. Statistical data analysis will be carried out via King’s College London owned remote device connected to the AIMES Management Service Ltd Trustworthy Research Environment (TRE) network either directly in person or remotely, using an appropriate statistical package. To remotely access the devices requires a secure 2-factor authenticator (VPN) and users are then able to securely access the secure server on The AIMES Management Service Ltd Trustworthy Research Environment (TRE). All data analysis will be conducted within the confines of the secure server and will not be downloaded to remote devices for storage or processing.

The TRE is centrally managed and standardised for simple usage, utilising a controlled platform and secure access (Virtual Private Network or VPN), making use of standardised data retention, back-up policies and secure VDI architecture.

It is intended that the record-level NHS Digital data will remain on the TRE server. The data will be destroyed at the end of the agreed period and a data destruction certificate provided to NHS Digital.

It is possible that King’s College London may elect to use a different service provider in the future. In that situation the study team will inform NHS Digital of the change and request an amendment to the data sharing agreement so that the data can be moved lawfully.

AIMES supply IT infrastructure for King's College London and are therefore listed as data processors. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

HES and ECDS DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, data processors must make sure that:
• National-level figures only may be presented unrounded, without small number suppression
• cell values from 1 to 7 (inclusive) are suppressed at a sub-national level to prevent possible identification of individuals from small counts within the table.
• Zeros (0) do not need to be suppressed.
• All other counts will be rounded to the nearest 5.
Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.


Investigating the health of the socially excluded: physical and mental health multimorbidities across the social gradient in a nationally representative sample — DARS-NIC-320217-X8P0W

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2019-11-01 — 2022-10-30

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

King’s College London (KCL) is requesting the APMS 2014 record-level data for use in a research project investigating physical and mental health multimorbidities, defined as the co-existence of two or more chronic conditions, one of which is either a mental health or physical health condition of long duration, or an infectious disease of long duration (Academy of Medical Sciences, 2018). Previous research in this area has been limited but has highlighted an association between residency in deprived areas and the presence of a larger number of multi-morbidities (Barnett et al 2012). Using data from APMS 2014 and from 2007 surveys KCL aims to explore these issues further.
Justification for the processing of the data is under Article 6(1)(e) of the GDPR, for the performance of a task in the public interest; and Article 9(2)(j) of the GDPR, where processing of the data is necessary for research purposes in the public interest.

The present project will not only look at the social gradient of health morbidities – KCL will also address concerns that individuals who may have experienced social exclusion and extreme inequalities have worse health outcomes across the life course. A recent international meta-analysis of previous research has found that health inequalities persist in these groups for mortality and across a wide range of health conditions (Aldridge et al., 2018). The present analysis will build on this work with a focus on the presence of physical health morbidity with mental health conditions, which are known to be elevated in prevalence in these groups. Further knowledge on mental and physical health multi-morbidities across the social gradient and beyond is valuable to provide recommendations for co-ordinated and evidence-based healthcare and inform public health policy for individuals who are socially disadvantaged and excluded.

KCL's objectives are to look at (1) The association of occupational social class and other indicators of socioeconomic position with the presence of multi-morbidities, specifically characterising prevalence and types of multi-morbidity clusters most common in those of lower socioeconomic position compared to those of a higher socioeconomic position; (2) The presence, prevalence and nature of multi-morbidities in individuals who are socially excluded. Based on the literature this will include people who have experienced extreme social exclusion, for example have had previous or current experience of homelessness, sex work, or imprisonment. Patterns of physical and mental health multi-morbidities in this group will be compared to individuals who have not reported having these experiences.

As described in the NHS long-term plan (January 2019), addressing health inequalities is a key priority for research, policy and clinical practice. This project is part of a wider body of work into health inequalities which is being conducted by King’s College London researchers in the Department of Psychological Medicine, at the Institute of Psychiatry, Psychology and Neuroscience.

King's College London is the data controller and also processes the data for this study.  No other organisations process the data for this purpose. The data analysis will take place entirely at KCL. Only approved KCL researchers will have access to record level data, which will only be enabled through secure, password protected KCL computers operated by KCL research staff. KCL is not receiving any funding or involvement from any external body for this project. No other organisation is involved in this work.

References:

Academy of Medical Sciences (2018). Multimorbidity: a priority for global health research. https://acmedsci.ac.uk/file-download/82222577

Aldridge, R. W., Story, A., Hwang, S. W., Nordentoft, M., Luchenski, S. A., Hartwell, G., ... & Hayward, A. C. (2018). Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. The Lancet, 391(10117), 241-250.

Barnett, K., Mercer, S. W., Norbury, M., Watt, G., Wyke, S., & Guthrie, B. (2012). Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. The Lancet, 380(9836), 37-43.

Expected Benefits:

Main benefits include:
• To inform local NHS Practice:
KCL is the academic partner for King’s Health Partners (KHP) (https://www.kingshealthpartners.org/), which includes local NHS Trusts in partnership with the university. Findings from this study will be disseminated amongst relevant clinicians, charities and service providers in KHP, who will be able to use such outputs to provide holistic care to patients with multi-morbidities or those who have experienced social exclusion. For example, the King’s Health Partners Pathway Homeless Team has been launched within the South London and Maudsley NHS Foundation Trust, which provides health and social care for individual’s experiencing homelessness. The outputs expected from this project are directly applicable to clinical care in this area. The senior investigator for this project (Dr Jayati Das-Munshi) also works closely with the local Public Health and is on the ‘mind-body’ steering committee across KHP, which promotes best practice for integrated (mental/physical) healthcare. Therefore, outputs will inform local clinical practice, service development, KCL university-NHS partnerships and local public health.

• To inform national NHS Practice and public health:
This study seeks to increase the evidence base on the multi-morbidities in the general population and in individuals who are or have been socially excluded. Such evidence will contribute to public health policy through informing the evidence-based, which is currently scant (AoM, 2018). The findings will also help to inform how clinical care could be optimised in people living with multi-morbidities (for example through informing service development and delivery), which will benefit patients directly.

• To contribute to the academic literature on inclusion health:
There is an absence of literature on the prevalence of multi-morbidities in populations experiencing extreme social exclusion. This study will contribute to this area. Outputs will be disseminated to the research community to inform further research.

Outputs:

Planned outputs include:
1. One or two published peer reviewed reports in open access journals which will be widely disseminated to healthcare and public health practitioners, clinicians and the wider academic community, by the end of 2022;
2. At least one presentation to disseminate findings to healthcare and public health practitioners, clinicians and the wider academic community, by the end of 2022;
3. At least one online blog and social media posts (on Twitter) sharing findings to reach communities, by the end of 2022.

The findings will be submitted for publication to open-access, peer-reviewed academic journals. These will be clinical or epidemiology journals, eg the Lancet or BMJ. The estimated publication date will be in December 2022. Anticipated audiences for this manuscript will be researchers and academics, healthcare providers, clinicians, public health practitioners and policy makers.

Further research posters and/or oral presentations will be submitted to relevant conferences, including the Health Inequalities Research Network (HERON) Conference in 2020 (https://heronnetwork.com/). HERON is funded by the Wellcome Trust and is run by an academic in the Department of Psychological Medicine, IoPPN, KCL. Yearly HERON conferences are instrumental in promoting public engagement for inclusion health research and initiatives to allow cohesive and evidence-based recommendations for policy and clinical practice. By submitting research outputs from the current project to HERON, KCL are promoting impact by sharing the findings with the community, local charities, public health researchers, health practitioners and stakeholders at this event.

KCL will use institutional websites and social media accounts to share findings through links and summaries of any published work, which will promote engagement efforts to reach communities and services.

Outputs will also be fed back to NHS Digital.

All outputs (for dissemination, publication, presentations or otherwise) will only contain data that are aggregated with small numbers. Outputs will be suppressed in line with the HES Analysis Guide and will comply with the NHS Digital disclosure control rules.

Processing:

The 2014 APMS data set is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk) and the UKDS is responsible for dissemination under direction by NHS Digital. King's College London will receive the pseudonymised APMS data set. There is no facility to select individual variables. KCL will be able to download the data set from UKDS for the period specified within the Data Sharing Agreement and must securely destroy all local copies of the data set when the Agreement expires and notify NHS Digital in line with standard procedures. This 2014 version of the data set available has been redacted on Disclosure Control Procedure advice to minimise the likelihood of individuals being able to identify anyone taking part in the survey.

UKDS will transfer the pseudonymised APMS data to KCL. No other organisations will be involved in the flow of data.

KCL store data on a server site which can be remotely accessed through secure and password protected computers owned by KCL.

The APMS 2014 dataset will be used by KCL to conduct research in mental and physical health multi-morbidities among groups who are socially excluded in the UK as well as in the survey population as a whole, with a focus on the social class gradient, building on the current evidence base identified above in the 'Objective for Processing' section. The data will be analysed using STATA.

Individual level APMS data will not be linked to any other datasets.

There will be no requirement nor attempt to re-identify individuals from the data.

Data will only be accessed by individuals within KCL who have authorisation to access the data for the purpose(s) described, all of whom are substantive employees of KCL.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.


Investigating the relationship between caregiver reports of domestic violence exposure and health morbidity in a representative sample of English population. — DARS-NIC-309751-G8D4H

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2019-11-18 — 2022-05-31

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

King’s College London (KCL) is requesting access to APMS 2014 data to enable its use in a doctoral (PhD) research project. This project’s overarching aim is to investigate patient-initiated violence in informal caregiving relationships, in the context of severe mental health conditions and will comprise four individual studies. As a forerunner to the study programme, the first study (study 1) intends to investigate the relationship between caregiver reports of domestic violence exposure and health morbidity in a representative sample of English population. To this end, study 1 seeks to use both the 2007 and 2014 APMS datasets in order to examine patterns of reported domestic violence, and to explore possible associations between these reports and differences in the reported health outcomes of caregivers who do and do not report experiences of domestic violence, and compared to non-carer populations. This project is being conducted within the Psychology Department at KCL’s Institute of Psychiatry, Psychology and Neuroscience (IoPPN).

This doctoral project was proposed by researchers at KCL. KCL will therefore be the only Data Controller and also processes the data for this study. No other organisations process the data for this purpose. All research analyses will be conducted at KCL. As such, only KCL will have access to record-level data. This will only be enabled through secure, password protected KCL computers, operated by the PhD student (undertaking the doctoral research project) and the project supervisors (named above). This doctoral studentship has received full sponsorship (National Institute of Health Research Senior Investigator (SI) Award, and KCL Department of Psychology funding).

The overall research project aims to address existing gaps within the literature on the relationship between informal caregivers and violence exposure and particularly within severe mental health conditions, such as psychotic disorders. Considerable progress has been made with respect to improving understanding of key patient risk factors associated with the perpetration of violence in psychotic disorders. These factors include younger patient age, substance use, experiencing hallucinations, and persecutory delusions. It has also been well established within the literature that victims of patient-initiated violence are most often known to the perpetrator. Despite evidence highlighting that the relatives of patients, rather than strangers, are more commonly targets of patient-initiated violence, understanding of both family factors associated with this violence and the impact of violence on relatives is limited. This is due to research efforts, to date, having focused predominantly on the identification of patient risk factors.

Previous work undertaken by the research group overseeing the PhD has investigated national survey carer mental health, caregiver reports of patient violence in early and longer-term psychosis groups. However, the implications of patient violence for family functioning and the ways in which informal carers make sense of violence related events have been relatively unexplored. Some prevalence studies have estimated that patient-initiated violence towards carers of people with psychosis occurs in approximately 50-60% of informal caregiving relationships. This high lifetime prevalence rate necessitates an improved understanding of both person-based factors and contextual factors which may serve to increase the risk of carers being targets of patient violence. An improved understanding of these factors might be harnessed to inform the development of clinical interventions designed to reduce the frequency of violence and its negative impact on families and to optimise outcomes for patients and their family members. Extending previous work, the four studies set out in this doctoral project propose to improve understanding of the issues faced by individuals providing informal care generally, and those informal caregivers of patients with severe mental health conditions, including psychotic disorders. This understanding will be used to inform the development, and evaluation, of a psychological, family-based intervention aimed at reducing violence and its negative impact within the family.

The data under this agreement will be processed in the interest of the public under GDPR Article 6 (1) (e) and Article 9 (2) (j).

The first study, for which KCL are seeking access to the APMS 2014 dataset, aims to examine associations between caregiver reports of domestic violence exposure and health morbidity using APMS 2007 and 2014 data. Data will be used by KCL to enable comparisons between 3 key groups: (a) carers reporting experiences of domestic violence; (b) carers reporting no domestic violence; and (c) non-carer populations. Primary analyses will be conducted to explore differences among these 3 groups across a range of reported physical and mental health outcomes (these will include psychiatric symptomatology; reported health conditions; mental wellbeing and quality of life). Secondary analyses will explore differences between these groups in reported outcomes pertaining to other life domains (including alcohol and substance use; social support and support networks). Of importance, the 2014 survey yields greater detail in relation to the ‘caring responsibilities’ section. Specifically, the 2014 survey gathered data on the type of relationship between the patient and carer (e.g. mother, partner, etc.), and the living situation of the dyad (co-residing; living separately). This information will therefore be used to explore whether severity of outcomes (listed above) differ as a function of the living situation or type of relationship. Finally, analyses will be conducted to investigate potential differences in outcomes depending on carer demographics (i.e., whether the severity of reported outcomes differ as a function of carer’s age, gender, ethnicity, education level, and socio-economic status).

The main research questions are:
1. Do carers reporting a history of domestic violence in comparison to carers reporting no violence and non-carers, report poorer health outcomes?
2. Do carers reporting a history of domestic violence, in comparison to carers reporting no violence and non-carers, report poorer outcomes in other lifestyle domains such as alcohol and substance use, social support networks, social capital and participation, stressful life events, and debt?

Secondary research questions are:
1. In carers exposed to violence, does the severity of carer outcomes differ depending on the type of relationship between patient and carer, and the living situation of the patient and carer?
2. In carers exposed to violence, does outcome severity differ depending on the carer’s demographics (i.e., do sub-groups of carers (differing on demographics) report poorer outcomes, e.g. female carers > age 60)?
3. To what extent can carer social networks and social capital improve understanding of informal caregiving and domestic violence?

The Adult Psychiatric Morbidity Survey collects a vast amount of insightful data which is of key relevance to the proposed project’s objectives. Therefore, obtaining this data for analysis will enable achievement of the stated aims of the project. The relevant topic areas assessed in the APMS survey include:
• Caring responsibilities (frequency of care; carer and patient relationship; living situation)
• Socio-demographic variables of self-identified carers (e.g. age; gender; education level)
• Experiences of domestic and sexual abuse
• Measures of mental and physical health (e.g. psychiatric symptomatology (CIS-R); common mental disorders; physical health; mental wellbeing)
• Stressful life events
• Debt
• Alcohol and substance use
• Medication and service use
• Social support networks
• Social capital and participation

APMS 2014 data are therefore being requested from NHS Digital in order to fulfil the aims of study 1, outlined above. The data requested will be used for the purpose(s) of this project only and will not be used for any wider projects, associated work or follow-up work. The data will not be used for any commercial purposes, it will not be provided in record-level form to any third party and will not be used for direct marketing.

Expected Benefits:

The overarching aim of the related PhD studies is to improve understanding of caregiver accounts of violence exposure and their implications for health and functioning, particularly for carers with severe mental health problems. The research outputs aim to extend what is currently known about risk factors associated with violence through exploration of carer-based risk factors and contextual factors which might perpetuate risk of violence in informal caregiving relationships.

The first step in the sequence of events necessary to achieve this project’s aims will be the dissemination of the outputs described in the previous section (Section 5c). The knowledge, obtained from study 1 will also, potentially, contribute to the development of a family-based psychological intervention for mental health carers affected by domestic violence (developed at a later stage of the PhD project). As such, this project will make a distinctive contribution to the broader literature, the evidence base and the development of a targeted intervention.

Expected benefits from the dissemination of study 1, specifically, centre around improving understanding in the following ways:
a) In cross-sectional and nationally representative samples, it will provide information on health-related outcomes in carers reporting violence exposure, those carers reporting no violence, and non-carer populations;
b) It will provide information about differences in outcomes relating to other life domains between these groups;
c) It will elucidate sub-groups of carers with a history of violence exposure who may, due to socio-demography, be particularly vulnerable to poorer health-related outcomes.

Additionally, as the findings obtained from the analyses of APMS data (study 1) will help to inform aspects of the later studies to be conducted as part of the wider research project, and thereby forming an integral part of this doctoral project, benefits are expected to be multifaceted. By adding to the evidence base, the doctoral project will seek to improve the practice of professionals working with informal carers affected by violence. Benefits are also expected to reach the scientific community, through an improved understanding of a complex phenomenon. Finally, benefits are expected to reach both carer and patient communities through peer reviewed journals, mental health blogs and academic and user led conferences.

Completion of this doctoral project is also in the public interest, given that approximately 6 million people in the UK provide informal care; a figure that is anticipated to reach 9 million by 2037. The widespread phenomena of informal caregiving and evidence suggesting that the prevalence of violence is approximately 50-60% in these relationships, necessitates research efforts to understand carers’ experiences of violence. An improved understanding is essential for the planning of effective future intervention and prevention strategies, aimed at minimising the risk of violence in informal caregiving relationships.

As the research project is currently in its infancy and data analysis is yet to be conducted, it is not possible at this stage to accurately quantify the expected benefits and magnitude. That said, it is anticipated that improving understanding of the multifaceted components of informal caregiver roles, which might include experiences of victimisation and violence would be an important benefit. The findings might help to identify potential areas of unmet clinical and social need in a vulnerable group and provide support for further research resources and support programmes. As the doctoral project progresses, the expected benefits, and anticipated magnitude of said benefits, will be formalised and updates will be shared with NHS Digital accordingly.

Outputs:

A PhD thesis will be submitted in May 2022 to the relevant reviewing committee at KCL. This thesis will contain a report of the key findings from study 1, which will have utilised APMS 2014 (and APMS 2007) data for analysis. Findings will additionally be submitted for publication in a peer-reviewed journal. The target date for this expected output, depending on the time taken to access the required datasets, is likely to fall in late 2020 early 2021. The level of data contained in these outputs will be aggregated, with small numbers suppressed in line with the HES Analysis Guide referred to within the NHS Digital guidance provided to applicants.

Processing:

The 2014 APMS data set is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk) and the UKDS is responsible for dissemination under direction by NHS Digital. King's College London will receive the pseudonymised APMS data set. There is no facility to select individual variables. KCL will be able to download the data set from UKDS for the period specified within the Data Sharing Agreement and must securely destroy all local copies of the data set when the Agreement expires and notify NHS Digital in line with standard procedures. This 2014 version of the data set available has been redacted on Disclosure Control Procedure advice to minimise the likelihood of individuals being able to identify anyone taking part in the survey.

UKDS will transfer the pseudonymised APMS data to KCL. No other organisations will be involved in the flow of data.

KCL store data on an on-site server which can be remotely accessed through secure and password protected computers owned by KCL. For authorised users only, the data can be remotely accessed via secure, password protected, computers within the institutions. Data will only be accessed by individuals within KCL who are granted authorisation to access the data for the objectives described previously in this Agreement. All individuals requiring access to the data are substantive employees of KCL, or personnel (doctoral research student) working under the supervision of the stated substantive employees of KCL.

The APMS 2014 dataset will be used by KCL to conduct research into patterns of domestic violence and to explore possible relationships between caregiver reports of domestic violence exposure and health morbidity, in order to address gaps within the literature identified in the previous section (Section 5a). The nationally representative data, yielded from the 2007 and 2014 surveys, is required in order to maximise the potential to offer informed conclusions.

Individual level APMS data will not be linked to any other datasets.

There will be no requirement nor attempt to re-identify individuals from the data.

Data will only be accessed by individuals within KCL who have authorisation to access the data for the purpose(s) described, all of whom are substantive employees of KCL.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

The data will not be used for any commercial purposes, it will not be provided in record-level form to any third party and will not be used for direct marketing.


Investigating the association between X-ray guided endovascular aortic aneurysm repair and incidence of cancer — DARS-NIC-264102-D2X7J

Opt outs honoured: Anonymised - ICO Code Compliant (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2021-07-09 — 2024-07-08

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

Objectives:

This application from King’s College London is to study the potential association between X-ray guided endovascular aortic aneurysm repairs (EVAR), which expose patients to radiation both during the procedure and follow-up CT scans, and future incidence of cancer. It is hoped that defining the risk of cancer after EVAR will contribute to the process of informed consent and decision making between open aneurysm repair and EVAR.

Primary objective:
To define the relative risk of developing cancer after EVAR versus after open repair for aortic aneurysms.

Secondary objectives:
To identify the types of cancers that develop in patients after EVAR.
To determine the median intervals between radiation exposure during EVAR and development of cancer.

Lawful basis:
King’s College London’s justification for processing is GDPR Article 6 (1) (e): The processing necessary to perform this task is in the public interest and the task has a clear basis in law. The results of this study will provide information about the risks of radiation-cancer associated with EVAR. Given that an alternative is available, these results could inform decisions about which treatment should be offered to patients in future. KCL are a public authority (university) carrying out a research project.

GDPR Article 9 (2)(j): processing is necessary for scientific research purposes and shall be proportionate to the aim pursued, respect the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject. This is a scientific research project.

Ethical considerations:
The dissemination of the aggregated results of this study pose minimal risk to the public.

Potential ethical considerations are that patients in the HES registry and NCRAS did not actively give consent for their data to be used for this study, and seeking consent is not feasible due to the number of patients involved and the fact that many of these patients will already be deceased. The study team have gained authorisation to use this data under s251 approval. Potential data breaches are another ethical consideration. The study team (at KCL) will be minimising this by requesting only pseudonymised data from NHS Digital and NCRAS and only the necessary data for the analysis to be transferred to KCL. However, there will be a need for one transfer of data owed a duty of confidence (NHS number and DOB) between NHS digital and Public Health England in order to facilitate data linking. Both NHS Digital and Public Health England will then send pseudonymised data to the research team at Kings College London. The data linkage between the NHS D data and the NCRAS data will occur based on the pseudo-IDs. The pseudonymised data received by KCL will be stored on 2 encrypted password protected computers.

The study team have discussed the feasibility of the proposal with NHS digital and Public Health England, who hold and manage the HES and NCRAS databases, respectively. Both of these organisations will be named as sources of the data on any ensuing publications. Publications resulting from this data will be readily available to healthcare professionals, patients, and the public.

Where possible, the study team have sought to seek the opinions of relevant patient groups and the public on this research. The study team recently held an event at the Academic Department of Vascular Surgery attended by vascular and cardiology patient groups, as well as donors and staff from the British Heart Foundation. This study proposal was presented and discussed during a session on the effects of ionizing radiation in vascular surgery. The study has also been discussed with the local Patient and Public Involvement group for their input.

It is hoped that the data requested will allow an assessment of the relative risk of cancer after EVAR compared to open aneurysm repair. It will also inform on the most likely types of cancer.

The request is part of a PhD based at the Academic Department of Vascular Surgery (King’s College London), a British Heart Foundation centre of excellence. The PhD student is substantively employed at King’s College London as a Clinical Research Fellow. The wider project commenced in October 2018 and is investigating the effects of radiation in vascular surgery, both on patients and surgeons.

The data requested here will be used for the described segment of the project only and will have no use in any other segment of the wider project. However, the wider project, as above, commenced in October 2018 and is investigating the effects of radiation in vascular surgery, both on patients and surgeons. This mainly involves basic laboratory research and is a collaboration between the team at King’s College London and the Centre for Health Effects of Radiological and Chemical Agents (Brunel University) and the Centre for Radiation, Chemical and Environmental Hazards (Public Health England). The requested data will be used for the arm of the study investigating the long-term effects of radiation from EVAR on patients. The PhD consists of several parts - one of which depends on the requested data from NHS Digital and PHE.

The subjects in this study are all patients over 50 years old who have undergone aortic aneurysm repairs. The study arm will be made up of those who underwent an endovascular aneurysm repair (EVAR), which involves radiation, whereas the control arm is made up of patients who underwent an open aneurysm repair. Within the EVAR group, the patients can be further subdivided into simple and complex EVAR for subgroup analysis.

The purpose of this project is to investigate the association, if any, of radiation exposure during endovascular aneurysm repair (EVAR) with future development of cancer. For this the study team will be comparing a cohort of patients undergoing EVAR with a control cohort undergoing open aneurysm repair.

Patient identifiers (DOB and NHS numbers) will be required in order to facilitate linking of HES data with the National Cancer Registration and Analysis Service (NCRAS) database. Patient demographics, age, past medical history and social history are also required to account for confounding factors during statistical analysis.

Once the initial transfer from NHS digital to PHE (NCRAS) is complete, patient identifiers will be removed, and the research group will receive pseudonymised HES data.

The number of years requested is based on the following power calculation.
To achieve 95% confidence, 80% power assuming proportion of deaths caused by any cancer of 20.9% (EVAR) and 19.7% (open) – these figures are taken from the currently available literature.
Recommended sample size = 39,000 patients (13,000 EVAR, 26,000 open)
+ 3% for attrition of data = 40,170 (13,390 EVAR, 26,780 open)
Based on approximate number of patients undergoing EVAR and open aneurysm repairs in England each year, 18 years of data will be required to achieve these number.

Only data that will be required from statistical analysis to answer the study question has been requested. Patient identifiers will be required for data linkage with NCRAS so once the HES data has been extracted by NHS Digital based on ICD-10 and OPCS-4 codes, the relevant identifiers (NHS Number, DOB) and pseudonymised data (Date of Surgery and Study ID) will be passed to PHE. However, beyond the first transfer of data from NHS digital to PHE, patient identifiers will not be used, and the resultant HES data will be pseudonymised before being sent to the research team at KCL.

Data Flow

The steps involved in this are as follows:
1) King’s College London provides inclusion criteria to NHS Digital
2) NHS Digital identifies patients from HES according to ICD-10 and OPCS-4 codes
3) NHS Digital transfers identifiers of those patients only (NHS number, DOB) along with pseudonymised data (date of surgery, pseudo ID) to Public Health England. This will be done under DARS-NIC-467721
4) NHS Digital transfers patient demographic and surgical data and pseudo IDs to King’s College London. This will be done under DARS-NIC-264102 (THIS AGREEMENT)
5) Public Health England extracts cancer data relevant to these patients from NCRAS
6) Public Health England sends cancer data and pseudo IDs to King’s College London
7) Linking of demographic, surgical and cancer data at King’s College London (via pseudo study ID)

The sole data controller will be the research team at King’s College London as previously detailed. The other organisation involved is National Cancer Registration and Analysis Service (NCRAS), based at Public Health England (PHE). The team at PHE will provide cancer data from NCRAS pertaining to the patients identified from the HES database.

The primary investigator is a substantive employee of King’s College London and has a clinical role at St Thomas Hospital. No other St Thomas Hospital staff will be involved in the project. The PI will lead on the processing of the data and will be responsible for any output from this project.

No other organisations will be involved in accessing or processing this data. The Centre for Health Effects of Radiological and Chemical Agents (Brunel University) is involved in the wider project and their role is specifically in the processing of biological samples. They will not be involved in the processing or decision making regarding NHS Digital data.

No funders/commissioners will be involved in the project.

******This application is for the flow of data to KCL.********

Expected Benefits:

It is anticipated the data will inform on the risk of radiation-related cancer after endovascular aneurysm repairs and be beneficial when informing and consenting patients for operations and help them decide, with the clinical team, which procedure is most appropriate for them. It is anticipated the information will also inform the vascular community about the long-term risks of these procedures and contribute to the debate about the cost effectiveness of endovascular aneurysm repairs. The dissemination of the results will be in the public interest as it will provide transparency around the knowledge base upon which treatment decisions are taken.

Ultimately, patients will be reliably informed of their risk of developing cancer after endovascular aneurysm repairs. They will be able to use this information in deciding whether to accept that risk or opt for an open surgical repair, or indeed to decline surgery altogether.

It is hoped the outputs will provide a calculation of the relative risk of developing cancer after having an endovascular aneurysm repair versus and open aneurysm repair. After accounting for confounding factors, a comparison will be made between the two procedures, thus achieving the stated purpose.

It is hoped that the benefits of this project will be to add to the current knowledge base and better inform patients with abdominal aortic aneurysms about their options and the risks involved.

The research team are clinicians in vascular surgery and therefore will be able to directly use the outputs of this project to inform their patients. Hopefully, dissemination of data will allow other clinicians to do the same.

******This application is for the flow of data to KCL.********

Outputs:

The data will be analysed by the research team at King's College London and its conclusions will be published in the medical literature in adherence to local publication policies. The outputs of this project will also contribute to a PhD thesis. All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. NHS digital and PHE will be named as sources of the data on any resulting publications. The conclusions of the study will also be disseminated by way of presentations at vascular surgery conferences such as the Vascular Society of Great Britain and Ireland, Charing Cross Symposium, and the European Society of Vascular Surgeons. As a result of participation at these conferences, the headline messages from the project may be shared on social media platforms.

By these means of publicly available medical journal publications and conference presentations, the key message of the relative risk of radiation-related cancer after endovascular aneurysm repairs will be disseminated. This information will be beneficial when clinicians are informing and consenting patients for operations and help them decide, with the clinical team, which procedure is most appropriate for them. Furthermore, these conclusions will add to the current knowledge base and better inform patients with abdominal aortic aneurysms about their options and the risks involved.

The raw data will be deleted at the end of the study. The target date for completion of the study is October 2023.

One member of the research team who will be involved in data analysis is currently undertaking a PhD and is a substantive employee of King's College London. The outputs of this project will contribute to his PhD studies.

******This application is for the flow of data to KCL.********

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)”.

Patients undergoing aortic aneurysm repair either by an open approach (OAR) or endovascular approach (EVAR) between January 2000 and December 2018 will be identified by NHS Digital from the Hospital Episode Statistics (HES) dataset using OPCS codes.

These patients will be over the age of 50, as those under the age of 50 have a different pathology which makes them unsuitable for this study. This should provide approximately 40,000 patients as per the sample size calculation detailed above.

Once the patients have been identified from HES by NHS Digital, the national opt-out will be applied to remove any patients who have requested an opt-out. Patients aged under 50 years at time of operation and patients having their operation outside of England will also be excluded at this stage.

A list of the remaining patient NHS numbers, dates of birth and a unique pseudo ID will be transferred to Public Health England (PHE) by secure electronic transfer agreed between NHS Digital and PHE. This will be done under DARS-NIC-467721
Patients will be identified by ICD-10 diagnostic codes for aortic aneurysm and also by OPCS-4 for various types of aortic aneurysm repair as follows:
ICD-10 Diagnostic codes – 1714, 1719
OPCS-4-Procedural codes – L184, L185, L186, L188, L189, L194, L195, L196,L198, L199, L231, L236, L238, L239, L254, L258, L259, L49, L271, L275, L276, L278, L279, L281, L285, L286, L289

At PHE, the National Cancer Registration and Analysis Service (NCRAS) will perform a look up on the cancer registry using deterministic matching based on NHS number and date of birth. This process will identify which patients developed cancer after their procedure. Follow-up on NCRAS will continue to December 2020 such that any patients from the original HES dataset who have a diagnosis of a primary tumour as per future NCRAS data releases can be included in the analysis.

PHE will then send the cancer data including date of diagnosis, type and stage of cancer to King’s College London (KCL) in a pseudonymised format using pseudo IDs.

NHS digital will also send the demographic (date of birth, sex), clinical details (e.g. smoking status, diabetes, heart disease) and operative details to KCL in a pseudonymised format using the same pseudo IDs. (THIS WILL BE DONE UNDER UNDER DARS-NIC-264102 - THIS AGREEMENT)

Linking of pseudonymised data from HES and NCRAS will then be performed at KCL. At this point, dates of surgery will be compared with dates of cancer diagnosis to allow exclusion of patient with pre-existing cancers or previous radiotherapy treatment. An interval period between date of surgery and date of cancer diagnosis will also be applied to account for concurrent diagnoses.

******This application is for the flow of data to KCL.********


Contextual determinants and participant perspectives on the common mental disorders and access to psychological treatments in UK ethnic minorities: mixed methods study utilising data from the Adult Psychiatric Morbidity Surveys (APMS). — DARS-NIC-195618-N6T1R

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007; Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2018-12-03 — 2021-12-03

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

King’s College London (KCL) is requesting APMS 2014 data for use in a doctoral research project investigating mental health inequalities in ethnic minority communities in the UK, titled Contextual determinants and participant perspectives on the common mental disorders and access to psychological treatments in UK ethnic minorities: Mixed methods study utilising data from the Adult Psychiatric Morbidity Surveys (APMS). The project is being conducted at the Department of Psychological Medicine, at the KCL Institute of Psychiatry, Psychology, and Neuroscience together with the National Centre for Social Research.

The research project was a successful proposal to a studentship competition held by the London Interdisciplinary Social Science Doctoral Training Partnership (LISS DTP). LISS DTP objectives include addressing key research priorities and global societal challenges across a breadth of interconnected social science disciplines, enabling postgraduate research at the interface with health, the natural sciences, engineering, and the arts and humanities. The programme trains social science research students to work collaboratively with peers and service users alike, and to have a global outlook in career development, employability, entrepreneurship, public engagement, and impact.

LISS DTP’s Collaborative (CASE) Studentship programme promotes partnerships between social scientists at participating universities and end-user, non-academic partner institutions, to initiate longer-term partnerships and to ensure the impact of research. More information can be found on the LISS DTP website (https://liss-dtp.ac.uk/case-studentships-student-applicants/#1513161186335-8d31ca62-50b7).

The project in this application is between university partner King’s College London (KCL), the Data Controller, and the non-institutional partner, National Centre for Social Research (NatCen), the Data Processor. The project research analysis work will be conducted at KCL, where the student is based and which will direct the research work overall. The role of NatCen is secondary and will be to support the student in managing the data towards the project (such as through data linkage activities) and provide the student with general training in research skills, developing studies, and translating research into policy. Therefore NatCen remains only a Data Processor for the purposes of this project. The role of NatCen is to support the student to manage data and develop the skills necessary to best analyse and communicate the results of this research project.

The aim of the research work is to address the longstanding concerns in the UK that Black and Minority Ethnic people experience inequalities in access to mental health treatments. Targeting policy to address inequalities in these groups are part of NHS strategy on mental health. A number of reasons for low levels of access to treatments by ethnic minority groups in the UK have been proposed in recent research. This study seeks to establish reasons behind the treatment gap for CMD in ethnic minority groups within the UK.

The project combines a quantitative study and qualitative study to investigate the contextual determinants and participant perspectives on the common mental disorders and access to psychological treatments in UK ethnic minority groups. The quantitative analysis part of the project seeks to utilise data from the Adult Psychiatric Morbidity Surveys (APMS).
This research seeks to assess these aims:
1. Prevalence, risk factors and trends in common mental disorders (CMD) stratified by ethnicity (particularly individual-level risk factors in ethnic minority groups).
2. Differences in reported access to treatments for each main ethnic minority group within APMS, and individual-level predictors for this.
The research seeks to use individual-level data from APMS 2007 and 2014 linked to area-level information, to assess:
3. Association of area-level deprivation and proportion of ethnic minorities with outcomes: prevalence of CMD and reported access to treatments for CMD.
Using a nested qualitative study (protocol to be developed for later approval):
4. To gain an understanding of mental health care access barriers in people purposively sampled from high and low own ethnic density areas.

The work aims to develop understanding and evidence base for inequalities to access in mental health treatment. Improving the equality of access to and outcomes in mental health services for ethnic minority groups is a policy focus area for the NHS, as outlined in the Five Year Forward View for Mental Health.

This new investigation seeks to build on recent analysis of APMS data as well as wider research in trends in mental health problems and access to mental healthcare by ethnic minority groups in the UK. Black people are more likely to experience complex pathways into mental healthcare, with less contact with primary care and more experience of coercive pathways. Recently released data from the 2014 APMS indicated that Black respondents were less likely to receive treatments for Common Mental Disorders (CMD) than White British respondents. An analysis utilising consecutive APMS surveys indicated that Black respondents with CMD were less likely to be prescribed antidepressants than White respondents and less likely to have reported seeing their GP for a mental health problem. Further investigation into the reasons behind this is an objective of this project. Similarly, authors of a nationally representative survey of ethnic minorities living in the UK, noted low levels of psychological service access by Indian, Pakistani and Bangladeshi people, despite high levels of primary care consultation.

APMS 2014 data is therefore required from NHS Digital in order to carry out the above outlined study in order to investigate these key research questions further through analysis of a nationally representative survey into CMD.

Expected Benefits:

These research outputs seek to directly increase the evidence base in mental health inequalities in England for ethnic minority groups, for whom there are longstanding concerns about access to mental health treatment. By increasing the evidence base, an indirect objective is to contribute further to improved public health policy and programming. The eventual aim would be to achieve benefits to health through support for improved access to services and therefore quality of life for these groups.

The sequence of events required to achieve this would first be delivering outputs, conducting stakeholder mapping to identify relevant stakeholders with whom to discuss results, engagement with stakeholders on results to discuss their uptake. At this point, actual expected benefits and magnitude are as yet not quantified given data analysis has not been conducted. However through the course of the doctoral project a more detailed dissemination plan focusing on policy recommendations that emerge from the research will be formulated to formalise these steps, and progress will be shared with NHS Digital.

Outputs will be primarily discussed and presented in engagement through the Health Inequalities Research Network (HERON), led by the project co-supervisor. HERON is an international public engagement network funded by the Welcome Trust, aimed at people involved in action and research in inequalities in health and health service use (further information linked here). HERON conferences, seminars and talks are hosted with a range of stakeholders including voluntary sector advocates and health practitioners. It is reasonable to expect these benefits will be realised primarily because the research results will have policy implications for ethnic minority groups already targeted for policy focus for improved health outcomes, and further because the dissemination strategy is working closely with established networks such as HERON to leverage impact.

As coordinated by the HERON network, the project results will be disseminated with organisations tackling health inequalities in ethnic minority communities such as Black Thrive, as well as with practitioners through organisations such as King’s Health Partners.

The target policymakers for this research project would be Public Health England (PHE), and the Department of Health and Social Care. Engagement with research is already outlined as a responsibility for PHE, therefore efforts will be made with this project to communicate with relevant teams working on mental health to ensure any policy recommendations that emerge towards reducing mental health inequalities for ethnic minority communities, a target group for PHE, can be followed up.

Engagement with local BME service user groups will enhance knowledge exchange with wider audiences. Further engagement will also be strategised with NatCen and LISS DTP teams.

Outputs:

It is hoped that the outputs of this project will contribute towards a better understanding of the issues facing those from ethnic minority backgrounds who access pyschological treatments. Through publication (in peer reviewed journals), promotion (through institutional websites/social media) and presentations (through the Health Inequalities Research Network) the findings will influence policy makers with responsibility for tackling health inequalities.

A doctoral thesis will be submitted to the relevant reviewing committee at the KCL Institute of Psychiatry, Psychology, and Neuroscience in August 2021, which will cover all key findings of the study. Once assessed, the findings will be submitted for publication to open-access, peer reviewed journals, with an estimated publication date of January 2022.

Further research conference posters and/or oral presentations will be submitted to the Health Inequalities Research Network Conference in October 2019.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide/compliant with the MHSDS disclosure control rules including suppression and rounding.

For each paper published on the research, short presentations will be developed to summarise the findings for different stakeholders, including local BME service user groups.

Institutional websites/ social media accounts will be used to promote findings through summaries or links to published work - for example host blog posts on King’s Health Partners and NatCen websites, and through institutional Twitter accounts to promote engagement efforts so that research benefits reach communities to support improved health outcomes.

All outputs published will be in the form of aggregated outputs with small numbers suppressed (as is in line with the HES-Analysis guide).

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

The 2014 APMS dataset is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk ) and UKDS are responsible for dissemination under direction by NHS Digital. UCL will get the whole dataset; there is no facility to select individual variables. They will be able to download the dataset from UKDS for the period specific within the DSA and they must securely destroy all local copies of the dataset when the DSA expires and notify DARS in line with standard procedures. This 2014 version of the dataset available via DARS has been redacted on Disclosure Control Procedure advice to minimise the likelihood of individuals being able to identify anyone taking part in the survey.

Record level APMS 2014 data is requested, which will flow from NHS Digital to KCL, the Data Controller in this application. NatCen, the Data Processor in this project, are already data custodians of APMS, therefore no flow is required to enable data access for project research at NatCen.
KCL and NatCen store data on a server on site which can be remotely accessed via secure, password protected computers supplied by the institutions.
Data will only be accessed by individuals within KCL and NatCen who have authorisation to access the data for the purpose(s) described, all of whom are substantive employees of KCL and NatCen or personnel (research student on LISS DTP ESRC studentship) working under supervision on behalf of KCL and NatCen.

There will be no requirement nor attempt to reidentify individuals from the data.

The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

Individual level APMS data will be linked to Office for National Statistics Middle Layer Super Output Areas (MSOA) (approval depending) - which are geographical areas comprising a mean of 7200 people residents in an area - to derive area-level deprivation and percentage of ethnic minorities resident in the area, using appropriate look up files (further information on ONS UK census geography can be found on their website, linked here: https://www.ons.gov.uk/methodology/geography/ukgeographies/censusgeography).

The APMS 2014 dataset is requested to conduct research in mental health problems and access to mental healthcare in ethnic minority groups in the UK, building on the gaps identified in the Objective for Processing section. Nationally representative data is required to reach generalisable conclusions which are relevant for public health policy and programme development in this sector of health. Given the APMS data is already pseudonymised, the required degree of data minimisation has already been ensured.

Only KCL and NatCen (who are already data custodians of the APMS ) will have access to record level data, which will only be enabled through secure, password protected KCL computers operated by the research student and supervisors.
The research is funded by the Economic and Social Research Council (ESRC), which was secured after KCL and NatCen


Domestic and sexual violence: exploring associations with mental health — DARS-NIC-188499-K4G0M

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2019-03-07 — 2022-03-06

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

The overall objective is to improve understanding of the associations between mental disorders and (1) experiencing sexual violence and (2) perpetrating domestic violence.

Previous work by the Principle Investigator (PI) has highlighted several evidence gaps regarding a potential association between mental disorders and domestic and sexual violence. These include a lack of evidence regarding (i) associations between experiences of sexual violence and mental disorder (Oram et al 2017); and (ii) associations between recent perpetration of domestic violence and mental disorder (Oram et al 2014). Other limitations of previous studies include (i) unrepresentative samples; (ii) small sample sizes; and (iii) lack of data collected on potential confounder and mediators.

Use of the 2014 Adult Psychiatric Morbidity Survey will allow the above evidence gaps to be addressed. The survey also has important strengths relative to other datasets: it uses a nationally representative sample of households in England and Wales, has a relatively large sample size, and collects data on a wide range of variables.

All analyses will take place at King’s College London, in the UK. No other organisations (e.g. CCGs, local authorities) will be involved in the proposed analyses.

REFERENCES

Oram, S., H. Khalifeh and L. M. Howard (2017). "Violence against women and mental health." The Lancet Psychiatry 4(2): 159-170.

Oram, S., K. Trevillion, H. Khalifeh, G. Feder and L. Howard (2014). "Systematic review and meta-analysis of psychiatric disorder and the perpetration of partner violence." Epidemiology and psychiatric sciences 23(04): 361-376.

Outputs:

Outputs will include (1) a scientific paper on the prevalence and risk of domestic violence perpetration among people with mental disorders (target submission date September 2019); (2) a scientific paper on the prevalence and risk of sexual violence among people with mental disorder (target submission date December 2019).

Scientific papers will be submitted to peer-reviewed academic journals; targets include PLOS Medicine, The Lancet Psychiatry, the British Journal of Psychiatry, Epidemiology and Psychiatric Sciences, and Trauma Violence and Abuse.

Papers will also be submitted to academic conferences, including the 2019 International Association of Women’s Mental Health and the 2019 International Federation of Psychiatric Epidemiology.

Scientific papers will be published on an open-access basis where possible (i.e. where funds are available and/or where an article processing charge fee waiver is obtained). If funds/waivers are not available, a pre-print version of the article will be made available on an open-access basis from the KCL PURE repository.

Outputs will contain only aggregate level data with small numbers suppressed in line with Code of Practice for Official Statistics and the ONS Statistical Disclosure Control for tables produced from surveys.

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

The 2014 APMS dataset is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk ) and UKDS are responsible for dissemination under direction by NHS Digital. KCL will get the whole dataset; there is no facility to select individual variables. They will be able to download the dataset from UKDS for the period specific within the DSA and they must securely destroy all local copies of the dataset when the DSA expires and notify DARS in line with standard procedures. This 2014 version of the dataset available via DARS has been redacted on Disclosure Control Procedure advice to minimise the likelihood of individuals being able to identify anyone taking part in the survey.

The data will be transferred from NHS Digital to King’s College London (UK) where the data will be stored and processed. No further data flows will occur.

The dataset that is being requested by King’s College London is anonymised and will contain no identifiers when it is transferred from NHS Digital to King’s College London.

The legal basis for accessing this data is Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii).

No data will be accessed from outside the UK, and no one who is not a direct employee of King’s College London will be permitted to access the data.

The proposed analyses do not involve linking or comparing the 2014 Adult Psychiatric Morbidity Survey with other datasets.


The analysis of 2014 APMS data to understand the mental health and wellbeing of veterans: A King's Centre for Military Health Research proposal — DARS-NIC-183359-N7P0D

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-04-25 — 2022-03-24

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Yielded Benefits:

Expected Benefits:

MILITARY EMPLOYMENT STUDY

The mental health impacts of unemployment and poor work performance are legion. The UK Government has clearly stated its intent to ensure that as many people as possible are able to work in order to ensure the economy is buoyant and that individuals are able to progress with their, and their families, lives. Furthermore, the military covenant directs that military veterans, whatever their age, should be at ‘no disadvantage’ as a result of their military service and this study will provide an insight into whether veterans are indeed disadvantaged in terms of their post-service employment. The results from this work will be able to inform the planning and delivery of health care services, interventions and policy reform.


MILITARY DEMENTIA STUDY

The prevalence of dementia is increasing with the number of people living with dementia in the UK estimated to reach over 1 million by 2025. With approximately 3-5 million veterans residing in England currently, it is imperative to establish the possible link between mental ill health and dementia in this specific group of elderly in order to identify if there may be a need for specific services for this group. The UK Government has published the military covenant which directs that military veterans, whatever their age, should be at ‘no disadvantage’ as a result of their military service. The results from this work will be able to inform the planning and delivery of health care services, interventions and policy reform.


MILITARY MENTAL HEALTH-FEMALE STUDY

This study will be used to quantify mental health need amongst the spouses/partners of UK military personnel and first responders compared to women in the general population. This will be used to inform support services for these populations and to conduct further research into the causes of poor mental health within these groups.


MILITARY MENTAL HEALTH-MALE STUDY

This study will help develop the ideas originally put forward by Woodhead et al. in 2011 and contribute to the knowledge of veteran specific outcomes in terms of healthcare utilisation and mental health. Developing this understanding and sharing it with military charities will allow them to target their spending on appropriate interventions within those groups most in need.


MILITARY DVA STUDY

The research will provide the first population level information on prevalence of and risk factors for DVA in the UK military compared to the general population, which will inform the need for prevention and support services and the development of evidence-based risk assessment for DVA perpetration and victimisation in this population, and identify potentially modifiable risk factors which can be targeted by interventions to reduce risk of DVA.

This research has the potential to reduce the harm resulting from DVA to serving and ex-serving military personnel and their families, both perpetrators and victims, and the costs associated with it. The findings from this study will provide the first UK evidence to inform expert consensus on good practice in DV prevention and management in this population and a framework for change in practice and policy will be developed along with educational materials to skill the multiagency workforce in how to identify and manage DV in this population.

Outputs:

MILITARY EMPLOYMENT STUDY
The findings of this study will be published in international peer reviewed scientific journals and presented at conferences worldwide within one year of receiving the data. Once peer-reviewed and published, it will form a part of newsletters that are shared with the military cohorts involved in longitudinal research, such as the health and well-being survey and ADVANCE study. The newsletter will also be available via the website (www.kcl.ac.uk/kcmhr). The work will be shared with military charities such as Forces In Mind Trust, Combat Stress and Help for Heroes with the hope that this research will have a positive impact on their work with serving and ex-serving personnel.

The work may also be published in a PhD dissertation.


MILITARY DEMENTIA STUDY
The findings of this study will be published in international peer reviewed scientific journals and presented at conferences worldwide within one year of receiving the data. Once peer-reviewed and published, relevant information will be included in newsletters that are shared with the military cohorts involved in longitudinal research, such as the health and well-being survey and ADVANCE study. The newsletter will also be available via the website (www.kcl.ac.uk/kcmhr). The work will be shared with military charities such as Forces In Mind Trust, Combat Stress and Help for Heroes with the hope that this research will have a positive impact on their work with serving and ex-serving personnel.

The work may also be published in a PhD dissertation.


MILITARY MENTAL HEALTH-FEMALE STUDY
The findings of this study will be published in international peer reviewed scientific journals and presented at conferences worldwide within one year of receiving the data. Once peer-reviewed and published, it will form a part of newsletters that are shared with the military cohorts involved in longitudinal research, such as the health and well-being survey and ADVANCE study. The newsletter will also be available via the website (www.kcl.ac.uk/kcmhr). The work will be shared with military charities such as Forces In Mind Trust, Combat Stress and Help for Heroes with the hope that this research will have a positive impact on their work with serving and ex-serving personnel.

The work may also be published in a PhD dissertation.


MILITARY MENTAL HEALTH-MALE STUDY
The findings of this study will be published in international peer reviewed scientific journals and presented at conferences worldwide within one year of receiving the data. Once peer-reviewed and published, it will form a part of newsletters that are shared with the military cohorts involved in longitudinal research, such as the health and well-being survey and ADVANCE study. The newsletter will also be available via the website (www.kcl.ac.uk/kcmhr). The work will be shared with military charities such as Forces In Mind Trust, Combat Stress and Help for Heroes with the hope that this research will have a positive impact on their work with serving and ex-serving personnel.

The work may also be published in a PhD dissertation.


MILITARY DVA STUDY
The findings of this study will be published in international peer reviewed scientific journals and presented at conferences worldwide within one year of receiving the data. Once peer-reviewed and published, relevant information will be included in newsletters that are shared with the military cohorts involved in longitudinal research, such as the health and well-being survey and ADVANCE study. The newsletter will also be available via the website (www.kcl.ac.uk/kcmhr). The work will be shared with military charities such as Forces In Mind Trust, Combat Stress and Help for Heroes with the hope that this research will have a positive impact on their work with serving and ex-serving personnel.

The work may also be published in a PhD dissertation.


In order to protect patient confidentiality in publications resulting from analysis of APMS data users must:
• guarantee that any outputs made available to anyone other than those with whom this agreement is made, will meet required standards, including the guarantee, methods and standards contained in the Code of Practice for Official Statistics and the ONS Statistical Disclosure Control for tables produced from surveys;
• apply methods and standards specified in the Microdata Handling and Security Guide to Good Practice for disclosure control for statistical outputs.

Processing:

The 2014 APMS data was collected by NATCEN on behalf of NHS Digital. A minimised dataset (having gone through Disclosure Control Procedure advice) is held at UK Data Service for dissemination under direction by NHS Digital, however this does not contain the military specific fields listed in the objective for processing section. Under this agreement, NATCEN, under direction from NHS Digital, will produce and disseminate a bespoke extract of 2014 APMS data which will include the military fields specified to King’s College London. This data consist of personal health care data of a pseudonymised and sensitive nature.

Data will be securely stored on a dedicated server which is regularly audited by MoD data security specialists. All data are stored in an encrypted form using an AES256 encryption algorithm. Only named and vetted King’s College London staff who have signed a confidentiality agreement will have access. All data will be stored on a virtual server managed by King’s College London IT services. The King’s servers are located and backed up both on the Strand campus and Slough premises, on physical servers locked in a secure area so data isn’t compromised. A regular backup schedule is in place.

No data will be linked to patient records. No data will be passed on to other organisations. No attempts will be made to identify participants from the dataset.

The data processing at KCL will only be carried out by substantive employees of KCL or PhD students with a signed contract with KCL. All individuals will be expected to have completed KCL’s GDPR training and NHS Level 1 Data Security Awareness Training and who have confirmed in writing they have read and understood the protocols outlined and referred to in the Data Security and Protection Toolkit.

The data will be held as an encrypted file on KCL’s secure network drive. The encrypted file will be held in an access-controlled area of the network drive and the data will be accessible to authorised study personnel only, by means of a password or a recovery key. All users have their own username and password, and these will never be shared. Access to the data for the study will be cancelled as soon as a user leaves the study, KCL, or if they are absent for a long period.

Data will be stored on servers owned and managed by KCL, within the JISC Southern Data Centre. Only individuals with the administrative rights to those servers will be able to access data stored on them. The only individuals with those administrative rights are KCL’s IT Computer & Storage team. JISC is a United Kingdom not-for-profit company whose role is to support post-16 and higher education, and research, by providing relevant and useful advice, digital resources and network and technology services, while researching and developing new technologies and ways of working.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).


HES and NICOR data linkage for cardiac failure population analysis — DARS-NIC-174209-R8G8N

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2020-10-20 — 2021-10-19

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. HES:Civil Registration (Deaths) bridge
  2. Hospital Episode Statistics Admitted Patient Care

Objectives:

There are an estimated 81,000 people living with heart failure, with admissions accounting for an estimated 1 million inpatient bed-days (around 2% of the entire NHS total). Up to 70% of these costs are due to hospitalisation costs, so attempts to reduce costs must be focused on reduced admissions.

King’s College London (KCL)* requires 5 years of HES data (linked with NICOR data) for use in a research study quantifying heart failure patients who have to deal with repeat readmissions and evaluating the risk factors for repeat readmissions.

*Please note: KiTEC (King’s Technology Evaluation Centre) is a part of King's College London (KCL), based in the School of Biomedical Engineering & Imaging Sciences. The King’s Technology Evaluation Centre (KiTEC) is a collaboration between several King’s College London departments and the Medical Physics Department of Guy’s and St Thomas’ NHS Foundation Trust (GSTT) Kings Collage London are the Data Controller for KiTEC. All analysis will be done within KiTEC and no other part of KCL will be involved in this project. All KiTEC staff are employed by KCL and KiTEC is covered by KCL’s employers, public and professional liability insurance. For clarity, the term KCL has been used in all instances.

KiTEC is King’s College London’s Health Technology Assessment Centre (HTA) with experience in carrying out Medical Technology (MedTech) evaluations. It is a collaboration between the King’s College London School of Biomedical Engineering & Imaging Sciences, the School of Population Health and Environmental Sciences, and King’s Health Economics.

The National Institute for Cardiovascular Outcomes Research (NICOR) based within Barts Health NHS Trust has been added as a Data Processor as they will be receiving from NHS Digital a bridging file of pseudonymised HES-IDs derived from the NICOR cohort Patient Identifiable data in order for NICOR to create a data set for KiTEC to link to the 5 years of pseudonymised HES Data being provided directly to KiTEC from NHS Digital.

Heartfelt Technologies (a commercial company based out of the University of Cambridge) expressed mutual interest to KCL (as part of a workshop on innovation organised by the Health Foundry) regarding this project with the aim of establishing an accurate picture of repeat readmissions in heart failure patients, and the costs incurred by avoidable readmissions. Heartfelt Technologies has developed an in-home monitoring device for heart failure patients. Heartfelt Technologies wish to understand various aspects of the likely target patient population, in order to ascertain which patient groups are most likely to benefit from the technology, and in which patient groups the greatest avoidable costs arise that their technology may assist in reducing. KCL agree that this is a useful line of enquiry but also believe that many other research questions can be answered using the requested data. The primary goal of this research is to provide health benefit to heart failure patients and KCL believe that several journal articles can be developed using the requested data.

KCL briefly searched existing literature discovering that more comprehensive answers could be found by using registry data, specifically by linking the HES and NICOR datasets. Due to the significant cost burden heart failure admissions place on the NHS, it is expected that KCL's research - if able to identify a sub-population responsible for repeat hospital admissions - will identify an unmet need with potential savings leading to a benefit to health and social care. The outcome of the publication will go as far as identifying this unmet need and not a solution or a product for it. It is therefore, not related to any commercial gain for Heartfelt Technologies.

Heartfelt Technologies have stated that they will not be the data controller and will have no involvement in the analysis or processing of the data. Heartfelt Technologies will act as research collaborators in an advisory role only (having expressed mutual interest to KCL to start this project), providing input on statistical analysis methodologies, but will not have access to the data, do not have an active decision-making role and KCL will remain in complete control of the data analysis plan. Moreover, although Heartfelt have provided their thoughts on a potential statistical analysis, KCL have developed the analysis plan independently to answer multiple research questions. KCL’s statistical analysis plan will both inform about current rehospitalizations in subgroups of populations and generate answers to other questions of interest to KCL. For example, KCL will also look to build a predictive model to enable the accurate prediction of short term re-hospitalisation (and death) during the first year from the start of the follow-up process.

KCL will not deliver an internal report to Heartfelt Technologies; the only output will be a publication (or publications) in an open access journal. These publications will focus entirely on the unmet need of identifying the distribution of and risk factors for repeat readmissions in heart failure patients and prediction of hospitalisations. The publication will not focus on any technology and will be of no more relevance to Heartfelt Technologies than any other company or research group working on the field of heart failure. Heartfelt Technologies hope to find out it if there is a clinical need to be addressed by the technology which will help these patients and the NHS.

Heartfelt Technologies have agreed to fund the costs of obtaining and linking the data only and KCL will not receive any other funding for this project (See SD3). Heartfelt Technologies will benefit from this research as it will allow them to focus their device to the patient groups that will find it of most benefit. This will also allow for more accurate cost modelling. This is the first project of this kind KCL have undertaken and the benefit to KCL is in demonstrating their ability to carry out this kind of research, plus generating high quality articles for publication. KCL are named as Data Controller and Data Processor. No KCL staff are receiving any reimbursement from Heartfelt Technologies for analysing the data.

The study will test the hypothesis that there are specific risk factors associated with repeat readmissions. It is KCL's hypothesis that a minority of patients account for the majority of re-hospitalisations, and therefore are at higher risk for worst clinical outcomes and the majority of the cost implications. Real world data are becoming an important source of information for patient outcomes and combining two complementary registries is a novel way to conduct research. There is a notable lack of evidence on both the frequency and distribution of readmissions, particularly in the UK, and very little information on risk factors for readmissions.

By identifying risk factors, it will become apparent which, if any, are avoidable. It will then be possible to calculate the potential cost savings associated with preventing such avoidable admissions. Heartfelt Technologies research questions include:
• What is the distribution of hospital admissions on a per-patient basis over the average life expectancy for this patient cohort?
• What are the objective patient selection criteria that capture the maximum number of repeat-admissions and minimum number of single-admission patients?
• What is the distribution of further admissions following that selection point?
• What are the symptoms, or clusters of symptoms, that correlate between hospitalisation events on a per-patient basis?
• What is the clinical utility of peripheral oedema monitoring in predicting heart failure readmission?

This study is the first of its kind – there has been no preliminary or background work for this research. The study is not part of a bigger study.

HES data is required, across a 5-year period, in order to identify patients who have multiple admissions for heart failure, as well as the distribution and dates of admissions. NICOR offers classification of peripheral oedema which can be used, along with other clinical parameters, to identify patients that are more likely to be readmitted for heart failure. Linking this data will allow us to determine whether oedema monitoring can reduce emergency readmissions for heart failure. KCL will also quantify which population characteristics influence the chance of re-admission for heart failure. Quantifying the impact of age, sex and comorbidities is vital to ensure that support for patients with heart failure is appropriately targeted. Controlling for comorbidities and case-mix also allows KCL to quantify the impact of differences in socioeconomic status on access to care and outcomes. They will then determine the costs associated with patient subgroups. The research will identify groups that would benefit from existing NHS pathways to improve health outcomes in the most vulnerable and the cost implications of changes to care pathways.

This agreement is for research. Therefore the lawful basis for processing data is GDPR article 6(1)(f): Processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child. NHS Digital have assessed the KCL Legitimate Interests Assessment against the ICO’s checklist (https://ico.org.uk/for-organisations/guide-to-the-general-data-protection-regulation-gdpr/lawful-basis-for-processing/legitimate-interests/) and are content that all requirements are met.

As the research involves health data, which is included in the definition of special categories of personal data, it requires an additional condition for processing. Based on guidance, for health research this is article 9(2)(j), which details that processing is necessary for scientific and research purposes, subject to appropriate safeguards.

The legal basis for the flow of identifiable data data from NICOR to NHS Digital are section 251 support, and the Legal Basis for Processing are GDPR Articles 6(1)(f) / Article 9(2)(j).

HES DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, you must make sure that:
· cell values from 1 to 7 are suppressed at a local level to prevent possible identification of individuals from small counts within the table.
· Zeros (0) do not need to be suppressed.
· All other counts will be rounded to the nearest 5.
Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

Expected Benefits:

Study findings will be instructive to clinicians treating heart failure patients in terms of highlighting risk factors for avoidable repeat readmissions. There is currently a lack of evidence on risk factors for readmissions. These findings will also highlight possible opportunities for remote care and telehealth initiatives that could prevent readmissions. The logical sequence of events would include the effective dissemination of KCL's findings, an interpretation of them leading to changes in clinical practice, and finally the adoption of new clinical practice in treating patients with heart failure.

It is reasonable to expect that clinicians will act on these findings; KCL will disseminate the key findings from the publication in relevant departments of the university (KiTEC, the team carrying out this project within KCL is part of the School of Biomedical Engineering & Imaging Sciences and works closely with cardiologists from Guy’s and St Thomas’ NHS Trust). KiTEC also has a track record of presenting research at conferences (e.g. the Health Technology Assessment International annual meeting) and is planning to do the same with the results of this study. This is in addition to the publication that will be in a relevant high-impact open access journal. KCL's patient engagement work has shown that the project is of interest to patients and the results will be welcomed. The key findings will be disseminated among relevant patient organisations.

Preventing avoidable readmissions would lead to substantial reductions in resource use and expenditure, as well as better patient experience and quality of life.

There are an estimated 81,000 people living with heart failure, with admissions accounting for an estimated 1 million inpatient bed-days (around 2% of the entire NHS total). Up to 70% of these costs are due to hospitalisation costs, so attempts to reduce costs must be focused on reduced admissions.

It is reasonable to expect that KCL's publications will be taken into consideration by NICE as evidence for the next update of the NICE clinical guideline on chronic heart failure in adults: diagnosis and management (NG106). NICE guidance is updated every 3 years by means of a systematic review (which would include our publication) and through means of open consultation (contributions to which would be supported by the publication). KiTEC is an external assessment centre for NICE and therefore has very close links to these activities, and is well placed to contribute to guidance updates.

KCL (KiTEC) have advertised on People in Research (a website run by the NIHR), looking to involve members of the public at all stages of the research. To promote the results and findings, a Plain English document will be distributed to interested members of the public. KCL have made use of social media (twitter, LinkedIn) in the past for such dissemination and will use these avenues again. KCL currently have two responses to the advert from patients willing to be involved in the research. This involvement will include reviewing of the study protocol and any outputs from the research, particularly the Plain English summary of results.

KiTEC staff have training in Patient and Public Involvement (PPI), run by the Wellcome Engineering and Physical Sciences Research Council (EPSRC) Centre for Medical Engineering (CME) and have access to public engagement resources through this centre and also within the school of Biomedical Engineering and Imaging Sciences at King’s College London.

Two patients have so far agreed in principle to be involved with this research. Both have reviewed the study protocol and provided feedback to the research team. In addition to these 2 patients, it is hoped that at least 3 more can be recruited to form a PPI consultation group. The members of this group will primarily participate in this research by reviewing the outputs of the research, to ensure their readability and understandability. Outputs will include at a minimum: a Plain English Summary of results, social media posts and information on KiTEC’s website (www.kitec.co.uk). If possible the group will meet (or discuss over MS Teams), to discuss the findings of the research and request feedback from the group on other possible analysis or other possible ways to disseminate the research.

Outputs:

Academic papers will be published open-access in a high impact cardiology journal (such as The Journal of the American College of Cardiology (JACC): Heart Failure) on KCL's methodology, analyses and results, on the impact of repeat readmissions on costs and the attendant risk factors for repeat readmissions. The intention is to publish early in 2021, and there is no plan to publish interim results.

For each paper published, a short presentation is developed to summarise the findings for a range of stakeholders, including health technology assessment practitioners and the funder, Heartfelt Technologies. Findings will be presented at the Health Technology Assessment International (HTAi) Annual Meeting in Beijing.

The KiTEC website provides links to the open access papers and summaries of findings. Publications are also listed on individuals’ KCL Pure pages. KCL Pure is KCL's public-facing Research Portal [https://kclpure.kcl.ac.uk/portal/en/], where the public can find out information about KCL's research such as funding, researcher biographies and outputs such as published books and peer-reviewed journal articles.

All publications and conference presentations are promoted on LinkedIn, via the KiTEC account.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

KCL submits applications to NHS Digital and NICOR in parallel. The reference for the NICOR application is HQIP295 (18-HF-01).

STEP 1: NICOR send the Patient Identifiable Data (NHS Number, Date of Birth, Postcode) plus a study specific ID for the specific study cohort to NHS Digital. The NICOR study cohort contains only patients who are aged over 18 years old with heart failure in England between 2013/14 and 2017/18. The NICOR study cohort will contain approx. 81,000 people per year for 5 years.

STEP 2: NHS Digital
2a: Creates a bridging file of the pseudonymised HES-ID for the patients included in the NICOR cohort provided above and send this to NICOR.
2b: Creates a full set of 5 years of pseudonymised HES data from the NICOR Patient Identifiable Data and sends this to KiTEC.

NB: (separately to this NHS Digital agreement) NICOR will use the pseudonymised HES-IDs to create a full set of 5 years of pseudonymised NICOR data and send this separately to KiTEC.

KiTEC will therefore receive two separate data sets which will be linkable only via the pseudonymised HES-ID and therefore individual patients cannot be identified.

KiTEC does not have the ability to re-identify any individuals within the dataset and will make no attempt to re-identify individuals.

The data will not be made available to any third parties except in the form of aggregated outputs, in the form of academic paper(s) published in an open access journal, with small numbers suppressed in line with the HES Analysis Guide.

KCL is requesting linked HES Admitted Patient Care and NICOR data, linked using sensitive fields (NHS number, date of birth, post code) which have section 251 approval as documented in the separate NICOR application - HQIP295 (18-HF-01). No sensitive or identifiable fields will flow to KCL: the linked HES-NICOR data set is pseudonymised.

KCL requires linked HES-NICOR data from the years 2013-14 to 2017-18 (5 years), filtered by condition: heart failure patients (where 4-character codes i50.0-i50-9 appear in the diagnosis fields (DIAG_4_CONCAT)); additionally, linking HES data to the NICOR dataset will automatically filter the cohort by condition because all patients in the NICOR dataset have the codes i50.0-i50-9. KCL require this length of time in order to adequately cover the period in which numerous repeat readmissions might occur. Note that the data requested has not been minimised to exclude one-off admissions (i.e. patients who are not readmitted) because KCL requires data on these patients in order to perform comparisons between them and patients who are readmitted, either once or multiple times. Existing literature on the topic has employed a similar length of follow-up, i.e. 5 years (Leva, F., et al. (2017). "Multi-state modelling of repeated hospitalisation and death in patients with heart failure: The use of large administrative databases in clinical epidemiology." Statistical Methods in Medical Research 26(3): 1350-1372). KCL require national data because the study is a national one and is not limited to specific geographical areas; in addition, the study will consider whether geographical region is a potential risk factor for repeat readmissions.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Redcentric PLC [also known as Redcentric Managed Solutions, and Redcentric Solutions Limited as well as Redcentric PLC (Harrogate)] are NOT able to access the data stored on NICOR (Barts Health NHS Trust) servers. The data servers are managed by NICOR staff, including all server maintenance, backups etc. Redcentric only provide the secure facility (bricks and mortar) with power and internet connectivity for us to house our servers. Servers are in a secure locked environment which Redcentric do not access. Therefore, any access to the data held under this agreement by Redcentric Ltd would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. Barts Health NHS Trust staff have access to the data via remote access.

The back-ups are managed entirely by NICOR (either remotely or on site) and are not conducted by the data centre. The data centre functions only in providing an IT infrastructure.


Adult Psychiatric Morbidity survey 2014 — DARS-NIC-167122-G6W8K

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2019-11-01 — 2022-10-31

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

The Institute of Psychiatry, Psychology and Neuroscience within King’s College London (KCL) requires Adult Psychiatric morbidity survey 2014 data for a Economic and Social Research Council (ESRC) funded project.

Justification for the processing of the data is under Article 6(1)(e) of the GDPR, for the performance of a task in the public interest; and Article 9(2)(j) of the GDPR, where processing of the data is necessary for research purposes in the public interest. The ESRC have funded KCL to look at the increasing length of people’s lives and the health impacts of working longer or retiring earlier. Separate groups were established to look at physical health and mental health. The objectives of using 2014 adult psychiatric morbidity data (APMS) is to support improvements to mental health among non-employed and employed communities by analysing data and producing papers to be published in academic journals.

The 2014 adult psychiatric morbidity data will be used to investigate the trends in paid employment and common mental health disorders (CMD). Association between common mental health conditions (anxiety, depression, cognitive impairment) will also be investigated and associated with non-employment using 2014 adult psychiatric morbidity data.

King's College London (KCL) has previously used Adult Psychiatric Morbidity Survey data in 1993, 2000 and 2007 and has published a paper - "Paid employment and common mental disorders in 50-64 year olds: analysis of three cross sectional nationally representative survey samples in 1993, 2000 and 2007" Perera, G., Di Gessa, G., Corna, L. M., Glaser, K. & Stewart, R. 24 Aug 2017 In : Epidemiology And Psychiatric Sciences. There was feedback from Department for Work and Pensions that further analysis would be beneficial specifically including trends in strength of this association and strength of the association with other age groups.

Two members of Psychological Medicine department, Institute of Psychiatry, Psychology and Neuroscience at King’s College London will be leading this project. A consultant working in KCL's Department of Old Age Psychiatry is the academic lead for this project and an epidemiologist will be analysing the APMS data. Only these two members of the of Psychiatry, Psychology and Neuroscience will have access to APMS data.

The aim of this study is to explore changes in relationship between employment status, adverse life events and psychological health. KCL will be using ONS Psychiatric Morbidity Surveys: 1993, 2000, 2007 and 2014 data. Key outcomes included detailed psychological measures using Common mental disorder ascertained using the revised Clinical Interview Schedule (CIS-R) (e.g. depression, anxiety, sleeplessness).

KCL will be addressing following key questions:
i. What is the relationship between non-employment and common mental disorders?
ii. Does it vary according to the reason for non-employment?
iii. Does it vary by age group?
iv. Has it varied over time (1993, 2000, 2007)?
v. Is it related to particular common mental health disorders (CMD) symptoms?

The Adult Psychiatric Morbidity Survey (APMS) series provides data on the prevalence of both treated and untreated psychiatric disorder in the English adult population (aged 16 and over). This survey is the fourth in a series and was conducted by NatCen Social Research, in collaboration with the University of Leicester, for NHS Digital.

The previous surveys were conducted in 1993 (16-64 year olds) and 2000 (16-74 year olds) by the Office for National Statistics, which covered England, Scotland and Wales. The 2007 Survey included people aged over 16 and covered England only.

The work aims to develop understanding and evidence base for association between non-employment and common Mental Disorders in the UK and trends of such strengths of this association between 1993 and 2014.

The UK has witnessed significant increases in the percentage of older workers in the labour market, and the employment rate for those aged 50 and over is currently 57% (ONS Labour Force Survey, 2016) compared with 31% around a decade ago (Whiting, 2005), reflecting policies to encourage older workers to remain active in the labour market and delay retirement (Bartley, 1994; Vickerstaff, 2010). Investigations of employment status and mental health have primarily focused on unemployment as an exposure and its negative impact on psychological well-being. Studies of retirement and mental health have yielded mixed results. On the one hand, reduced prevalence of depressive episodes and mental fatigue has been reported following retirement (Westerlund et al. 2010; Calvo et al. 2013; Choi et al. 2013). However, this appears to coincide with the statutory retirement age and not the timing of individual exit from work (Villamil et al. 2006). British data indicate worse mental health associated with early retirement (Buxton et al. 2005), an association, which diminishes closer to statutory retirement ages (Melzer et al. 2004; Butterworth et al. 2006). Older workers may leave the workforce due to disability, unemployment, or early retirement, although these distinctions are often blurred (Calvo, 2006): for example, influenced by availability of disability and/or retirement benefits (Laaksonen et al. 2016; ONS Labour Force Survey, 2016) as well as perceived poor health or the presence of a chronic disorder (Mein et al. 2000; Monden, 2005; Vickerstaff, 2010), and more heterogeneous factors such as lower education, being single, physical inactivity and a high body mass index (Alavinia & Burdorf, 2008).

Few studies have investigated paid employment and mental health closer to retirement age: instead focusing on younger age groups (Butterworth et al. 2013), all working age groups (Weich & Lewis, 1998; Martikainen et al. 2000; Ford et al. 2010), or on early retirement (Buxton et al. 2005). A study of Korean men aged 55 years and older found that those in paid employment had a lower prevalence of depressive symptoms than the non-employed group (Park et al. 2016), similar to findings from two US studies (Calvo, 2006; Glass et al. 2006), and to those from various multinational European surveys based on respondents aged 60 years and older (Choi et al. 2013; Di Gessa & Grundy, 2014); however, all relied on brief screening instruments as mental health measures or single questions as outcomes.

APMS 2014 data is therefore required from NHS Digital in order to carry out the above outlined study in order to investigate these key research questions further through analysis of a nationally representative survey into CMD.

Expected Benefits:

The aim of these papers is to investigate effect of mental health among non-employed and employed community. The findings will be published with the assistance of various government and non-governmental organisations in order to disseminate those findings. In addition to the publications, KCL will present their findings to stakeholder organisations, including the Department for Work and Pensions, and the Pension Policy Institute.

These research outputs seek to directly increase the evidence base for association between common Mental disorders and non-employment in England for various age and gender group, for whom there are longstanding concerns about non-employment. By increasing the evidence base, an indirect objective is to contribute further to improved public health policy and programming. The eventual aim would be to achieve benefits to health through support of employment for those with common mental disorders and predict those who are about to become patients with common mental disorders and therefore to improve quality of life among population in England.

At this point, actual expected benefits and magnitude are as yet not quantified given data analysis has not been conducted. However, through the course of the project a more detailed dissemination plan focusing on policy recommendations that emerge from the research will be formulated to formalise these steps, and progress will be shared with NHS Digital. Outputs will be primarily discussed and presented in engagement through Department for Work and Pensions (DWP), led by the project co-supervisor. Furthermore, KCL will present these findings at the European Psychiatric Association (EPA) section of Social epidemiology. EPA conferences, seminars and talks are hosted with a range of mental health practitioners. It is reasonable to expect these benefits will be realised primarily because the research results will have policy implications for old age and disadvantaged groups.

Outputs:

King's College London expect to submit 5 papers to peer-reviewed publications by December 2022. Although the specific journals are not yet confirmed, the list of possibilities is expected to include:
> Epidemiology and Psychiatric Sciences
> Age and Ageing
> European Journal of Ageing
> Psychological Medicine

The findings will be submitted for publication to open-access, peer reviewed journals, with an estimated publication dates between August 2019 and of January 2022.

Further research conference posters and/or oral presentations will be submitted to various national and international conferences All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide/compliant with the MHSDS disclosure control rules including suppression and rounding. For each paper published on the research, short presentations will be developed to summarise the findings for different stakeholders, such as for pensioners, KCL will use institutional websites / social media accounts to promote findings through summaries or links to published work - for example, host blog posts on King’s Health Partners and through institutional Twitter accounts to promote engagement efforts so that research benefits reach communities to support improved health outcomes.

King's College London expect to submit 5 papers to peer-reviewed publications by December 2021. Although the specific journals are not yet confirmed, the list of possibilities is expected to include:
> Epidemiology and Psychiatric Sciences, Age and Ageing, European Journal of Ageing and Psychological Medicine.

Processing:

The 2014 APMS data set is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk) and the UKDS is responsible for dissemination under direction by NHS Digital. King's College London will receive the pseudonymised APMS data set. There is no facility to select individual variables. KCL will be able to download the data set from UKDS for the period specified within the Data Sharing Agreement and must securely destroy all local copies of the data set when the Agreement expires and notify NHS Digital in line with standard procedures. This 2014 version of the data set available has been redacted on Disclosure Control Procedure advice to minimise the likelihood of individuals being able to identify anyone taking part in the survey.

UKDS will transfer the pseudonymised APMS data to KCL. No other organisations will be involved in the flow of data.

The APMS 2014 dataset will be used by KCL to conduct research in non-employment and common mental disorders in the UK, building on the gaps identified in literature. Nationally representative data is required to reach generalisable conclusions which are relevant for public health policy and programme development in this sector of health.

Once the APMS data has been received by KCL, it will be saved in Kings College London secure folders which only approved employees of KCL will have access to. KCL store data on a server on site which can be remotely accessed via secure, password protected computers supplied by the institutions.

The data will be analysed using STATA. KCL will analyse trends over time, and investigate any associations between mental health and non-employment. The APMS data will allow KCL to look at sub-components of common mental health disorders.

Individual level APMS data will not be linked to any other datasets.

There will be no requirement nor attempt to re-identify individuals from the data.

Data will only be accessed by individuals within KCL who have authorisation to access the data for the purpose(s) described, all of whom are substantive employees of KCL.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.


Survival and recovery after hip fracture surgery by timing of mobilisation — DARS-NIC-164830-L7L7C

Opt outs honoured: Anonymised - ICO Code Compliant (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2018-11-19 — 2021-11-18

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care

Objectives:

Background:
Annually UK hospitals admit 75,000 men and women over the age of 60 years with hip fracture. Even with treatment, 30% of patients die within a year. Among survivors, 25% never walk again, and 22% transition from independent living to long-term care.

Early mobilisation after hip fracture surgery is defined as getting out of bed within 36-hours of the procedure. Proponents of early mobilisation argue that longer waits affect recovery through rapid loss of muscle strength induced by bedrest. The average patient with hip fracture is 83 years old, frail, and has at least one comorbidity. For these patients, maintaining the strength required to get out of bed could mean the difference between returning home and admission to long-term care. Further, longer waits may lead to potentially-fatal complications such as pulmonary embolism, or pneumonia.

Concern about the potential harm from delays led National Health Service Improvement to add early mobilisation to the Fragility Hip Fracture Best Practice Tariff in 2017. To comply with the Tariff, hospitals across the UK will start prioritizing mobilisation after hip fracture surgery over other surgeries, such as femoral shaft fractures. Yet it remains unclear whether early mobilisation yields a survival or recovery benefit for these patients.

One obstacle in studying the effects of delayed mobilisation has been a lack of information about rehabilitation and recovery in hospitalisation records. Therefore, King's College propose to examine available records from the National Hip Fracture Database (NHFD). This registry assembles data on the timing of mobilisation, and functional status before and 30-days post-fracture for patients hospitalised with hip fracture in England, Wales and Northern Ireland.

The National Hip Fracture Database (NHFD) is a clinically led, web-based quality improvement initiative commissioned by the Healthcare Quality Improvement Partnership (HQIP) and managed by the Royal College of Physicians (RCP). Crown Informatics are RCP's data processor who will be sending in the cohort to NHS Digital for linkage. RCP and HQIP will have no access to the data and will play no part in the processing of the data for this study.

Kings College London made an application to the Scientific and Publications Committee of the NHFD for access to data to provide robust estimates of the effect of early mobilization (one of the NHFD's core quality indicators) on outcomes. This application was approved as it deemed to support the objectives of the NHFD.

All 182 eligible hospitals in England, Wales and Northern Ireland are now regularly submitting data to National Hip Fracture Database (NHFD). The largest hip fracture database in the world, with:
> a third of a million cases recorded since its launch in 2007
> over 95% of all new hip fracture cases being documented
> 5,700 records being added every month.

This research will use the NHFD linked to HES to determine whether early mobilisation is associated with survival and recovery after hip fracture surgery. More specifically, the objectives are:

1) To determine whether mobilisation within 36 hours of surgery is associated with the cumulative incidence of survival on discharge;
2) To determine whether mobilisation within 36 hours of surgery is associated with survival and recovery at 30-days post-fracture; and
3) To determine whether these putative associations vary across subgroups defined by characteristics of patients, their injury and care delivery.

HES data will be used to provide rich information on comorbidities and complications for regression adjustment and subgroup analysis this will be linked to Civil Registration (mortality) data to provide the fact of death at 30-days. The linked HES and audit data will provide information for the whole period of hospitalization for the patient regardless of which consultant they are under and crossing hospitals where a transfer has taken place.

Processing:

Study cohort:
All patients 60 years of age or older who underwent hip fracture surgery in England, Wales, or Northern Ireland between 2011 and 2016 (n = 225,000).

Data source:
King's College will retrieve data on the characteristics of patients, their injury, and care delivery, survival on discharge, and survival and recovery at 30-days by linking the NHFD to the Hospital Episode Statistics linked to Civil Registration (mortality) data. A separate application will be made to the Patient Episode Database for access to Welsh data.

Statistical analysis:
King's College will calculate the cumulative incidence of live discharge as a function of postoperative day, with in-hospital death being a competing event, by timing of mobilisation. King's College will use regression with weighting by inverse propensity score to compare the ratio of live discharge, survival and recovery at 30-days, by timing of mobilisation. Analyses will be adjusted for factors associated with poor survival and recovery after hip fracture surgery. Subgroup and interaction analyses will be conducted to determine whether there is variation in the effect of mobilisation timing across patient subgroups.

Expected output:
This study will determine whether early mobilisation is associated with survival and recovery after hip fracture. The study will identify who may benefit most from early mobilisation, as optimal timing may vary across patient subgroups.

Dataflow:

Crown Informatics send NHS Number, Date of Birth, Forename and Surname, Full postcode, Study ID and date of admission to NHS Digital.

NHS Digital provide Kings College London with HES pseudo non sensitive product data (inclusive of fact of death at 30 days) and Study ID.

Kings College London will store the data electronically in a file that is only accessible by nominated study personnel working at Kings College London. The data will not be shared with third parties and will only be used for the purposes outlined in this agreement.

Kings College London will link by study ID the product data to pseudonymised NHFD data from Crown Informatics. Data will be analysed for research purposes outlined above by a team within the School of Population Health and Environmental Sciences at King's College London. The team are are all substantive employees of King's College London and are subject to King's College London's policies, procedures and sanctions.

There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).


A study of alcohol misuse and dependence; UK MPs compared to the UK population — DARS-NIC-164024-C3N9T

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2018-07-17 — 2021-07-16

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

There are concerns that UK Members of Parliament suffer from a higher prevalence of alcohol use disorders, possibly related to their working conditions. There have been no previous studies on this, the present study seeks to address this gap in knowledge, in order to inform health and service provision, mental health awareness and support for UK Members of Parliament. This work is being led by a research team at King's College London (KCL).

Main objective: In order to understand the prevalence of alcohol use disorders amongst current UK Members of Parliament the research team seeks access to data from the APMS as a nationally representative comparison sample. for a study of UK Members of Parliament alcohol misuse and dependence.

Expected Benefits:

The findings will be of benefit of highlighting and improving the health of current UK MPs as it will help to determine whether alcohol misuse/ dependence is a problem in a UK MP sample (relative to the national population) and will help to inform parliamentary healthcare/ service provision for this group of people.

United Kingdom Members of Parliament (MPs) are exposed to many risk factors for alcohol/ substance misuse, including high workloads, intense media scrutiny, in addition to working away from their families much of the time. However, to date, no formal, quantitative, survey has been conducted to assess MP’s mental health, and their access to support and treatment services. The present proposal will utilise nationally representative data from the Adult Psychiatric Morbidity Surveys to provide a reference for alcohol use disorders (via the AUDIT) for a sample of MPs from UK parliament, in whom researchers wish to estimate the prevalence of alcohol use disorders.

Main benefits will be
1. Improvements to the provision of mental healthcare to parliamentarians (this may involve making existing services more visible and accessible). This will be through sharing findings from the report with the Parliamentary Health & Wellbeing Service.
2. The findings will also inform measures to screen and manage alcohol use disorders and common mental disorders in parliamentarians- for example the findings will be fed back to the existing providers of care to better inform their current interventions.
3. Inform discussions of parliamentarian mental health- to be measured through social media (eg. twitter), press releases and national press reporting (following publication of paper) and other announcements on institutional websites- by Dec 2020. This may lead to a reduction in stigma in people's attitudes concerning parliamentarian mental health and may mean that parliamentarians themselves are more likely to seek help for their own mental health problems.

Outputs:

The outputs of this work will be produced into a peer reviewed manuscript for submission to a journal. KCL will also produce a report for UK parliament- a member of the research team is a current member of parliament and holds links with the parliamentary health and wellbeing group. NHS Digital data (in the form of data from the APMS surveys) will be used as a comparison sample for derived estimates in all main reports and manuscripts. There will be no attempt to link or re-identify KCL survey data with APMS survey data. See anticipated dates for outputs below.

In summary- anticipated outputs:
1. One peer reviewed manuscript- to be submitted to a journal eg. The British Medical Journal- by Dec 2019. Anticipated audience for this will be academics and other researchers, healthcare providers and policy makers. A copy will also be made available to the Parliamentary Health and Wellbeing Group.
2. Report or statement of findings to be distributed to relevant individuals in UK parliament- by Dec 2019


The TIDES study: Inequalities in health use — DARS-NIC-159251-K4Y6Q

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2018-05-15 — 2021-05-14

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

The TIDES study (tackling inequalities and discrimination experiences in health services) seeks to investigate unaddressed questions about the role of discrimination by healthcare providers (HCPs) in generating inequalities through unconscious but demonstrable discriminatory biases. With recent NHS Equality and Diversity Council mandates encouraging service improvements through addressing inequalities, this study will use innovative approaches to generate evidence for interventions, aimed at reducing discrimination among HCPs. It will draw upon comparable national and community survey data to enable intersectional analyses examining, inequalities in health service use. TIDES will utilise findings from these analyses to inform subsequent collection of both quantitative and qualitative data in an ethnically and socioeconomically diverse part of London (South East London). The TIDES study is being carried out by King's College London (KCL).

The purpose of the TIDES study is to gather both quantitative and qualitative information from HCPs for the following objectives:
1. Determine the prevalence of discrimination (witnessed, anticipated or experienced) among HCPs and how they are interrelated.
2. Identify how levels of bias and discrimination among HCPs differ by social background, such as gender, ethnicity and migration status.
3. Assess how bias and discrimination are related to HCPs job satisfaction, health and health service use.
4. Explore, in qualitative interviews and focus groups, how biases and discrimination among HCPs may contribute to health service inequalities.

The APMS data will be used specifically to demonstrate current national-level health service utilisation, examine sociodemographic data to identify disparities, compare findings at the national level to those observed locally (via the South-east London Community Health (SELCoH) Survey data, this survey was originally modelled on APMS), and help to determine what should be included in KCL's upcoming survey of health care practitioners.

The TIDES study is funded by the Wellcome Trust, commenced in 2017 and is scheduled to complete in 2022. The study has been approved by KCL REC and the Health Research Authority. There will be no 3rd party involvement or work taking place outside the UK.

Expected Benefits:

KCL hope to deliver benefits to the health and social care (analysis, quantitative and qualitative surveys, simulations) on tackling inequality and discrimination experiences in health services.

The study's ultimate goals are an intervention framework aimed at early career HCPs, and to inform national guidelines for training, practice and policy. The guidelines will be developed in conjunction with stakeholder groups including community members, service users, health/social care advocates, researchers, NHS clinicians and managers, medical educators and policy makers. KCL have direct relationships with Equality and Workforce leads at South London and Maudsley NHS Trust, NHS England and the Workforce Race Equality Standard working group and the Mental Health Policy Unit (a joint initiative between KCL and UCL). KCL plan to disseminate the findings and intervention framework through these organisations in order to influence policy and institutional practice.

Outputs:

Submission to peer-reviewed journals, possible journal is Epidemiology and Psychiatric Sciences, but it has not been determined yet where this paper would be submitted. Outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. This would hopefully be written and published in 2018 or 2019. Lay summaries will be produced for all publications for access by wider audiences and will be made available on our study website (www.tidesstudy.com)

Other outputs include:
Results of the APMS analysis will inform the questions that are being asked of health-care practitioners in the upcoming survey, this will commence mid 2018.

A number of events are planned with local communities to present findings on inequalities in health service use, this will include findings from publications that use APMS 2014 data. These events will include presenting findings using different visual media and discussion between researchers, healthcare practitioners, service users and local communities.

Specific reports for stakeholder groups e.g. service user groups and healthcare practitioners will be produced with the aim of influencing policy and institutional practice

Other:
Data will only be accessible by TIDES team members, only for the purposes of analysis resulting in publication and informing KCL's survey questions.

All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide

Processing:

The APMS 2014 survey data will be analysed using statistical software to determine if there are any identifiable disparities in healthcare service use, based on sociodemographic variables. (Hypothesis 1: After accounting for levels of need, those with multiple disadvantaged social statuses will report less service use, more barriers and poorer service quality. Hypothesis 2: The patterning of inequalities will differ between multiple versus single statuses, with previously unidentified inequalities emerging with the former.) Only TIDES team members will access the data set. The data will not be linked.

Results of the analysis may be compared to a local survey (SELCoH, mentioned previously), as the questions asked in the SELCoH survey were largely based on those asked in the first APMS survey. This comparison would occur at an aggregate level (e.g. health-care service usage by ethnicity).

Papers may be published that reference the findings in the APMS 2014 survey. Again, these would be at an aggregate level. KCL have yet to determine where they would submit a paper, but a possible journal would be Epidemiology and Psychiatric Sciences.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

The 2014 APMS dataset is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk ) and UKDS are resp onsible for dissemination under direction by NHS Digital. The Data Controller will receive the whole dataset; there is no facility to select individual variables. They will be able to download the dataset from UKDS for the period specific within the DSA and they must securely destroy all local copies of the dataset when the DSA expires and notify NHS Digital in line with standard procedures. This 2014 version of the dataset has been redacted on Disclosure Control Procedure advice to minimise the likelihood of individuals being able to identify anyone taking part in the survey.


Smoking cessation among people with mental health problems — DARS-NIC-159225-C9N9P

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2018-07-25 — 2021-07-24

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

The APMS data will be used to conduct a quantitative study with the overall aim of identifying how the frequency and success of quit attempts can be enhanced among smokers with a range of mental health problems (MHPs). This study comprises part of a project entitled “Improving smoking cessation in smokers with mental health problems” funded by a CRUK/BUPA Foundation Cancer Prevention Fellowship (C52999/A19748). The funders do not have any influence on the results of the research.

This study is motivated by the observation that one third of smokers have MHPs, that smoking prevalence among people with MHPs is far higher than in the population as a whole, and the fact that NICE now recommends that all secondary care settings become smoke-free while providing interventions to support patients. A significant proportion of those requiring support may also be affected by MHPs. This study will be the first time that mental health status and detailed smoking and cessation information will be analysed using data from a representative survey. The study will be purely quantitative in nature and will attempt to incorporate advanced quantitative methods where appropriate.

Expected Benefits:

It is hoped that the aggregate-level findings of the research using APMS 2014 data will deliver relevant findings for policy and clinical practice at the population level. This will be the first time that mental health status and detailed smoking and cessation information will be available within a representative survey. Thus, the study outputs will provide novel and unique information related to cessation among smokers and recent ex-smokers with MHPs living in the community to identify specific issues and areas for action.

The Addiction Department’s research informs tobacco policy and NICE appraisals, and it is hoped that the findings may inform future policy debates and research on, and implementation of, tobacco cessation interventions. As such the results will be disseminated among the Department's research and funding partners. First, the results and final publications will be shared with Cancer Research UK (the project funder) and Public Health England to potentially inform future research funding priorities and public health policies at the national level. Second, Department research staff participate in the Mental Health and Smoking Partnership and will disseminate the results of the proposed research among its members. The Mental Health and Smoking Partnership brings together groups committed to reducing rates of smoking; particularly among people with a mental health condition. These Royal Colleges, professional bodies, voluntary sector organisations, academics and service users. The Partnership examines implementation of current policies, reviews their progress and issues policy statements on topical issues to influence the policy discourse and highlight areas for future action.

The study’s results may point to gaps in access for groups with specific MHPs due to differences in treatment-seeking behaviours and signpost future work on improving implementation of interventions for specific groups for whom particular interventions may be more or less effective. The findings will be published/disseminated in 2018 or 2019.

Outputs:

It is anticipated the results will be submitted to peer-reviewed journals as one or more research papers. Although Addiction and Nicotine & Tobacco Research may be suitable options it has not been determined yet where papers would be submitted. These articles are expected to be written in mid-to-late 2018 and published in 2018 or 2019.

Processing:

The study will comprise two phases. First, a preliminary analysis will be carried out to determine smoking prevalence by mental health status (both lifetime and recent diagnosis). The association of level of nicotine dependence and odds of making quit attempts with mental health status (and other sociodemographic variables) using data from the Adult Psychiatric Morbidity Survey will then be investigated. Data from two waves (2007 and 2014) will be used to determine whether there has been change over time. The data for 2007 have already been obtained from the UK Data Service. The entire 2014 dataset is required due to the exploratory nature of this analysis. Its findings will inform the modelling approach in the subsequent phase as it will specify important MHPs and identify relevant covariates and interventions for analysis.

In the second phase, multivariate analyses will be used to address the following research questions as set out in the terms of the fellowship plan presented to CRUK/BUPA Foundation:
1. Do smokers with MHPs make quit attempts as frequently as those without MHPs?
2. What are the most frequent triggers for quit attempts in this population? Does this differ from the general population?
3. Does the use of generally more effective intervention options (prescription medication, behavioural support) differ in smokers with and without MHPs?
4. Does success of quit attempts with different interventions / support used vary with mental health status?

Data are already anonymised. KCL are aware of the potential element of risk that individuals could be re-identified, however. To preclude this, all published results will be at the aggregate level and will only be used to draw population-level inferences. The data will not be linked as there are no identifiers to link on.

Papers may be published that reference the findings from the APMS 2014 survey and compare these with 2007 data.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

In order to protect patient confidentiality in publications resulting from analysis of APMS data users must:
•guarantee that any outputs made available to anyone other than those with whom this agreement is made, will meet required standards, including the guarantee, methods and standards contained in the Code of Practice for Official Statistics and the ONS Statistical Disclosure Control for tables produced from surveys;
•apply methods and standards specified in the Microdata Handling and Security Guide to Good Practice for disclosure control for statistical outputs.


Health and Economic Effect of Air and Noise Pollution near Airports — DARS-NIC-03398-N1D2C

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2018-06-27 — 2020-06-26

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Outpatients

Yielded Benefits:

Expected Benefits:

London Heathrow airport has reached full capacity since 2011. One implication of this situation is that the UK government has to make a decision over its expansion.

Kings College London’s research is motivated by the vivid policy debate on the costs and benefits of the aviation industry. In particular King’s College London is interested in estimating the component of the total health costs imposed on society by air traffic-related pollution.

In terms of benefits to the UK Health and Social Care system, the first contribution this project will make will be to provide an up-to-date insight into the negative effects of ambient noise and air pollution on well-being. In fact, individual well-being and health status are major factors influencing individual productivity (either contemporaneous or future), which in turn affects the aggregate productivity of labour. Airports generate both air and noise pollution, which can each be measured separately and relatively accurately.

Most importantly, with the support of a natural experiment setting, Kings College London’s research explores the causal effect of airport-related emissions on health. Health outcomes include hospital admissions for cardiovascular, respiratory and nervous system-related diseases, low birth weight and length of gestation. The approach used is a difference-in-differences (DID) estimator that exploits changes in flight regimes over time and across areas affected by flights to and from London Heathrow airport.

A subsequent step would be to look at all major airports in England to have a better understanding of health care needs in areas located near to airports.

King's College London will present their results to policy audiences in order to disseminate the results from our research.

The aim this research ‘Health and Economic Effect of Air and Noise Pollution near Airports’ is to rigorously identify a causal relationship between air and noise pollution emissions from air traffic and health outcomes of the population living underneath flight paths.

This project essentially aims to reply to three broad research questions. Firstly, what are the size and the nature of the health effects of airport activities on the local population, mainly from air and noise pollution? In particular, the aim is to univocally define the causal relationship between pollution emissions from aircraft movements and human health. This is done around London Heathrow airport, which is characterised by a highly dense urban area and good availability of data. A further research will be done using a multi-airport approach in order to increase the generalizability of these results. A major contribution of this research will be a clearer understanding of the simultaneous health effects of both air and noise pollution.

Secondly, does airport-related pollution causes new disorders or does it simply induces a worsening of health status to people with previous medical conditions? Having access to HES data is the essential key to unravel the opaque distinction between exacerbation and initiation of ailments.

Finally, what are the costs borne by society? The concluding task is to get some figures of the actual costs of illness induced by airport-related pollution. This aims to take part and fundamentally contribute to the current policy-making discussion over costs and benefits of the aviation market in the UK.

To summarise, the benefits would be both to society in terms of a clearer understanding of the health effects of environmental hazards and to the field of microeconometrics. In fact, the use of a quasi-experimental approach is an econometric technique which is receiving growing interest within the social sciences. In conclusion, information about the impacts of air and noise pollution around airports will help the NHS to better plan its resource allocations, especially with regard to expansion of Heathrow and increased air traffic more generally.

The research work being conducted is key to inform the NHS that Kings College London are doing work that will directly benefit the NHS by providing new and reliable results on the impact of air and noise pollution for population living near major airports.

Kings College London will plan to discuss details and implications of the research to public health departments in the local authorities relating to the data areas covered and by circulating a summary version of their research and offer to meet with them to present the main results and discuss the implications as a result of the research.

Outputs:

Kings College London confirms that the data received will only be held and analysed in England and no record level data will be shared to any third party. The data will not be used for commercial purposes. The initial study was completed in February 2018 with the dissertation published on King’s College London’s website - https://kclpure.kcl.ac.uk/portal/en/theses/health-effects-of-noise-and-air-pollution(edfd9ba5-4378-49b3-8cd1-3d8b190c5faa).html. A London based newspaper have taken note of this work and published an article (in paper form only). The article highlights that Heathrow airport representatives are also aware.

Through publications in peer reviewed journals, this study will therefore contribute to the broader literature on the health and economic effects of environmental pollution as well as the specific debate on the future of airport development in London and the South East England.

This agreement allows academic papers to be written and published. It is expected that the results in the study will help decide on the correct timings of aircraft landing around Heathrow. But the expectation is that the media coverage (KCL is planning a press release at the time of publication) will allow the results to be well published and can help plan the correct approach for every UK airports situated near urbanised areas.


All outputs consist of aggregated results with small number suppression applied in line with the HES analysis guide.

Processing:

In order to investigate how morbidity and mortality trends respond to changes in pollution emissions, Kings College London look for shocks to usual emission rates of both air and noise pollution. Regarding Heathrow airport, Kings College London identified one major non-gradual exogenous variation to aircraft noise and air pollution emission rates. For five months, from 5th November 2012 to 31st March 2013, Heathrow airport ran the Early Morning Arrivals Trial in collaboration with the noise pressure group HACAN (Heathrow Association for the Control of Aircraft Noise), British Airways and NATS (formerly National Air Traffic Services). The aim of this trial was to investigate the feasibility of providing a predictable relief period for some communities close to Heathrow's approach paths. The conditions of the five-month trial are set out in a detailed report (Tucker, K., Williams, R., and Leighton, S. 2013. Heathrow Airport - Early Morning Arrival Trial Final report. Helios, London.). These include the identification of two pairs of exclusion zones, which would alternatively be avoided by aircraft between 23:30 and 06:00 for the duration of the trial. Other air traffic variations at Heathrow airport and other airports were expected to be identified.

The goal of this project was to assess the impact of changes in aircraft emissions on health outcomes for those people living underneath flight paths. The clearest way to simultaneously isolate causal effects of the flight changes and control for confounding factors is to explore over time outcome differences between communities that experience the flight change and communities that do not.

The empirical design adopted here is a standard two-period difference-in-differences (DD) approach. It consists of examining differential trends of postcode districts (or LSOAs) affected by the change and non-affected postcode districts over time (before and during the trial).

To actually calculate the health effects King’s College London estimated a regression equation which has hospital admission outcomes as dependent variable and geographical (e.g., postcode district, LSOA), environmental (e.g., noise and air pollution levels at aggregate level, precipitations, humidity, temperature, wind speed and wind direction) and socio-economic dummies as independent variables.

To carry out this work, Hospital Episode Statistics Admitted Patient Care 2008/09 to 2013/14, HES Outpatient 2011/12 to 2013/14 and HES A&E 2011/12 to 2013/14 was requested and disseminated to KCL under a previous iteration of this Data Sharing Agreement.

By using a methodology relying in DD, KCL need data over a sufficient long period before the implementation in order to verify that pre-trial conditions in the chosen treated and control groups were following a similar pattern (a condition named as ‘parallel trend assumption’ in the econometrics jargon).


This DD model furnishes several advantages. Firstly, it produces easily interpretable estimates (i.e. what happens if an average area is exposed to changes in flight path?). Additionally, the difference-in-differences identification is applicable in more complex settings with multiple time periods and manifold treatment intensities.

The control group includes those areas with no change in air traffic before and during the trial. The treatment group can ideally be represented by all the other areas clustered depending on the nature of variation. This range of variations creates the perfect environment for the aforementioned multiple treatment classifications. Both treatment and control regions naturally incorporates both rural and urban regions, both poor and rich socio-economic characteristics. Even though the areas need a robust check for their comparison to be validated, the trial seems to have all the properties to build a natural experiment setting.

The DD regression and all the analysis involved in this project was run (and continues to be) using Stata software (StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP). The DD design was implemented for all the different clusters of health outcomes (respiratory disease, cardiovascular disease, nervous system disease, birth outcomes) and also for the aggregation of all medical conditions. This was to investigate the effect of environmental stressors on specific illness as well as the overall health status depletion.

Data will not be stored, processed or in any other way accessible by a third party organisation and will be stored in only a single location at King's College.


A population-based retrospective cohort study into the factors associated with Emergency Department attendance by people with dementia in the last year of life. — DARS-NIC-365602-V5H3Z

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2020-12-01 — 2023-11-30 2021.03 — 2022.06.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Accident and Emergency
  5. Civil Registration (Deaths) - Secondary Care Cut

Objectives:

King’s College London requires data from the Hospital Episode Statistics Data (HES) Accident and Emergency Set (A+E), HES Admitted Patient Care (APC) data set and Civil Registration (Deaths) - Secondary Care Cut data for the study “A population-based retrospective cohort study into the factors associated with Emergency Department attendance by people with dementia at the end of life”. In this study, the Emergency Department (ED) is defined as a consultant-led accident and emergency service with full resuscitation facilities operating all day, every day (1).

Data will be used for analysis of a single observational study that constitutes the quantitative strand of a mixed methods study as part of a standalone PhD. This PhD is one of three funded by the Alzheimer's Society and aims to understand why people with dementia attend the Emergency Department (ED) at the end of life. The PhD Clinical Training Fellow is a substantive employee of King’s College London and is supervised by two senior clinical academics who are also substantive employees of King’s College London. The other two PhDs are not focused on ED attendance or end of life care for people with dementia and are not the focus of this application.

An estimated 850,000 people have dementia in the UK (2). The disease has an uncertain trajectory and for many, in the last year of life, there are multiple hospitalisations and Emergency Department (ED) attendances (3,4). Hospital transfer at the end of life is widely considered to be a marker or poor-quality care (5). It can be distressing and disorientating for the patient with dementia (6) and places additional strain on the emergency and acute care services with sharp increases in hospital costs in the final few months of life (7).

A recent systematic review of international literature has found high strength evidence of individual, clinical and environmental risk factors increasing ED attendance by people with dementia towards the end of life (8). However, the majority of the reviewed studies were conducted in the USA. Furthermore, whilst much of the literature focuses on ‘burdensome’ transitions to hospital, comparatively few focus on ED attendance, fewer are conducted in the UK, and none that are on a population-based scale. One small-scale study within four London boroughs showed increasing number of ED attendances with closer proximity to death. The study also identified differential predictors of ED attendance, including various socio-economic variations (4). Expanding on these findings, and contributing to the international literature in the field, this study aims to capture population-based variance to increase generalisability and practical application.

On the basis of the literature, this study aims to identify the factors associated with ED attendance by people with dementia in the last year of life. The objectives of the study are:

1) To examine the frequency of ED attendance and re-attendance by people with dementia in the last year of life;

2) To ascertain the reasons for ED attendance among people with dementia in the last year of life;

3) To identify the predictors of ED attendance by people with dementia in the last year of life.

To meet these objectives, King's College London requires pseudonymised data from HES A&E, HES APC and Civil Registration (Deaths) - Secondary Care Cut databases for linkage. Details of how access to this data will meet these objectives are as follows:

Objective 1: Access to HES A&E to obtain the attendance category, disposal and department type to enable review of frequency of ED attendance, stratified by outcome of ED attendance and number of attendances for the same incident. Linked to data from the Civil Registration (Deaths) - Secondary Care Cut, this data will provide insight into the proportion and frequency of ED attendances, at different intervals within the last year of life (e.g. last twelve, six and three months, and last 30, seven and three days of life).

Objective 2: Access to HES A&E to obtain the attendance category, department type, arrival mode, incident location type, source of referral for A&E and A&E diagnosis to enable review of the types and frequency of precipitants to ED attendance. A&E investigations and clinical treatments will provide insight into the acuity and severity of the incident that has led to ED attendance. Access to HES APC to obtain the diagnosis and episode duration and type if the patient was admitted into hospital from the ED. Linked to data from the Civil Registration (Deaths) - Secondary Care Cut, this data will provide detail on the main reasons for ED attendance in the last year of life (i.e. ambulatory care sensitive conditions, carer strain).

Objective 3: Access to HES A&E to obtain the arrival mode, arrival date, arrival time, IMD decile group, IMD Index of Multiple Deprivation, Lower Super Output Area, CCG of GP Practice, county of residence, rural/urban indicator, A&E diagnosis, age at activity date, age on arrival, carer support indicator, ethnic category, month and year of birth, patient sex and postcode district. Access to HES APC will provide data on diagnoses, comorbidities, ambulatory case sensitive conditions, carer support and marital status. Linked to data from the Civil Registration (Deaths) - Secondary Care Cut, the data will provide valuable information of the predisposing factors associated with ED attendance and repeat attendance in the last year of life.

In order to improve the care and management of patients, it is important to understand the factors associated with ED attendance at the end of life. It is proposed that by analysing the frequency of, reasons for, and factors associated with ED attendance at the end of life, high-risk patients can be profiled and modifiable risk factors identified to direct future targeted policy and service interventions. It will also generate further research avenues into the effectiveness of these interventions and to address any gaps identified in the evidence base as a result of the findings of this study.

The study will require data about adult decedents with a diagnosis of dementia (of any sub-type and any severity) who died between 01 April 2018 and 31 March 2019. Linked HES A&E, HES APC and Civil Registration (Deaths) - Secondary Care Cut data will allow assessment of ED attendance in the last year of life, to correspond with the definition of end of life (9). Based on previous literature guiding this study, factors associated with end of life ED attendances will be grouped into categories and subject to mixed effects regression models to measure ED attendance counts and occurrences.

Data are requested from HES years 2016 to 2019 to identify people who had an ED attendance 12-36 months before death.

Only record-level data, with pseudonymised HES IDs, can yield the necessary information to draw conclusions about patterns of ED attendances, therefore no less obtrusive methods are available. Date of death has been requested. Acknowledging the sensitivity status of this field, there are no other means of measuring the number of ED attendances within the last twelve, six and three months, and last 30, seven and three days of life. Month and year of birth and age at death alone will be insufficient to accurately determine days, weeks and months in the last year of life. There is therefore no less obtrusive method available to determine this time-frame. However, it will be integral to the study in order to replicate findings of a previous local study (4) and to identify factors associated with the frequency of ED attendance compared to proximity of death.

King's College London is the only organisation involved in this study, being the sole Data Controller and Data Processor. No other organisations will process the data for this purpose. All researchers involved in the study are employed by King's College London as research or academic staff. Under this Agreement, King's College London requires pseudonymised data until the expiry date of this agreement. At this expiry date, all pseudonymised record level data will be destroyed with a Data Destruction Certificate submitted to NHS Digital as evidence.

Data will be presented at aggregate level with small number suppression applied in line with the HES analysis guide on all published results - so that no individuals are identifiable. The outputs will help clinicians and policy makers ensure the future provision of best care.

NHS Digital will extract data on patients as per the coding provided, securely link across all datasets requested and send to King’s College London a pseudonymised dataset for analysis.

References

(1) NHS Data Model and Dictionary (2020). Accident and emergency department type. Available from: https://www.datadictionary.nhs.uk/attributes/accident_and_emergency_department_type.html

(2) NHS England. (no date). Dementia. Available from: https://www.england.nhs.uk/mental-health/dementia/

(3) Leniz, J., Higginson, I. J., Stewart, R., & Sleeman, K. E. (2019). Understanding which people with dementia are at risk of inappropriate care and avoidable transitions to hospital near the end-of-life: a retrospective cohort study. Age and Ageing, 48(5), 672-679.

(4) Sleeman, K. E., Perera, G., Stewart, R., & Higginson, I. J. (2018). Predictors of emergency department attendance by people with dementia in their last year of life: Retrospective cohort study using linked clinical and administrative data. Alzheimer's and Dementia, 2018. 14(1): p. 20-27.

(5) Gozalo, P., Teno, J. M., Mitchell, S. L., Skinner, J., Bynum, J., Tyler, D., & Mor, V. (2011). End-of-life transitions among nursing home residents with cognitive issues. New England Journal of Medicine, 365(13), 1212-1221.

(6) Clevenger CK, Chu TA, Yang Z, Hepburn KW. Clinical Care of Persons with Dementia in the
Emergency Department: A Review of the Literature and Agenda for Research. Journal of the
American Geriatrics Society. 2012;60(9):1742-8.

(7) Georghiou, T., Davies, S., Davies, A., & Bardsley, M. (2012). Understanding patterns of health and social care at the end of life. London: Nuffield Trust.

(8) Thoms, L., Evans, C., Leniz Martelli, J., Yorganic, E., Cripps, R., & Sleeman, K. (unpublished). Factors associated with Emergency Department attendance by people with dementia near the end of life: A systematic review.

(9) NICE (2017). End of life care for adults. Quality Standard (QS13). Available from:
https://www.nice.org.uk/guidance/qs13/resources/end-of-life-care-for-adults-pdf-2098483631557.

Expected Benefits:

The dissemination of results plans to benefit the provision of healthcare and adult social care by providing evidence to inform change in clinical practice, policy and service design. This study has the opportunity to affect every person dying with dementia, as well as family, carers and healthcare professionals involved in providing their end of life care. It is hoped the outputs will provide robust evidence to demonstrate unmet need among this vulnerable population and the factors associated with poorer quality of end of life care. Wide dissemination through open-access resources and diverse communication channels is therefore considered to be in the public interest; not only for its relevance to a large population of people affected by dementia but also for the potential impact on health and social care provision and service design.

The benefits of the dissemination plan include targeting and reaching the most relevant individuals. Between August 2021 and April 2022, papers and abstracts will be sent to journals and conferences in palliative care and psychiatry. In September 2021, policy briefs and results summaries will be shared with relevant charities and third sector groups. The outputs from this project will hopefully show, for the first time as far is known, what factors are associated with ED attendance at the end of life for people with dementia across England, demonstrating whether there are differences and inequalities between patient profiles. This evidence is needed for change in the provision of care for this patient group.

The benefits will be measured in several ways. First, the reach of the results will be measured by summarising and evaluating the dissemination of the work, including readership of the journal in which the results are published, number of downloads, online readers and retweets. The anticipated benefits of increased awareness among clinicians and carers will also be measured by proxy through discussion between partners and collaboration between palliative care and other relevant specialities such as geriatrics and old age psychiatry.

The PhD Clinical Training Fellow and senior clinical academic supervisors will be responsible for disseminating results to maximise impact. By sharing the predisposing and mediating factors of ED attendance identified from analysis, it is hoped that policy makers, commissioners, and clinicians will be better informed to make strategic, service and clinical end of life decisions, enhancing the quality of end of life care for people with dementia.

It is hoped it will be possible to measure direct benefit for patients when changes are made to reflect the increased awareness of the need for considered ED attendance at the end of life for people with dementia, although this is likely to take time. It is hoped these changes will include fewer ED attendances at the end of life by people with dementia. In future years, King's College London will be able to perform time-trend analysis to explore if outcomes have improved over time.

Outputs:

For all outputs, results will be presented as aggregate data with small numbers suppressed, in line with HES analysis guide. The PhD Clinical Training Fellow, with two senior clinical academic supervisors, will be responsible for dissemination of findings to local and regional policy makers, Clinical Commissioning Group (CCG) leads and clinicians to ensure results have appropriate reach and impact. In doing so, strategic, service and clinical end of life decisions will be better informed to improve the quality of end of life care for people with dementia.


Dissemination strategy:
Within 18 months of receiving access to the data, the following will be produced:

1. Peer-reviewed publication to open-access, high impact journals to reach as wide an audience as possible

2. Peer to peer dissemination of findings through international conferences, such as Alzheimer's Association International Conference and European Association for Palliative Care Congress. Although dates for 2021 are not yet available, based on this year’s virtual events, anticipated dates will be 26th-30th July and 6th-8th October, respectively.

3. A policy brief to summarise the results of the study and to respond to any relevant calls for information from MPs, healthcare committees, task forces or special interest groups. Any individuals or groups with an interest in end of life care policy and dementia will be actively sought for dissemination of findings. These groups include, although are not limited to, the Fix Dementia Care campaign (Alzheimer’s Society), In My Own Bed Please (independent group of researchers and physicians), John’s Campaign (carers of people with dementia), Find Your 1% campaign (Dying Matters, Hospice UK) and the End of Life Care Campaign (national charity coalition).

The purpose of these publications, presentations and policy brief is to disseminate the project’s findings to the scientific, clinical and policy-maker communities and provoke discussion on how the results might shape services and the end of life care experience for people with dementia.

The PhD Clinical Training Fellow has drawn on the established Patient and Public Involvement (PPI) infrastructure at the Cicely Saunders Institute (CSI). This includes presentation at a virtual PPI workshop and use of the CSI Public Involvement Forum, designed to facilitate discussions and feedback between PPI representatives and researchers. The PhD Clinical Training Fellow also meets bi-annually with two volunteers from the Alzheimer’s Society Research Network, who, with their lived experience, monitor the progression of the research project.

Consultation has to date focused on the importance of the research aim and questions for people affected by dementia (please see uploaded evidence). Continued PPI will be integral to the study, as volunteers will assist in identifying and developing themes from data and advising on and helping to develop and implement dissemination plans, including identifying wider dissemination groups. The aims of this involvement will be to ensure the outcomes measured are of relevance to patients and carers, providing interpretations of findings beyond a researcher perspective, based on their lived experience, and supporting effective dissemination of the study results to appropriate groups. The PhD Clinical Training Fellow will continue consultation with PPI members by email and using the CSI Public Involvement forum and will continue to have bi-annual meetings with Alzheimer’s Society Research Network volunteers. The next meeting is scheduled for December 2020.

To support PPI throughout the study, PPI members are invited to receive training, including that available at the local Biomedical Research Centre and Clinical Research Network, and will be asked to reflect on their learning needs throughout the project. PPI members have been and will continue to be reimbursed for out-of-pocket expenses and receive an hourly fee in recognition of their time and contribution, in accordance with NIHR Involve guidance.

Communication strategy:
Within 18 months of receiving access to the data, information about the project will be shared with interested groups and more broadly to members of the public through different channels including, although not limited to, the Cicely Saunders Institute webpage (https://www.kcl.ac.uk/cicelysaunders/newsevents/news) and YouTube channel (https://www.youtube.com/user/CSIKCL), social media platforms (i.e. @CSI_KCL, @ThomsLEA; linkedin.com/in/lesleythoms), and the Alzheimer’s Society, who is funding the study and with whom the PhD Clinical Training Fellow and supervisors have direct contact.

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)”

NHS Digital will create the cohort using specified filters (ICD 10 Codes relating to dementia - ICD-10 codes F00*-03* and G30), extract relevant records and pseudonymise the data.

There will be a single flow of linked and pseudonymised record level data from NHS Digital to King’s College London, with pseudonymised ID and no identifying data. There will be no further flow of data. King's College London will be the sole organisation involved in processing the data.

Researchers at King's College London will manage the storage, cleaning, analysis and interpretation of the data. The data will not be linked with any other record-level data or be matched with publicly available data. There will be no requirement or attempt to re-identify individuals from the data.

In accordance with the Data Sharing Framework Contract between NHS Digital and King's College London, data will only be accessed by individuals within the Cicely Saunders Institute, King's College London, who have authorisation from NHS Digital to access the data for the purpose described, all of whom are substantive employees of King's College London and trained in data protection and confidentiality.

King's College London will store the data on a secure server at the Cicely Saunders Institute, King's College London. Following review of King's College London remote working policies, authorisation of remote data access from NHS Digital was granted on the 23-06-2020, should the COVID-19 social restrictions prohibit travel and entrance to the Cicely Saunders Institute building. On this basis, data securely stored on the server will only be accessible from within the Cicely Saunders Institute building (located at Denmark Hill campus, King's College London) or remotely using authorised departmental laptops only by researchers named on the project.

Data analysis will be conducted by role-based access, limited to researchers working in the study team, on the departmental computer or laptop. The data will not be made available to any third parties.

Results will be presented at an aggregate level in research outputs, with small cell counts suppressed (n<10). All data will remain anonymous. No record level data falling under this agreement will be shared with any third-party.


Investigating the association between X-ray guided endovascular aortic aneurysm repair and incidence of cancer (v2) — DARS-NIC-467721-N7C0L

Opt outs honoured: Identifiable, Yes (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2021-07-09 — 2024-07-08 2022.04 — 2022.04.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

Objectives:

This application from King’s College London is to study the potential association between X-ray guided endovascular aortic aneurysm repairs (EVAR), which expose patients to radiation both during the procedure and follow-up CT scans, and future incidence of cancer. It is hoped that defining the risk of cancer after EVAR will contribute to the process of informed consent and decision making between open aneurysm repair and EVAR.

Primary objective:
To define the relative risk of developing cancer after EVAR versus after open repair for aortic aneurysms.

Secondary objectives:
To identify the types of cancers that develop in patients after EVAR.
To determine the median intervals between radiation exposure during EVAR and development of cancer.

Lawful basis:
King’s College London’s justification for processing is GDPR Article 6 (1) (e): The processing necessary to perform this task is in the public interest and the task has a clear basis in law. The results of this study will provide information about the risks of radiation-cancer associated with EVAR. Given that an alternative is available, these results could inform decisions about which treatment should be offered to patients in future. KCL are a public authority (university) carrying out a research project.

GDPR Article 9 (2)(j): processing is necessary for scientific research purposes and shall be proportionate to the aim pursued, respect the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject. This is a scientific research project.

Ethical considerations:
The dissemination of the aggregated results of this study pose minimal risk to the public.

Potential ethical considerations are that patients in the HES registry and NCRAS did not actively give consent for their data to be used for this study, and seeking consent is not feasible due to the number of patients involved and the fact that many of these patients will already be deceased. The study team have gained authorisation to use this data under s251 approval. Potential data breaches are another ethical consideration. The study team (at KCL) will be minimising this by requesting only pseudonymised data from NHS Digital and NCRAS and only the necessary data for the analysis to be transferred to KCL. However, there will be a need for one transfer of data owed a duty of confidence (NHS number and DOB) between NHS digital and Public Health England in order to facilitate data linking. Both NHS Digital and Public Health England will then send pseudonymised data to the research team at Kings College London. The data linkage between the NHS D data and the NCRAS data will occur based on the pseudo-IDs. The pseudonymised data received by KCL will be stored on 2 encrypted password protected computers.

The study team have discussed the feasibility of the proposal with NHS digital and Public Health England, who hold and manage the HES and NCRAS databases, respectively. Both of these organisations will be named as sources of the data on any ensuing publications. Publications resulting from this data will be readily available to healthcare professionals, patients, and the public.

Where possible, the study team have sought to seek the opinions of relevant patient groups and the public on this research. The study team recently held an event at the Academic Department of Vascular Surgery attended by vascular and cardiology patient groups, as well as donors and staff from the British Heart Foundation. This study proposal was presented and discussed during a session on the effects of ionizing radiation in vascular surgery. The study has also been discussed with the local Patient and Public Involvement group for their input.

It is hoped that the data requested will allow an assessment of the relative risk of cancer after EVAR compared to open aneurysm repair. It will also inform on the most likely types of cancer.

The request is part of a PhD based at the Academic Department of Vascular Surgery (King’s College London), a British Heart Foundation centre of excellence. The PhD student is substantively employed at King’s College London as a Clinical Research Fellow. The wider project commenced in October 2018 and is investigating the effects of radiation in vascular surgery, both on patients and surgeons.

The data requested here will be used for the described segment of the project only and will have no use in any other segment of the wider project. However, the wider project, as above, commenced in October 2018 and is investigating the effects of radiation in vascular surgery, both on patients and surgeons. This mainly involves basic laboratory research and is a collaboration between the team at King’s College London and the Centre for Health Effects of Radiological and Chemical Agents (Brunel University) and the Centre for Radiation, Chemical and Environmental Hazards (Public Health England). The requested data will be used for the arm of the study investigating the long-term effects of radiation from EVAR on patients. The PhD consists of several parts - one of which depends on the requested data from NHS Digital and PHE.

The subjects in this study are all patients over 50 years old who have undergone aortic aneurysm repairs. The study arm will be made up of those who underwent an endovascular aneurysm repair (EVAR), which involves radiation, whereas the control arm is made up of patients who underwent an open aneurysm repair. Within the EVAR group, the patients can be further subdivided into simple and complex EVAR for subgroup analysis.

The purpose of this project is to investigate the association, if any, of radiation exposure during endovascular aneurysm repair (EVAR) with future development of cancer. For this the study team will be comparing a cohort of patients undergoing EVAR with a control cohort undergoing open aneurysm repair.

Patient identifiers (DOB and NHS numbers) will be required in order to facilitate linking of HES data with the National Cancer Registration and Analysis Service (NCRAS) database. Patient demographics, age, past medical history and social history are also required to account for confounding factors during statistical analysis.

Once the initial transfer from NHS digital to PHE (NCRAS) is complete, patient identifiers will be removed, and the research group will receive pseudonymised HES data.

The number of years requested is based on the following power calculation.
To achieve 95% confidence, 80% power assuming proportion of deaths caused by any cancer of 20.9% (EVAR) and 19.7% (open) – these figures are taken from the currently available literature.
Recommended sample size = 39,000 patients (13,000 EVAR, 26,000 open)
+ 3% for attrition of data = 40,170 (13,390 EVAR, 26,780 open)
Based on approximate number of patients undergoing EVAR and open aneurysm repairs in England each year, 18 years of data will be required to achieve these number.

Only data that will be required from statistical analysis to answer the study question has been requested. Patient identifiers will be required for data linkage with NCRAS so once the HES data has been extracted by NHS Digital based on ICD-10 and OPCS-4 codes, the relevant identifiers (NHS Number, DOB) and pseudonymised data (Date of Surgery and Study ID) will be passed to PHE. However, beyond the first transfer of data from NHS digital to PHE, patient identifiers will not be used, and the resultant HES data will be pseudonymised before being sent to the research team at KCL.

Data Flow

The steps involved in this are as follows:
1) King’s College London provides inclusion criteria to NHS Digital
2) NHS Digital identifies patients from HES according to ICD-10 and OPCS-4 codes
3) NHS Digital transfers identifiers of those patients only (NHS number, DOB) along with pseudonymised data (date of surgery, pseudo ID) to Public Health England. This will be done under DARS-NIC-467721 (THIS AGREEMENT)
4) NHS Digital transfers patient demographic and surgical data and pseudo IDs to King’s College London. This will be done under DARS-NIC-264102
5) Public Health England extracts cancer data relevant to these patients from NCRAS
6) Public Health England sends cancer data and pseudo IDs to King’s College London
7) Linking of demographic, surgical and cancer data at King’s College London (via pseudo study ID)

The sole data controller will be the research team at King’s College London as previously detailed. The other organisation involved is National Cancer Registration and Analysis Service (NCRAS), based at Public Health England (PHE). The team at PHE will provide cancer data from NCRAS pertaining to the patients identified from the HES database.

The primary investigator is a substantive employee of King’s College London and has a clinical role at St Thomas Hospital. No other St Thomas Hospital staff will be involved in the project. The PI will lead on the processing of the data and will be responsible for any output from this project.

No other organisations will be involved in accessing or processing this data. The Centre for Health Effects of Radiological and Chemical Agents (Brunel University) is involved in the wider project and their role is specifically in the processing of biological samples. They will not be involved in the processing or decision making regarding NHS Digital data.

No funders/commissioners will be involved in the project.

******This application is for the flow of data to PHE********

Expected Benefits:

It is anticipated the data will inform on the risk of radiation-related cancer after endovascular aneurysm repairs and be beneficial when informing and consenting patients for operations and help them decide, with the clinical team, which procedure is most appropriate for them. It is anticipated the information will also inform the vascular community about the long-term risks of these procedures and contribute to the debate about the cost effectiveness of endovascular aneurysm repairs. The dissemination of the results will be in the public interest as it will provide transparency around the knowledge base upon which treatment decisions are taken.

Ultimately, patients will be reliably informed of their risk of developing cancer after endovascular aneurysm repairs. They will be able to use this information in deciding whether to accept that risk or opt for an open surgical repair, or indeed to decline surgery altogether.

It is hoped the outputs will provide a calculation of the relative risk of developing cancer after having an endovascular aneurysm repair versus and open aneurysm repair. After accounting for confounding factors, a comparison will be made between the two procedures, thus achieving the stated purpose.

It is hoped that the benefits of this project will be to add to the current knowledge base and better inform patients with abdominal aortic aneurysms about their options and the risks involved.

The research team are clinicians in vascular surgery and therefore will be able to directly use the outputs of this project to inform their patients. Hopefully, dissemination of data will allow other clinicians to do the same.

******This application is for the flow of data to PHE.********

Outputs:

The data will be analysed by the research team at King's College London and its conclusions will be published in the medical literature in adherence to local publication policies. The outputs of this project will also contribute to a PhD thesis. All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. NHS digital and PHE will be named as sources of the data on any resulting publications. The conclusions of the study will also be disseminated by way of presentations at vascular surgery conferences such as the Vascular Society of Great Britain and Ireland, Charing Cross Symposium, and the European Society of Vascular Surgeons. As a result of participation at these conferences, the headline messages from the project may be shared on social media platforms.

By these means of publicly available medical journal publications and conference presentations, the key message of the relative risk of radiation-related cancer after endovascular aneurysm repairs will be disseminated. This information will be beneficial when clinicians are informing and consenting patients for operations and help them decide, with the clinical team, which procedure is most appropriate for them. Furthermore, these conclusions will add to the current knowledge base and better inform patients with abdominal aortic aneurysms about their options and the risks involved.

The raw data will be deleted at the end of the study. The target date for completion of the study is October 2023.

One member of the research team who will be involved in data analysis is currently undertaking a PhD and is a substantive employee of King's College London. The outputs of this project will contribute to his PhD studies.

******This application is for the flow of data to PHE.********

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)”.

Patients undergoing aortic aneurysm repair either by an open approach (OAR) or endovascular approach (EVAR) between January 2000 and December 2018 will be identified by NHS Digital from the Hospital Episode Statistics (HES) dataset using OPCS codes.

These patients will be over the age of 50, as those under the age of 50 have a different pathology which makes them unsuitable for this study. This should provide approximately 40,000 patients as per the sample size calculation detailed above.

Once the patients have been identified from HES by NHS Digital, the national opt-out will be applied to remove any patients who have requested an opt-out. Patients aged under 50 years at time of operation and patients having their operation outside of England will also be excluded at this stage.

A list of the remaining patient NHS numbers, dates of birth and a unique pseudo ID will be transferred to Public Health England (PHE) by secure electronic transfer agreed between NHS Digital and PHE. This will be done under DARS-NIC-467721 (THIS AGREEMENT)
Patients will be identified by ICD-10 diagnostic codes for aortic aneurysm and also by OPCS-4 for various types of aortic aneurysm repair as follows:
ICD-10 Diagnostic codes – 1714, 1719
OPCS-4-Procedural codes – L184, L185, L186, L188, L189, L194, L195, L196,L198, L199, L231, L236, L238, L239, L254, L258, L259, L49, L271, L275, L276, L278, L279, L281, L285, L286, L289

At PHE, the National Cancer Registration and Analysis Service (NCRAS) will perform a look up on the cancer registry using deterministic matching based on NHS number and date of birth. This process will identify which patients developed cancer after their procedure. Follow-up on NCRAS will continue to December 2020 such that any patients from the original HES dataset who have a diagnosis of a primary tumour as per future NCRAS data releases can be included in the analysis.

PHE will then send the cancer data including date of diagnosis, type and stage of cancer to King’s College London (KCL) in a pseudonymised format using pseudo IDs.

NHS digital will also send the demographic (date of birth, sex), clinical details (e.g. smoking status, diabetes, heart disease) and operative details to KCL in a pseudonymised format using the same pseudo IDs. This will be done under DARS-NIC-264102.

Linking of pseudonymised data from HES and NCRAS will then be performed at KCL. At this point, dates of surgery will be compared with dates of cancer diagnosis to allow exclusion of patient with pre-existing cancers or previous radiotherapy treatment. An interval period between date of surgery and date of cancer diagnosis will also be applied to account for concurrent diagnoses.

******This application is for the flow of data to PHE.********


TRIANGLE HES Data Application — DARS-NIC-272253-P9X9Y

Opt outs honoured: Anonymised - ICO Code Compliant, No (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-09-30 — 2024-09-29 2022.02 — 2022.03.

Access method: Ongoing, One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Emergency Care Data Set (ECDS)
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Admitted Patient Care
  4. Mental Health Services Data Set

Outputs:

The overall aim of this research study is to inform clinical practice within the NHS. The proposed dissemination plan is multi-faceted and will target various audiences at different levels, acknowledging the wide range of stakeholder groups with an interest in the TRIANGLE intervention:

The study protocol (Cardi et al., 2017) was published by the study team in the European Eating Disorders Review in 2017 and is accessible here: https://onlinelibrary.wiley.com/doi/abs/10.1002/erv.2542. Qualitative findings have been published (Clark Bryan et al., 2020) and indicate the valued nature of remote support from the perspective of the TRIANGLE patient and carer cohort, during conditions of increased isolation and reduced access to eating disorder services (i.e. https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/erv.2762).

The research team will submit further scientific reports to peer reviewed journals for publication. Early secondary level academic papers from the baseline data are planned for submission in 2022, reporting on the comparison of the baseline variables and service use / carers of adult patients with severe AN in the early vs the late phase of AN- on service use.

The proposed late trial phase academic papers include:
(1) A Randomised Controlled Trial comparing a joint family intervention (Transition Care in Anorexia Nervosa Through Guidance Online from Peer and Carer Expertise (TRIANGLE)) with treatment as usual. 12 months outcome, cost effectiveness (to help address the primary outcome).
(2) A Randomised Controlled Trial comparing a joint family intervention (Transition Care in Anorexia Nervosa Through Guidance Online from Peer and Carer Expertise (TRIANGLE)) with treatment as usual. 18 months outcome, cost effectiveness (or perhaps a combination or Paper 1 and Paper 2).
(3) Predictors of service use. 12- & 18-months outcomes.
(4) Trajectories of illness following inpatient care.

Additionally, KCL aim to present their findings at hosted events such as eating disorder, psychiatric, student counselling and primary care conferences and to special interest groups within the professional bodies of the multiple disciplines involved in the care of this group of patients (nurses, psychology, occupational therapy, dieticians, social workers, etc.). These plans are hoped to be in place from 2023.

Data sharing with potential collaborators (UK and International) will be encouraged in an anonymised format, aggregated with small numbers suppressed. The researchers also aim to present the findings via online events such as presentations, webinars, online conferences etc. So far, during the study, the digital intervention has been presented to the Consultant Psychiatrist and his team from the Anxiety Disorders Residential Unit at the Bethlem Hospital (part of South London and Maudsley NHS Foundation Trust in the UK) who aim to develop a transition tool.

The carer component of the intervention has been used to facilitate carer groups within SLAM eating disorder services for adults via Zoom. The intervention is also being adapted to be tested in child and adolescent services in collaboration with the Clinical Lead for the Eating Disorder Service for Young People (Northwest Boroughs Health Care NHS Foundation Trust) and Honorary Clinical Lecturer, University of Liverpool.

Policy:
A full report with the executive summary will be sent to all NHS commissioning agencies. The co-applicant LG, CEO of the Beating Eating Disorders (BEAT) charity, will use this to assist in dialogues with policy makers, including MPs.

Patients and public:
Patients and the public are a core part of the research study and have been involved at all stages of the research process so far. BEAT will coordinate the patient and public involvement aspect of dissemination. Dissemination strategies will include emails updates to participating patients, carers and hospitals, presentations/blogs on eating disorder charities and carer and user websites, and communication channels (FEAST; Families Empowered and Supporting Treatment of Eating Disorders, BEAT, Student Minds, etc.) at yearly carers and users’ workshops, media articles, discussion forums, website postings, and schools’ training events. Training will be conducted through presentations, discussions, small group teaching and large group seminars. A summary of findings will be made available on the websites of the key charities and the Psychological Medicine website at the Institute of Psychiatry. All participants will also be sent newsletters and will have free admission to the carers conference.

Media:
The Press Offices at South London and the Maudsley NHS Foundation Trust and Kings College London will co-ordinate dissemination to the media. Researchers at KCL aim to present the results on radio stations Woman's Hour and All in the Mind, via academic webpages and via social media platforms such as Twitter (please see @kingsedresearch). The study team will also inform patient participation groups, newspapers, and neighbourhood organisations to disseminate findings in an anonymous form, aggregated with small numbers suppressed.

Processing:

Data processing will only be carried out by substantive employees who have been appropriately trained in data protection and confidentiality.

The data will be stored on the “King’s College Military Health Research” (KCMHR) secure network and will be accessible from a single nominated machine within the eating disorders research unit (system access will be granted by KCMHR). The person(s) will be granted access to the data once they have completed the required training and have signed the KCMHR confidentiality agreement. King’s College London performs weekly secure offsite backups stored at a data centre in Slough. This procedure follows Cyber Security Essentials guidelines. All data stored on the KCMHR network is encrypted prior to these back-ups taking place. Only KCMHR IT management have access to the encryption keys.

King’s College London will supply the following information about each patient:
Study ID
NHS Number
Gender
Date of Birth
Date each participant was consented into the trial
CONSENT_1 - Earliest date patient information will be requested
CONSENT_2 - Latest date patient information will be requested

DATA FLOW
1. KCL researchers will create a file containing personal identifiers (i.e., study ID, date of birth, Gender, postcode) for consented TRIANGLE participants.
2. This file will contain a TRIANGLE Study ID, which is a personal identification number used by KCL researchers to identify consented TRIANGLE participants.
3. TRIANGLE study IDs will then be pseudonymised in a separate file to protect the confidentiality of the data; this pseudo-ID will be created for the purpose of sending data to NHS Digital to undertake linkage.
4. The TRIANGLE Study ID and pseudo-ID will be stored on an encrypted device within the KCMHR secure server.
5. KCL researchers will create a file with personal identifiers, the pseudo-ID, removing the original TRIANGLE Study ID and remainder of the cohort data.
6. This dataset will be sent securely by KCL researchers to NHS Digital.
7. NHS Digital will link the personal identifiers (i.e., study ID, date of birth, Gender, postcode) to HES and MHSDS data for the consented cohort.
8. KCL researchers will receive a pseudonymised linked dataset containing the requested HES, ECDS and MSDS variables with only a pseudonymised ID to ensure KCL researchers cannot identify patient records.
9. KCL will link this dataset containing HES and MHSDS data to the TRIANGLE pseudonymised cohort data using pseudo-ID as a linkage key, resulting in an analysis dataset containing pseudonymised HES, MHSDS and TRIANGLE cohort data.
10. The raw data will be stored on the KCMHR secure server till the DSA end date. Once the DSA ends KCL will securely destroy NHS Digital data and provide NHS Digital with a data destruction certificate.

There will be no subsequent flows of data.

DATA MINIMISATION
The following steps are taken to mitigate any risk of reidentification where data is linked:
• The pseudo-ID and TRIANGLE Study ID are stored on encrypted device in the KCMHR secure server.
• NHS Digital will remove personal identifiers from the HES and MHS dataset and send the pseudonymised dataset (including pseudonymised ID) securely back to KCL.

Once the HES and MHSDS data has been received by the data recipient at King’s College London, there will be no requirement/attempt to re-identify individuals.

Researchers from KCL will be using 5-character provider codes and site treatment codes to identify if care has been provided in the independent sector.

Researchers from KCL will provide NHS Digital with the consent date variables (this is the date each participant was recruited into the trial), to enable accurate windows of data to be provided for each participant. For all records researchers from KCL request data from each participant 12 months prior from their consent date and 18 months after their consent date.

Minimum datasets requested:
Researchers from KCL have requested four datasets:
Hospital Episode Statistics Admitted Patient Care,
Hospital Episode Statistics Accident & Emergency,
Emergency Care Data Set (as HES A&E ceased collection after 19/20) and the
Mental Health Services Data Set.
It is not relevant for the data to be narrowed further by clinical factors as the aim is to assess total length of stay in hospital for general admissions for any health problem. All patients’ episodes are required as researchers need to assess readmission rates. Maternity episodes are required, but the unborn child and neonatal records are not necessary, so these have not been requested.

Minimum patient records requested:
370 patient records have been requested, as that is the number of patients who have consented overall to participate in the research trial. This cannot be minimised further as a power calculation was used to inform researchers that approximately 370 patients were required to be able to statistically detect differences in total number of mental health contacts between the two study groups in the trial.

Minimum study time periods requested: 31/07/2016 – 20/01/2022
The period requested only spans the 30-month period for each participant in the trial, according to the consent that they have provided. Participants have provided consent for 30 months of their data to be used by researchers at KCL beginning one year prior to the date of randomisation using consent forms and an online method on the study website. The first patient in the overall cohort was randomised at 31/07/2017 – so data will be requested for participants starting from 31/07/2016 onwards, depending on each participant’s randomisation date. The last overall cohort participant was randomised at 20/07/2020 – so data will be requested up until 20/01/2022, as this date is 18 months post-randomisation. This period is necessary for researchers to assess the effectiveness of the intervention, as well as assess length of stay in hospital in the year prior to admission and eighteen months following randomisation into the trial.

Cohorts / Linkages:
Mental health service data will be linked to HES and ECDS data by NHS Digital. As the cohort were recruited into the trial from specialist eating disorder units it is very likely that there will be an associated mental health record for cohort patients. Therefore, the request to access and link both these data sets would be a logical and beneficial process to meet the outcomes of the trial. Furthermore, researchers at KCL could use these data relating to instances of service use with mental health services to calculate more accurately the costs associated with community-based MH provision for this cohort.


Mental illness, mental health service use, and lifetime domestic violence perpetration: an observational study. — DARS-NIC-207675-J4L7G

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2020-10-12 — 2023-10-11 2020.10 — 2021.05.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey

Objectives:

King's College London (KCL) requires data to examine the association between mental health and lifetime perpetration of domestic violence. KCL researchers aim to identify whether there is a significant relationship between mental health and perpetration of domestic violence and, if such a relationship exists, whether or not this can be explained by prior trauma; use of alcohol and/or drugs, and/or socioeconomic position. Given that much violence in the general population is gendered, KCL researchers wish to also assess whether there is a link between mental health and perpetration/victimisation in men and women. It is for this reason that KCL are requesting access to the 2014 Adult Psychiatric Morbidity Survey (APMS) dataset.

Access to the pseudonymised 2014 APMS dataset will support an ongoing body of work carried out by KCL’s Section for Women's Mental Health. The Section was set up to investigate the mental health needs of women, in response to the needs for the NHS, PHE, and the broader scientific community, with the aim of improving the mental health of women while further understanding and addressing violence and abuse. Prior to this request several meetings with mental health service users have been held to shape the purpose of the research. In these meetings it was identified that there is insufficient support for service users who were perpetrators of domestic violence.

It is intended that the findings from this analysis will inform a programme of work on the response of mental health services to the perpetration of domestic violence enabling an assessment of how best to identify mental health service users presenting the greatest risk of domestic violence and determining the treatments that might be most effective in reducing the risk of domestic violence.

The lawful basis for processing in this instance is GDPR Article 6(1)(e) ‘public task’ whereby processing is necessary to perform a task in the public interest. The processing of special category data can be justified under GDPR Article 9(2)(j), where processing is necessary for archiving, research and statistics (with a basis in law). This research is in the public interest because the processing of this data may yield benefits for the users of mental health services, carers/family members of people with mental illness, mental health professionals, and wider society. In addition to this processing may allow the identification of specific groups at relatively greater risk of domestic violence perpetration and/or victimisation.

There is currently limited epidemiological evidence on the perpetration of domestic violence, and improved knowledge in this area will enhance wider societal response to perpetration of domestic violence, as part of a future national perpetrator strategy. Globally, one in three women report domestic violence in their lifetime and improving evidence on perpetrators could result in added improvements in this area, leading to violence reduction.

All individuals who participated in the APMS were consenting adults living in England and Wales and, as such, the processing of their data for the purposes described here should not come as unexpected. As APMS is a nationally representative survey it provides an opportunity to generate the first nationally representative data on perpetration of domestic violence in relation to mental illness, as such KCL wish to receive national APMS data.

KCL is the sole data controller for the purpose of processing outlined above. KCL will be the only organisation processing the data for this purpose.

Expected Benefits:

Violence is a detriment to population health and places a large burden on the UK health and social care services. This research may allow health care professionals to better identify, assess and respond to domestic violence in the context of mental illness, and to better understand the possible role of mental health treatments.

The findings yielded from this study will inform national efforts towards a perpetrator strategy (linking different sectors but including mental health services) and will help to identify directions for more detailed scientific study of existing responses. As many as 40% of general population have experienced violence and abuse, and, based on existing evidence of association of perpetration of domestic violence with mental disorder, mental health services may play an important role in a national response to perpetrators- particularly if psychiatric or behavioural interventions play a role in shaping occurrence of violence in this group.

Evidence produced because of data processing will be in a position to shape national guidance on commissioning, and clinical management guidance on domestic violence (for example, in the context of alcohol/drug misuse).

Indicators of benefit will be: citation in local policy guidance on the management of domestic violence, citation in national reports on domestic violence perpetration, scientific citation. The incorporation of this evidence into guidelines could be expected to improve knowledge on the characteristics of perpetrators of domestic violence (DV), and the quality of service delivery, through better identification of risks.

It is expected that these benefits will be achieved in the five years following the publication of the scientific report detailed in section 5c.

This research is not in support of PhD or postgraduate study.

Outputs:

The data processing described above will result in a project report and scientific papers submitted for peer review. Presentations will be produced for the KCL Section of Women’s Mental Health, and the UKRI Violence, Abuse, and Mental Health Network.

Findings will also be disseminated to researchers via epidemiological networks including the Society for Epidemiological Research and the International Federation of Psychiatric Epidemiology. Further to this, findings will be presented via workshops to networks of researchers with a focus on violence and abuse, including the UKRI Violence, Abuse and Mental Health Network.

Existing infrastructure will be used to communicate findings to individuals who took part in the collection of the APMS dataset (APMS individuals).Findings will be shared with the Economic Social Research Council (ESRC) Centre for Society and Mental Health to reach a wide range of academic and policy-making communities. Scientific findings will primarily be communicated in psychiatric journals (BJPsych, Lancet Psychiatry) and violence focused journals (Trauma, Violence and Abuse, and the Journal of Interpersonal Violence).

Active public engagement with scientific messages will be encouraged over social media using tweet threads, blog posts, and press releases. Where possible given support arrangements at the time of publication, scientific reports will be published in open access journals to ensure the widest possible reach, for the purpose of the results reaching carer networks, victims/survivors and people with lived experience of mental illness.

To allow replication of scientific findings in other data, code will be published alongside scientific reporting. Target dates for the final scientific report and related manuscripts and all other outputs is December 2021.

Communication of scientific findings will be done sensitively, and mindful of not contributing to mental health stigma. Children's will not be processed.

The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

Processing:

There will be no flow of data from KCL to NHS Digital.

The 2014 APMS data set is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk) and the UKDS is responsible for dissemination under direction by NHS Digital. King's College London will receive the pseudonymised APMS data set. There is no facility to select individual variables. KCL will be able to download the data set from UKDS for the period specified within the Data Sharing Agreement and must securely destroy all local copies of the data set when the Agreement expires and notify NHS Digital in line with standard procedures. This 2014 version of the data set available has been redacted on Disclosure Control Procedure advice to minimise the likelihood of individuals being able to identify anyone taking part in the survey.

UKDS will transfer the pseudonymised APMS data to KCL. No other organisations will be involved in the flow of data.

It is intended that the APMS data received from NHS Digital will be described in statistical software, and analysed for association between exposure and outcome, as well as other variables. The statistical analyses performed should allow researchers to determine 1) whether there is a significant relationship between domestic violence perpetration and mental health, 2) whether this relationship can be explained by other factors (e.g. prior trauma, use of alcohol and/or drugs, socioeconomic position), and 3) if this relationship varies across different genders.

Data will be inspected to look for errors and cleaned as necessary. Correlations will be examined between the survey items (e.g. , survey weighting, age and sociodemographic variables, violence-related items, and mental health items). Researchers will assess the overlap between mental health and domestic violence-related variables, for errors and pre-analysis processing. Basic descriptions of bivariate distributions with victimisation will be tested, before and after statistical modelling (to account for other explanations of a link between domestic violence and produced, to identify basic data patterns. Analyses will then assess association between victimisation and a range of different mental health indicators).
Results will be displayed in tables with small numbers suppressed and reports -related characteristics, including depression, anxiety, and psychotic experiences. Adjustments will include socioeconomic and demographic characteristics.

The analysis will examine the overlap between domestic violence and factors. This may involve examining associations of lifetime perpetration of domestic violence with age, gender, and educational attainment, and mental health indicators including common mental disorder. Inclusion of covariates such as age, gender, educational attainment, and alcohol use in the assessment of association between mental health (including depression and anxiety).
This analysis plan respects the essence of the right to data protection, and clear and specific measures will be implemented to safeguard the rights and interests of the data subject.

Under this agreement data received from NHS Digital will not be linked and there will be no attempt to re-identify individuals who completed the APMS survey.

Data provided under this agreement will only be processed by substantive employees of King’s College London, all of whom have been appropriately trained in data protection and confidentiality.

KCL will store the data on servers behind a firewall which are inaccessible from the outside world, except via a Virtual Private Network (VPN), which provides a password-protected, encrypted, private communication channel for staff working outside the office. All analyses will be therefore be done on KCL equipment behind secure firewalls.


The National Early Inflammatory Arthritis Audit Data Linkage Request — DARS-NIC-199726-F4V3C

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Yes (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2019-03-14 — 2020-09-30 2019.09 — 2021.05.

Access method: One-Off, Ongoing

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Hospital Episode Statistics Outpatients
  3. HES:Civil Registration (Deaths) bridge
  4. Hospital Episode Statistics Admitted Patient Care
  5. Civil Registration (Deaths) - Secondary Care Cut

Objectives:

Aim and purpose of the application:

The Healthcare Quality Improvement Partnership (HQIP) are the sole data controllers. HQIP commissioned the British Society for Rheumatology (BSR) to undertake the NEIAA as part of the National Clinical Audit and Patient Outcomes Programme (NCAPOP).

The British Society for Rheumatology is the UK's leading specialist medical society for rheumatology and musculoskeletal professionals. The BSR subcontracted an academic unit at King's College Hospital NHS Foundation Trust (KCH) to carry out the data processing, including all analyses and linkage.

The Healthcare Quality Improvement Partnership (HQIP) requires hospital episodes statistics (HES) and mortality data for use in the National Early Inflammatory Arthritis Audit (NEIAA). This audit will help to improve the quality of care for people living with inflammatory arthritis across England and Wales. The current contract period is 1 October 2017 – 30 September 2020, with a further planned two year extension.

The aim is to improve the quality of care for people living with inflammatory arthritis by assessing the performance of rheumatology units against NICE Quality Standards. There is compelling evidence that early intensive treatment greatly improves the outcome of these disabling diseases, which predominantly affect people of working age.
Early diagnosis and treatment is a cornerstone of Early Inflammatory Arthritis (EIA) management and is underpinned by NICE guidelines (CG79). The audit will assess EIA services and will collect prospective data including:
• Waiting times;
• Time to treatment;
• Provision of education;
• Collection of patient reported outcomes;
• Clinical response.

• What’s included:
– NHS secondary care settings in England and Wales.

• What’s excluded:
– Children and children’s services
– Primary care

The linkage requested is necessary for the performance of a task carried out in the public interest; improving the quality of care for people living with inflammatory arthritis (covered by Article 6 (1)(e) of GDPR). Processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

The data requested will help to achieve the aim identified in the following ways:
(1) Deliver quality metrics to inform Care Quality Commission (CQC) regulation of providers.
(2) Create a dataset to inform quality improvement activity.
(3) Create a dataset for epidemiological and health service research.
(4) Quantification of the burden of disease for patients and society.
(5) Provide evidence for cost effective service delivery.
(6) Provide aggregate department level performance data for the Getting It Right First Time (GIRFT) programme

Data subjects:

Data are collected from all patients in England and Wales over the age of 16 who are seen in rheumatology services with a suspected diagnosis of early inflammatory arthritis.

Purpose of Request:
The collected audit data will be linked with the HES Outpatient and HES Admitted Patient Care dataset. It will also be linked the patient episode database for
Wales (PEDW), pending approval from the NHS Wales Informatics Service. This will enable
ascertainment of joint replacements, unplanned hospitalisations, and death. These linkages will be repeated annually. Only pseudonymised data will be requested - identifiers will be removed and a study ID will replace the identifiers.

There will also be linkage to the Civil Registration/Mortality data set to determine mortality outcomes. In addition data on the total number of patients diagnosed with rheumatoid arthritis in outpatients for each trust will be requested.

Data linkage will enable estimation of variation in the following:
(1) Treatment delay (outpatient referral dates, diagnostic imaging dates),
(2) Clinical outcomes (adverse events/unplanned hospitalisation, joint replacement surgery, mortality),
(3) Healthcare resource utilisation (outpatient activity in 12 months following diagnosis),
(4) Case-mix adjustment, and
(5) Allow an assessment of case ascertainment.

All data requested from NHS Digital will be pseudonymised data, this will allow patient level linkage while maintaining patient confidentiality.

Linkage is requested for the duration of the contract of the project, and for all Trusts in England as NEIAA is a national project. There are no alternative less intrusive methods to achieve the above purpose of linkage.

Data linkage will be reviewed on an annual basis to assess if the degree of data requested can be minimised.

The data processing under this agreement is not in support of a specific PhD/post graduate research study, but may be utilised for future work, in the future. An amendment to this agreement or separate data sharing agreement will be formulated and submitted to NHS Digital for approval for this in the future if necessary.

Yielded Benefits:

There are already clear signs since the launch of NEIAA that that it is helping to improve the quality of care for patients with EIA across England and Wales. Specific evidence of public benefit that has helped been achieved with the use of the NHS Digital data includes the following: • Publication of the first annual report, including a patient and public report. • Use of NEIAA data in Getting It Right First Time (GIRFT) reviews of rheumatology services in England • Collaboration with the Care Quality Commission (CQC) to develop 4 core provider-level metrics from the audit for inclusion in CQC reviews • Development of the Best Practice Tariff (BPT) in England, linked to audit data, to incentivise good quality care • Improvement in key metrics of EIA care- review time and treatment time • Evidence from trusts and health boards of improvements driven by NEIAA, including action plans, creation of new posts, introduction of additional/dedicated EIA clinics, changes in referral triage processes, and GP education initiatives. • Commendation in the HQIP Richard Driscoll Memorial Award for outstanding progress in demonstrating robust and sustained patient involvement in developing clinical audit and in reporting outcomes for patients through the programme.

Expected Benefits:

Dissemination of the NEIAA results will identify variation in early inflammatory arthritis care across England and Wales. Publication of this will reduce national variation in the quality of care in early inflammatory arthritis. More patients will attain a state of disease remission during their first year of treatment, fewer people leave work as a result of their arthritis, and overall quality of life for people diagnosed with inflammatory arthritis will improve.

In order for the benefits to be achieved, outputs will be used by the CQC to identify outlier rheumatology departments. This will lead to increased scrutiny and support for under-performing departments. The NEIAA team have already engaged with the CQC, who have confirmed they will be utilising performance measures from the project to assess departments. In addition, aggregated data with small number suppression will be provided to the Getting It Right First Time Programme (GIRFT) to assist departments in improving the quality of care delivered.

The Benefits:
A central tenet of undertaking a National Audit is to deliver change that will extend beyond the local Trust level.
(a) Deliver quality metrics to inform Care Quality Commission (CQC) regulation of providers.
(b) Create a dataset to inform quality improvement activity.
(c) Create a dataset for epidemiological and health service research.
(d) Quantification of the burden of disease for patients and society.
(e) Provide evidence for cost effective service delivery.



Outputs:

The following outputs will be produced:
a. A publicly available report with site, Trust, clinical commissioning group (CCG), and regional level data, will first be published in July 2019, and will be repeated on an annual basis. The report will include performance against the NICE quality standards for early inflammatory arthritis. The report will only contain aggregated data with small number suppression applied in line with the HES analysis guide.

b. Academic papers will be published in Rheumatology Journal on methodology, care variation, and impact of timely treatment on mortality and inpatient admissions. The BSR website will provide links to open access papers. The papers will only contain aggregated data with small number suppression applied in line with the HES analysis guide.

c. For each paper published, a short presentation is developed to summarise the findings for a range of stakeholders, including healthcare professionals and patient groups. Findings will be presented at project working group meetings.

d. Findings will be submitted for presentation at Rheumatology, EULAR, and ACR conferences in 2020.

e. The website dashboard will provide case-mix adjusted departmental data as a result of the linkages obtained. As above, all data will be presented at aggregate level, with suppression of small numbers in line with the HES analysis guidance.

Dissemination of results/outputs:
Aggregated findings will be primarily disseminated in a publicly available annual report. Academic papers will be disseminated via peer reviewed journals. Key findings will be disseminated to rheumatologists via the BSR newsletter. All reports and open access journal articles with be accessible via the BSR website.

Webinars providing updates on the audit are regularly made available on the BSR website.

Communication of results/outputs:
Summary level findings for health professionals and the general public will be available via the BSR website. Key findings will be reported publicly via social media. Again all results and findings will only contain aggregated data with small number suppression in line with the HES analysis guide.

Exploitation of results/outputs.
The data and knowledge collected in NEIAA are owned by HQIP, and managed by the BSR. Only aggregate data in annual reports will be open access.

The first annual report is expected to published in July 2019.

Processing:

All organisations party to this agreement will comply with the Data Sharing Framework Contract, including requirements on the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

1) Data flow to NHS Digital:
KCH will share patient identifiable information including unique study ID, NHS number, date of birth, and postcode for the purpose of linkage to NHS Digital. NHS Digital will link these identifiers to the HES OP, HES APC and Civil Registration/Mortality Database.

2) Data flow from NHS Digital to KCH:
NHS Digital will share the requested products (HES OP, HES APC, Civil Registration Data) alongside the unique study ID number provided by KCH. NHS Digital will share no identifiable information in the disseminated extract.

3) Data flow includes patient level information from providers to KCH and also from NHS Digital to KCH. Onward data flow from KCH to HQIP, the BSR and subsequent dissemination is aggregate, with redaction of data from sites with 5 or fewer subjects recruited to maintain anonymity (ie small number suppression in line with the HES analysis guide)

4) Data processing of the audit data (not NHS Digital data) takes place by Net Solving at the point of data entry from the providers. KCH then process the data for analysis, including preparing the linkage file for NHS Digital and then subsequently receiving the NHS Digital linked data.

5) Net Solving manage the online data entry portal and the data extract too for the audit data. Net Solving undertake no data manipulation and will have no access to the data disseminated by NHS Digital. KCH then process the data for the purpose of answering the specific questions set out by HQIP for NEIAA. KCH also receive the NHS Digital linked data for the same purpose. KCH produce aggregate data reports using the NHS Digital data.

6) The online portal entered data are linked to IMD rank (the Index of Multiple Deprivation (IMD) is a measure of relative deprivation for small areas), using postcode. The clinical data-set will be linked to the disseminated NHS Digital data extract using the IMD rank not postcode.

7) IMD rank is publicly available, and will be linked via the patients' postcode. After which the postcodes will be deleted from the data-set to reduce the risk of identification.

8) Linked data will be associated with a unique study ID. All patient identifiable data will be removed to prevent re-identification once data has been linked.

9) There will be no requirement/attempt to re-identify individuals within the extract.

10) Data provided by NHS Digital will only be accessible by individuals within the academic team at KCH who have authorisation from the academic lead to access the data for the purposes described. All individuals accessing data will have undergone GDPR training, and are substantive employees of the named data processors on the agreement.

11) Access to the NHS Digital data will only be granted to authorised substantive employees of the data processor. Third party organisations would have to make a formal NHS digital data access request in order to obtain the data-set.

12) KCH will store the data on a KCH secure server, which can only be accessed on site. Once linkage has occurred, the patient identifiable data used for linkage held by KCH will be destroyed. Linked data will never be stored in the same location as participant identifiable information.

13) The data will be stored on the premises of the data processor.

14) Summary level reports will be provided to HQIP and the BSR for public use and dissemination from KCH after the data processing has taken place. These summary level reports will only contain data that has been aggregated with small number suppression in line with the HES analysis guide.

15) All aggregated reports will suppress small numbers in line with the HES analysis guide.

There will no linkage permitted to other data sets apart from what is detailed in this agreement.

There will be no attempts by employees of the named data processors or controllers to re-identify participants in the audit.


MR795 - Cancer Risk & Mortality in a Sample of Service Personnel Deployed to Bosnia 1992 - 1996 — DARS-NIC-147847-P6MMR

Opt outs honoured: Yes - patient objections upheld, Identifiable, Anonymised - ICO Code Compliant, Yes (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-05-06 — 2022-02-07 2020.01 — 2021.03.

Access method: One-Off, Ongoing

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Civil Registration - Deaths
  5. Cancer Registration Data
  6. Demographics
  7. MRIS - Flagging Current Status Report

Objectives:

The data supplied by NHS Digital to King's Centre for Military Health Research (KCMHR) will be used only for the approved Medical Research Project MR795 - 'Cancer Risk & Mortality in a Sample of Service Personnel Deployed to Bosnia 1992 - 1996'. KCMHR is a research centre within King's College London (KCL).

Background:
There has been much speculation that military personnel who served on UN peacekeeping duties in Bosnia in 1992-1996 have higher than expected rates of cancer. This speculation has been based on individual case reports and some small clusters of leukaemia reported in Italian armed forces. It has been suggested that the allegedly higher rates of cancer are due to exposure to depleted uranium during deployment (Mayor, 2001). Other European nations have carried out studies to ascertain the incidence of cancer in their Bosnia veterans (Bogers et al, 2013; Gustavsson et al, 2004; Peragallo et al, 2010; Storm et al, 2006). In order to ascertain the rates of cancer and deaths in UK veterans who served in Bosnia, it is necessary to carry out systematic epidemiological studies and to date these have not been done. The study will determine whether the rates of cancer and death among personnel who served in Bosnia are higher than expected.

In 1997/8, using information provided by the Ministry of Defence (MoD), King’s College London (KCL) contacted members of UK Armed Forces who had deployed to Bosnia on UN peacekeeping duties as part of a larger study looking at the health consequences of the 1991 Gulf War. Data was collected using a questionnaire.

In 1997/8, KCMHR conducted a large epidemiological study on the health consequences of the 1990- 1991 Gulf War (Unwin et al, 1999). This involved identifying a cohort of 4250 individuals who had served in the Gulf, and two comparison groups: 4250 who had served on peace-keeping duties in Bosnia between 1992 and 1996, and 4250 individuals who were in the UK military at the time of the 1990-1991 Gulf War. In addition to demographic, health and service related data, environmental and combat related exposure data were collected from study responders.

In 2006, the Gulf War study team supplied personal data (name, date of birth, sex, NHS number, address) of participants in the Bosnia cohort of the 1997 KCL Gulf War study to the Office for National Statistics (ONS) so that participants could be traced and flagged. Self-reported data (and MoD provided data) relating to the Bosnia cohort have been retained as part of the KCL Gulf War study, with data relevant to addressing the aims of this additional sub-study held separately (the Bosnia study database).

Until 2014, the Bosnia study database held person identifying data along with cancer notifications and death registration details. On 27/03/2014, all directly identifying data had been removed from the Bosnia database, all hard copy notifications shredded and person identifying details deleted from notifications received electronically. Evidence of this was provided to NHS Digital. The Bosnia study data are pseudonymised. However, the personal data that relate the original KCL Gulf War study are still held at KCL (and will continue to be in anticipation of a possible follow up study). However, these data cannot be accessed by researchers from the Bosnia study.

In 2004 ethics committee approval was granted to ‘flag’ the Bosnia cohort with NHS Digital and to obtain cancer registration and death notifications (Joint SLAM/IOP NHS REC, study number 055/04). Section 60 of the Health & Social Care Act 2001 support was applied for and was granted in 2006 to supply patient identifiable data to NHS Digital, to flag the cohort and, for study responders, to supply death registration data, cancer registration data and exit information. For study non-responders summary tables for mortality and cancer incidence would be supplied at the end of the study. NHS Digital was provided with details of the Bosnia cohort (i.e. name, address, date of birth, and NHS number where available). A database of the study responders who were successfully flagged was compiled and is updated with details of cancer registrations and deaths as and when notifications are received from NHS Digital. In 2014 KCMHR again sought and received a favourable ethical review to continue to receive data from NHS Digital (REC reference 14/LO/1141, IRAS project ID 151260).

The immediate aim is to ascertain if the number of cancers and deaths reported so far would give sufficient power for meaningful analysis. Once researchers have the latest numbers of cancers and the number of deaths, a power calculation can be carried out to see if there is sufficient power (at least 80%) to show a clinically significant difference between the Bosnia group and a control group. Calculation showed that there were sufficient numbers to show a relative risk of 1.7 in the Bosnia cohort compared to the era group, in other words if there was an increased risk of cancer in the Bosnia cohort of 70% there would be sufficient power to detect it. That was based on the absolute risk of cancer reported by MacFarlane et al who found a low risk (0.5%) of cancer in the era group after 10 years. As time goes on, the absolute risk of cancer in both the era and Bosnia groups will increase (rates of cancers increase with age) so that after ~20 years it would be possible to detect a smaller increase in relative risk. There is not a specific number of cancers that would need to be reached in the Bosnia group since there may not actually be a difference in risk between the two groups. Of more importance is the length of time that needs to have elapsed since exposure for a possible difference in rate of cancer to have occurred. The latency period is the amount of time that elapses between initial exposure and the diagnosis of cancer. The latency period for blood related cancers e.g. non-Hodgkin lymphoma or myeloma have a shorter latency than solid tumours such as lung cancer. For example, the approximate latency period of lung cancer is approximately 14 years, of stomach cancer is 22 years and of kidney cancer is more than 40 years. It is now between 23 and 27 years since the Bosnia cohort deployed and this would be an appropriate time to assess whether the numbers of cancer notifications and /or deaths in this cohort compared to the era cohort show that there is an increased risk attributable to deployment to Bosnia.

If there have been sufficient occurrences KCMHR will not require further updates for the cohort.

For the longer term and main study aim KCMHR will ask the MoD to supply an anonymised dataset from the flagged “era group” containing information on age, sex, rank and cancer registrations and deaths. Researchers will then be able to compare cancer registrations and deaths in the Bosnia group with a non-deployed group serving at the same time, controlling for age, sex and rank. By comparing to data from the original study (Unwin et al, 1999), researchers will be able to assess whether risk of cancer in the Bosnia cohort is related to reported exposures to potentially harmful materials during deployment.

The overall aim of the study is to compare the incidence of cancer in a cohort of UK armed forces personnel who deployed to Bosnia between 1992 and 1996 and a cohort of personnel who were in service at the time but did not deploy to Bosnia. Researchers will also compare the rate of cancer in the Bosnia group with that in the general UK population using publicly available national statistics of cancer and mortality. Additionally, it will be assessed whether the risk of cancer in the Bosnia group is associated with exposures to harmful materials during their deployment.

The specific research questions are:
1. Are individuals who served in Bosnia between 1992 and 1996 at greater risk of developing cancer than other military personnel who did not serve there?
2. Are individuals who served in Bosnia between 1992 and 1996 at greater risk of developing cancer than the general UK population?
3. Is risk of cancer in the Bosnia cohort related to self-reported exposures to potentially hazardous materials during deployment?

If it is found that military personnel who served on UN peacekeeping duties in Bosnia in 1992-1996 do not have higher than expected rates of cancer, the Ministry of Defence and the Service charities will have evidence to allay fears among this population that they are at increased risk.

If researchers find an association between serving in Bosnia and increased risk of certain cancers, heightened awareness among health service providers of this particular risk could lead to earlier diagnosis and improved quality of care. In addition, if researchers find an association between particular exposures and cancer, the Ministry Of Defence could act to protect personnel from such exposures in the future.

Yielded Benefits:

Expected Benefits:

Once KCMHR have sufficient data for analysis there will be potential benefits to the population of UK Armed Forces personnel who deployed on UN Peacekeeping operations in Bosnia. If it is found that military personnel who served on UN peacekeeping duties in Bosnia in 1992-1996 do not have higher than expected rates of cancer, the Ministry of Defence and the Service charities will have evidence to allay fears among this population that they are at increased risk. There has been speculation of such an increase based on some small clusters of leukaemia reported in Italian Armed Forces personnel. Exposure to depleted uranium has been suggested as a possible risk factor.

Conversely, if researchers find an association between serving in Bosnia and increased risk of certain cancers, heightened awareness among health service providers of this particular risk could lead to earlier diagnosis and improved quality of care. In addition, if researchers find an association between particular exposures and cancer, the Ministry Of Defence could act to protect personnel from such exposures in the future.

Outputs:

The key milestone is the decision in if there is sufficient data to carry out significant analysis immediately or whether there is a need to wait a few years until further data is available.

This is a long term study recording the cancer status of veterans of The UK Armed Forces deployments to Bosnia between 1992 and 1996. In view of the anticipated long latency period between exposure and the appearance of cancers there may not be sufficient data yet to carry out the analysis.

Once a decision has been made that there is sufficient data the outputs will include:
- a report of the findings from the study with recommendations to the UK Ministry of Defence (MoD) and to Service charities dealing with veterans and their families (for example, The Royal British Legion, SSAFA). The report will include a lay summary which can be made available on the webpages of the MoD and Service charities.
- an academic paper giving an analysis and discussion of the results of the study that, subject to acceptance, will be published in an appropriate journal such as the BMJ.
- an infographic will be produced which will be hosted on the King’s website and distributed to all stakeholders for onward dissemination.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

In 2006 name, address, date of birth, and NHS number of the sample of UK Armed Forces personnel, who had deployed to Bosnia between 1992 and 1996 were sent from the KCMHR to the ONS so that they could be identified and flagged for long-term follow-up. Of the 4500 people sampled into the Bosnia group, 2620 responded to the questionnaire study. 2470 of those who responded were successfully flagged, and any death and cancer notifications or embarkations have been sent by ONS and subsequently by NHS Digital (after the service transferred in 2008) to KCMHR for this cohort.

The data received under this Agreement are pseudonymised - i.e. personal identifiers such as name, date of birth and NHS number are not sent to KCMHR.

The pseudonymised notifications from NHS Digital are downloaded and entered onto an analysis database by a Research Associate at King’s College, London. The database held by KCMHR is encrypted and password protected using 256-bit AES. It is accessed on a networked PC which is connected to a restricted access server at King’s College London, Strand campus and ‘backed up’ at Jisc Shared Data Centre, Slough (hosted by Virtus Data Centre). Access to the server is restricted to a single research associate. There are no personal identifiers held in the database.

The administrative database which contains the identifying details of the cohort with a common unique identification number which could technically re-identify individuals in the analysis database, has been archived to an encrypted external drive and is stored in a Ministry Of Defence approved safe. The combination to the safe is known to three people only: the Project Manager, the Database Administrator and a KCMHR research associate. Access to the safe is logged with the name of the person, date and reason for accessing. The research associate does not have access to the password to the encrypted external drive which is held in a secure password vault. No one who can access the administrative database can access the analysis database. These technical and organisational controls ensure the data under this Agreement remains pseudonymised.

The data will be analysed under supervision by KCMHR's Chief Investigator. Cancer and mortality rates will be calculated for the Bosnia group and compared with a group that was in service at the same time but did not deploy to Bosnia. A comparison of the rates of death and cancer will also be made with the UK general population. Exposures to environmental hazards will be examined to look for any associations with cancer.

Only the Bosnia group from the Gulf War study were flagged for KCL. However, the Gulf War details of all personnel who served in the Gulf area (n=53,462) were sent to ONS by the MoD along with an equal sized cohort of personnel who were in service but did not deploy to the Gulf - termed the ‘era’ group. Over 96% of both cohorts were identified and flagged on the NHS central register. KCL will apply to Defence Statistics at MoD for a pseudonymised dataset of their era cohort containing information on age, sex, rank and cancer registration or deaths and, subject to access to this data being granted, this will be used as the ‘control’ group.

Statistical analysis will be carried out using the statistical package, Stata. KCMHR will carry out a survival analysis, the outcome being defined as incident cancer registrations or death from cancer. For the Bosnia cohort, time at risk will be calculated from the point when the individual returned from deployment. For the control group, time at risk will be calculated from 1st April 1991. Failure events will be cancer registrations or deaths (whichever is recorded first). Individuals who emigrated from the UK will contribute up to the point of migration. Cox's proportional hazards model will be used to calculate hazard ratios with 95% confidence intervals for cancer registration. KCMHR will control for sex, age and rank. Standardised incidence ratios (SIR) and standard mortality ratios (SMR) will be calculated to compare cancers and deaths in the Bosnia group to the UK population.

Multivariable logistic regression will be used to examine associations between cancer and environmental exposures adjusting for potential con-founders restricted to the Bosnia cohort.

The key milestone is the decision in if there is sufficient data to carry out significant analysis immediately or whether there is a need to wait a few years until further data is available.

This is a long term study recording the cancer status of veterans of The UK Armed Forces deployments to Bosnia between 1992 and 1996. In view of the anticipated long latency period between exposure and the appearance of cancers there may not be sufficient data yet to carry out the analysis.
Once a decision has been made that there is sufficient data the outputs will include:
- a report of the findings from the study with recommendations to the UK Ministry of Defence (MoD) and to Service charities dealing with veterans and their families (for example, The Royal British Legion, SSAFA). The report will include a lay summary which can be made available on the webpages of the MoD and Service charities.
- an academic paper giving an analysis and discussion of the results of the study that, subject to acceptance, will be published in an appropriate journal such as the BMJ.
- an infographic will be produced which will be hosted on the King’s website and distributed to all stakeholders for onward dissemination.


MR1308 - Sentinel Stroke National Audit Programme — DARS-NIC-387635-C9Y0W

Opt outs honoured: Yes - patient objections upheld, N, Anonymised - ICO Code Compliant, Identifiable, Yes (Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2018-06-29 — 2021-03-31 2017.06 — 2021.03.

Access method: Ongoing, One-Off

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Hospital Episode Statistics Admitted Patient Care
  5. Demographics
  6. Civil Registration - Deaths
  7. MRIS - Scottish NHS / Registration

Objectives:

ONS: The Royal College of Physicians (RCP) is the data processor responsible for producing the CCG Outcomes Indicator Set (CCGOIS) measure of mortality at 30 days for stroke patients. These results are provided to NHS Digital to publish as part of the wider CCGOIS. The results are also provided at team level to provide necessary context on the performance of clinical teams treating stroke patients. As well as reporting on 30 day mortality, there is a need to show survival at other intervals such as at 6 months and 1 year. The outputs of the analysis by RCP will include mortality statistics at different time points and at different levels of granularity and dates of death will be used in statistical modelling. Any data reported on is carefully considered in terms of whether it could be potentially identifiable and advice is given on how the outputs should be interpreted. It is also important that Royal College of Physicians are able to provide the information back to the clinical teams who have treated the patients.

HES: The HES dataset is used to determine the case ascertainment (case ascertainment is a measure of the number of cases reported in the audit, compared to the number of cases identified in HES) of participants of the Sentinel Stroke National Audit Programme (SSNAP), that is, the proportion of coded stroke patients which are recorded in the audit; and identify any readmissions and further strokes, in order to compare quality of care with outcomes for patients. As the outputs of analysis of SSNAP are reported and publically available, the proportion of patients entered into the audit for each hospital team, compared with the numbers in HES, is vital in determining how results are used (for instance, if there is low case ascertainment, the mortality outcomes would not be reported so that there is no potential misrepresentation).

Yielded Benefits:

Case ascertainment information from HES has been used to target trusts who were not achieving good levels of data entry to the audit in previous years, which has resulted in those trusts entering more records onto SSNAP, therefore improving the overall case ascertainment of the audit and reducing potential biases. This results in higher quality data being used for decision making at trust level and nationally. Mortality information has been fed back to trusts in case-mix adjusted models, and outlier trusts have been identified. These trusts were contacted and encouraged to undertake case note reviews of their fatalities to identify areas for improvement. Outlying trusts were also offered a full peer review visit by the Stroke Programme, and a number of outlying trusts have taken up this offer to help identify where improvements in their service need to be made. The ability to adjust for variables such as stroke severity using the SSNAP Civil Registration/Mortality methodology is important, as stroke severity is a very strong predictor of mortality. Statistical analyses of the HES and Civil Registration/Mortality data have looked at variation in stroke care and outcomes based on the presence of other diagnoses, socioeconomic status, and organisational characteristics of the hospitals treating the patients. Some of these analyses have already been published, and others are currently being written up for submission to peer review journals. In 2018 the paper ‘Socioeconomic disparities in first stroke incidence, quality of care, and survival’ was published in The Lancet. It is available here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5887080/. Such analyses have the potential to highlight key areas for improvement and to drive change.

Expected Benefits:

Case ascertainment information will be used to target trusts who are not achieving good levels of audit case ascertainment, this leads to more complete data and more valid results in future audit. Complete audit information is essential for service improvement, and improvements to stroke patient care. HES data is utilised to compare the number of records submitted to the audit, with the number recorded in HES. SSNAP are currently finalising the methodology for determining the number of new stroke admissions per team, which will then be used to better triangulate which teams are submitting fewer patients to the audit than they are recording in HES. The previous years’ HES denominators enabled the audit to target teams with poorer case ascertainment and to chase those teams before submission deadlines in order to maintain the national case ascertainment above 90%. In the latest round of reporting (for Aug-Nov 2016), it was estimated that 90% of routinely admitting teams in England and Wales submitted over 90% of their stroke cases to the audit. The percentage case ascertainment at teams is used to penalise teams with low case ascertainment, and functions as a key driver for high participation levels.
This ongoing process is a key driver to high case ascertainment in the audit – comparing teams to HES has yielded a consistent 90%+ case ascertainment nationally, which is key to ensuring representativeness and usefulness of the audit data. The benefit of this the receipt of HES data is therefore to enable a useful audit dataset, and the use of previous years’ HES has ensured the audit’s reputation as a high quality data source, and enabled audit data to be used to highlight areas of unwarranted variation across the country, to identify key areas for improvement, and for use in a number of parliamentary questions.

Mortality within 30 days of hospital admission is part of Domain 1 of the NHS CCG Outcome indicator set “reducing premature mortality”. CCGs will access the published information and use it to improve services through identification of good and bad practice. This will be of benefit both in terms of better value for money and better patient outcomes. Mortality at CCG level using a casemix-adjusted model has been reported for 3 years now, for 2013/14, 2014/15 and for 2015/16. The CCG OIS mortality measure was last published by SSNAP and by NHS Digital in early 2017. CCG outliers were informed in late 2016 and conversations with the CCG chairs, and medical directors ensued. One CCG was flagged as an outlier, despite none of its constituent hospitals being flagged. This raised a question to be investigated by the CCG as to whether they needed to assess their commissioning of services. The analyses will also help CCGs and STPs in the debate around where services should be reconfigured by enabling the use of appropriately adjusted mortality information.
Outlier CCGs will again be contacted using an outlier processes to discuss where improvements in stroke care are needed in order to benefit both in terms of better value for money and better patient outcomes. The data will be published on the SSNAP website, as well as part of the CCG OIS, and is normally considered for other outputs such as PHE’s CVD profiles, Atlas of Variation etc. Reporting and publishing this information in the future is key to ensuring CCGs with high mortality rates are informed of this, and have the opportunity to improve.

Similarly, trusts will use team level mortality within 30 days of hospital admission to identify trends and good practice, again leading to better patient outcomes. Mortality at team level using a casemix-adjusted model has been reported for 3 years now, for 2013/14, 2014/15 and for 2015/16. In the past year, the mortality outlier for 2015-16 requested a stroke peer review visit to help identify key ways to improve their service. A quality improvement programme is now being implemented in this service, following from a detailed peer review visit.
Outlier teams will again be contacted using an outlier processes to discuss where improvements in stroke care are needed with the Chief Executive, medical director and clinical lead for stroke. This information will be put into the public domain so patients and the public can see which hospitals have poor outcomes, for example through the MyNHS website. A stroke peer review visit will be offered to outlying teams to assist with identifying key areas for improvement and ways to achieve that improvement.

Feeding back mortality information to teams, allows teams to investigate their patient outcomes and put in place ways to improve, for example by investigating patient deaths following the use of thrombolysis.

Statistical analyses investigating longer-term mortality will have the following benefits:
• assessing the real-world benefit of new interventions such as intra-arterial intervention (mechanical thrombectomy) and intermittent pneumatic compression stockings
• tracking changes in mortality trends over time
• monitoring the effect of reconfiguring services
• monitoring the effect of introducing 7-day working
• monitoring the impact of service decommissioning.

Investigating stroke rates and comorbidities using the HES data will be beneficial by:
• reducing the burden of data collection,
• helping identify key areas for quality improvement
• reducing unwarranted variation
• enabling a broader understanding of comorbidity and its impact of the receipt of key processes of care and patient outcomes.

Outputs:

ONS and HES: Indicators will be produced showing the performance of organisations and at national level for the purpose of monitoring and quality improvement, in particular:
• Mortality within 30 days of hospital admission for stroke CCG Outcomes Indictor Set (CCGOIS) at least annually (first publication on 17 December 2014, next publication anticipated to be published by the end of 2017, subject to timely receipt of ONS data from NHS Digital)
• Mortality within 30 days of hospital admission for stroke Team-level mortality results (published in line with CCGOIS and used for contextualising the results). (Team usually equates to a hospital).
• Audit case ascertainment information
• For statistical purposes such as monitoring trends registered individuals at Trusts can access date of death for patients they submit to the audit derived from ONS mortality data.
• As well as reporting on 30 day mortality, there is a need to show survival at other intervals such as at 6 months and 1 year. The outputs of the analysis by RCP will include mortality statistics at different time points and at different levels of granularity and dates and causes of death will be used in statistical modelling. Any data reported on is carefully considered in terms of whether it could be potentially identifiable and advice is given on how the outputs should be interpreted.
• Planned analyses following agreement with our steering group investigating stroke rates and associations with comorbidities recorded in HES to be published in peer-reviewed journals

Processing:

RCP will send cohort information to NHS Digital for linkage, they send NHS Number, Full postcode, Name, and a unique SSNAP ID. As part of the section 251 support, there is a method by which the information is sent to NHS Digital for linkage without the RCP viewing any patient identifiable information.

NHS Digital return;
• Non sensitive pseudonymised HES data with SSNAP ID for patients in cohort
• Non sensitive pseudonymised HES data for patients with a diagnosis of stroke
• Identifiable ONS date and cause of death

RCP combine HES and ONS data with SSNAP data and combine into separate databases; one with SSNAP and ONS data and the other with SSNAP and HES data.

Identifiers are held separately to other data and the pseudonym SSNAP ID is used to identify individual patients. With the exception of date of death, analysts access no identifiers.

Pseudonymised HES Data is then analysed to calculate case ascertainment information for the audit. HES data is also used to validate some of the information collected in the audit. No HES data is stored or processed by Netsolving, all processing is undertaken at the RCP.

Identifiable ONS data is analysed to produce 30 day mortality at CCG level and stroke team level (team usually equates to a hospital). Cause of death is used to disaggregate stroke specific deaths and deaths from other causes.
For statistical purposes such as monitoring trends identifiable ONS death data is also passed back (via the secure webtool hosted by Netsolving) to registered individuals at participating trusts whereby they can access date of death for patients they submit to the audit.
All arrangements for 3rd party access will be controlled through sublicensing agreements and will be for the benefit of health and care; all arrangements will be approved by the HSCIC before data being sent.

All individuals with access to the data are substantive employees of the Royal College of Physicians of London.


MR758 - Epidemiological studies of the Porton Down veterans: an update of mortality and cancer incidence — DARS-NIC-182736-Q2K7Y

Opt outs honoured: Yes - patient objections upheld, Identifiable, Yes (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-04-23 — 2021-04-22 2020.03 — 2020.09.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON, LANCASTER UNIVERSITY

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report
  3. MRIS - Members and Postings Report
  4. MRIS - Personal Demographics Service

Objectives:

Study background:

The study was originally set-up in 2003 by the University of Oxford to explore the long-term health of former servicemen who were exposed to chemical warfare agents as part of the ‘human volunteer programme’ at the UK government research establishment, Porton Down.

Using historical records, the researchers assembled a cohort of 18441 veterans who attended Porton Down, and a comparison cohort of 18103 who did not. To examine whether Porton Down veterans had unusual patterns of cancer incidence or mortality compared to non-Porton Down veterans, their records were linked to routine cancer registration and mortality data held by the Office for National Statistics up to 2004, namely, cause and date of death, type and date of cancer registration. The study established that, although there was a small (6%) excess of all-cause mortality in Porton Down veterans, this could not be attributed to any specific chemical exposure and might have been related to unmeasured factors such as smoking. There was no excess of cancers.

The new study aims to replicate the original analysis but with at least ten years of updated cancer registration and mortality data. This new data will allow the study team to repeat the analyses carried out previously, but with increased statistical power so that the impact of rare exposures and outcomes can be examined more fully, at a level of detail not possible in the original study (see Expected Measurable Benefits, ‘Ability to address new questions relevant to public health using unique cohort data’ for further detail).

Study aim:

To examine whether Porton Down veterans exposed to chemical warfare agent have unusual patterns of cancer incidence or mortality compared to non-Porton Down veterans

Study objectives:

1. Describe cause-specific mortality from 1941 to at least 2014 for the Porton Down Veterans cohort in relation to the general population and to the comparison cohort for (a) the whole cohort, (b) sub-cohorts with ‘vesicant’, ‘nerve agent’, and ‘other’ exposure, and (c) sub-cohorts exposed to specific chemicals of prior interest, e.g. sarin, pralidoxime; and examine dose-response relationships where data is available.

2. Describe cancer incidence from 1971 to at least 2014 for the Porton Down Veterans cohort in relation to the general population and to the comparison cohort for (a) the whole cohort, (b) sub-cohorts with ‘vesicant’, ‘nerve agent’, and ‘other’ exposure, and (c) sub-cohorts exposed to specific chemicals of prior interest, e.g. sarin, pralidoxime; and examine dose-response relationships where data is available.

What organisations are involved?

The new study will be undertaken by researchers at King’s College London (study lead) and the University of Lancaster. Researchers who worked on the original study at the University of Oxford will act as advisors due to their historical knowledge; for example, on how data was originally collected, study file structure and documentation, and suggestions for stakeholder engagement, but will not determine the manner in which data are to be processed.

King’s College London and Lancaster Universities are joint data controllers as both are involved in determining the purposes and means of processing the data; however the updated data will only be processed, stored, and analysed by King’s College London.

The study update has been awarded funding by the MRC (MR/R002932/1) to update cancer registration and death data to the latest available date; this data will be obtained from NHS Digital, NHS Scotland, and Northern Ireland and Statistics (for English/Welsh, Scottish, and Northern Irish data, respectively).

The study will not involve working with organisations outside the UK.

Reasons for data requested:

The updated data requested from NHS Digital is essential to enable the original analyses (which covered the period 1941-2004) can be updated.

The data required is limited to members of the Porton Down veterans study, this also includes the study cohort. Record-level data is essential in order to link deaths and cancer registrations to the correct military veteran and chemical exposure at Porton Down. Cause of death and type of cancer are required in order to investigative the wide variety of possible harms which might be attributed to chemical warfare agents.

For the original study, Oxford had a 2003 agreement with ONS for the supply of data to Oxford under ONS reference 107/053/02 and MR reference 758. The new request is for the same data fields as were supplied under the 2003 agreement.

The data will only be used to investigate the relationship between exposure to chemical warfare agents at Porton Down and patterns of cancer incidence, and mortality.

Expected Benefits:

The original study:

The original study was born out of concerns raised by veterans that their long-term health may have been affected by their exposure to chemical agents (e.g. vesicants, riot control agents, nerve agents, and their antidotes) as part of the ‘human volunteer programme’ at Porton Down. The study found that Porton Down veterans had no overall excess of cancer compared to non-Porton Down veterans, and a small excess (6%) of overall mortality, but this could not be attributed to any specific exposure.

These findings were published in the BMJ (Carpenter et al., 2009; Venables et al,. 2009), an international peer reviewed medical journal, and helped to clarify the health status of Porton Down veterans, and other former service personnel exposed to chemical warfare agents, which was believed to be reassuring to many veterans and their families.

What are the benefits of the new study?

Understanding long-term health risk of low-dose exposure to chemical warfare agents or their antidotes. Chemical warfare agents are easily manufactured and continue to be deployed by rogue states, e.g. Syria and Iraq (United Nations 2013), and by terrorists, e.g. on the Tokyo subway (Coleman 2005, Okumura et al. 2005). Most recently, a nerve agent developed in the former Soviet Union was used in Salisbury (BBC News 19 July 2018, OPCW 13 March 2018). Five people were exposed, and one died.

There is therefore a plausible and on-going risk of exposure to these agents in civilian, military and emergency service populations in the UK and internationally, yet the long-term health effects of low-dose exposure to chemical warfare agents are largely unknown. Concerns that these agents, or their antidotes, might cause delayed effects on health are likely to remain long into the future and it is in the public interest to accumulate research evidence to confirm, or refute, these concerns.

Ability to address new questions relevant to public health using unique cohort data:

The Porton Down cohort study is the largest and best-documented cohort with exposure to chemical warfare agents in the world. It is the only cohort with accurate, quantitative information on exposure, thus allowing the study of exposure-response relationships. As well as its large size, the exposure data is of exceptionally high quality compared to other sources; for example, information gathered after warfare or terrorist scenarios has many attendant biases, i.e. the precise nature of the exposures may be unclear; mixtures of chemicals may have been used; and the dose and duration of exposure are unknown. In the original analysis, over 7,000 Porton Down veterans had died in the period 1941-2004. The study update will increase this to about 12,000 deaths, and a proportional increase in cancer registrations. The increased number of outcome events increases statistical power which will enable to gain a greater understanding of the relationship between specific chemical agents and health outcomes (e.g. rarer forms of cancer) at a level of detail not possible in the original study.

New research questions of relevance to public health were posed after the original papers were published. For example, Barth et al. (2009) reported that US Gulf War veterans with potential exposure to nerve agents had an increased risk of central nervous system cancers and other neurological mortality. Updating this cohort will give an opportunity to confirm or refute Barth’s et al. study, and to add to the evidence base on nerve agents.

Likewise, it will be possible to look in more detail at riot control agents (CS gas) for which the original study noted a two-fold excess of oesophageal cancer (currently CS is not a known carcinogen), and also the relationship between pralidoxime, a nerve agent antidote, and increased risk of all-cause mortality (there has been repeated suggestion that nerve agent antidotes might be implicated in Gulf War syndrome (Abou Donia et al. 1996, Zakirova et al. 2015). These research questions cannot be easily examined in the absence of well-documented cohort data.

How will the findings be used?

If an association is found between exposure to chemical agents (e.g. vesicants, riot control agents, nerve agents, or their antidotes) and an increased risk of certain cancers, or cause of death, this could lead to raised awareness among health care providers, leading to improved diagnosis and quality of care. Likewise, if particular chemical warfare or riot control agents are associated with poor long-term health, the Ministry of Defence and other public health organisations could act to protect individuals from exposure in the future. Conversely, if there appears to be no long-term health risk, then this will reassure veterans and their families, and any other exposed groups, leading to a reduction in anxiety about their exposure.

Dissemination of findings:

The findings of the study will be submitted to high-profile medical journals and should be published between 2019-21.

The engagement with the MoD and the NHS Armed Forces Team will be sought to put in place any additional support needed for the veterans and their families prior to publication of the results. The findings will be helpful to organisations concerned with the health and welfare of the Porton Down veterans, e.g. the Legacy section of the Ministry of Defence, the Help Line at Porton Down, and the Medical Assessment Programme for the Porton Down veterans.

The findings will also be helpful for other groups exposed to chemical warfare or riot control agents including other military service personnel, emergency services, and the general population (e.g. police or demonstrators exposed to CS gas, and Salisbury residents following the Novichok incident).

The results will be useful to organisations responsible for public health and those concerned with the military response or emergency service response in the event of a release of a chemical warfare agent by a hostile country, individual, or agency, e.g. the Ministry of Defence, ambulance, police forces and fire brigades, and organisations concerned with civilian emergency preparedness, e.g. Public Health England.
The updated findings will also offer a unique contribution to the academic literature, which will be of benefit to other researchers investigating the relationship chemical warfare agents and long-term health.

Summary:

Very little is known about whether exposure to low-dose chemical agents (e.g. vesicants, riot control agents, nerve agents, and their antidotes) impact long-term health. The Porton Down cohort is uniquely placed to examine this question as it is the only dataset in the world with accurate, quantitative information on chemical agent exposure.

The findings of study are not only relevant to Porton Down veterans but all those who have been, or are at risk of, low-dose exposure to chemical warfare and riot control agents, including other military service personnel, emergency services, and the general population (e.g. those involved in warfare, public demonstrations, or caught in terrorist incidents). Greater understanding of the long-term risks associated with exposure to chemical agents could lead to improved diagnosis and quality of care, and help shape health policy to protect individuals from future exposure.

References:

Abou-Donia MB, Wilmarth KR, Jensen KF, Oehme FW, Kurt TL. Neurotoxicity resulting from coexposure to pralidoxime bromide, deet, and permethrin: implications of Gulf War chemical exposures. J Toxicol Environ Health. 1996;48:35-56.

Barth SK, Kang HK, Bullman TA, Wallin MT. Neurological mortality among U.S. veterans of the Persian Gulf War: 13-year follow-up. Am J Ind Med. 2009;52:663-70. doi: 10.1002/ajim.20718.

BBC News. Amesbury Novichok poisoning: What we know so far. 19 July 2018. (https://www.bbc.co.uk/news/uk-44721558).

Carpenter, L. M., Linsell, L., Brooks, C., Keegan, T. J., Langdon, T., Doyle, P., ... & Venables, K. M. Cancer morbidity in British military veterans included in chemical warfare agent experiments at Porton Down: cohort study. Bmj, 338, b655. 2009
(https://www.bmj.com/content/338/bmj.b655.full.pdf+html)

Coleman K. A history of chemical warfare. Basingstoke: Palgrave, 2005.

Venables, K. M., Brooks, C., Linsell, L., Keegan, T. J., Langdon, T., Fletcher, T., ... & Carpenter, L. M. Mortality in British military participants in human experimental research into chemical warfare agents at Porton Down: cohort study. Bmj, 338, b613. 2009.
(https://www.bmj.com/content/338/bmj.b613.short)

Okumura T, Hisaoka T, Yamada A, Naito T, Isonuma H, Okumura S, Miura K, Sakurada M, Maekawa H, Ishimatsu S, Takasu N, Suzuki K. The Tokyo subway sarin attack--lessons learned. Toxicol Appl Pharmacol. 2005;207:471-76.

Office for the Prohibition of Chemical Weapons. EC-87/NAT.5 13 March 2018. Statement by H.E. Ambassador Peter Wilson Permanent Representative of the United Kingdom of Great Britain and Northern Ireland to the OPCW at the Eighty-Seventh Session of the Executive Council. (https://www.opcw.org/fileadmin/OPCW/EC/87/en/ec87nat05_e_.pdf).

Outputs:

No individual will be identified in reports or publications. All outputs will only contain data that is aggregated, with small numbers suppressed, in line with the HES Analysis Guide.

Planned outputs:

Academic research articles:

Subject to acceptance, research articles will be published in open-access, high impact, peer-reviewed scientific journals, such as the British Medical Journal (BMJ).

1) Mortality in British military participants in human experimental research into chemical warfare agents at Porton Down: A 15-year update (planned submission 2019)
2) Cancer morbidity in British military veterans included in chemical warfare agent experiments at Porton Down:
A 15-year update (planned submission 2019)
3) Cohort Profile: The Porton Down veterans cohort (planned submission 2019)
4) A review of epidemiological studies of chemical warfare agent exposed populations (planned submission 2019)

Links to published scientific papers will appear on the websites of the collaborating universities.

The update study’s findings will also be presented at relevant academic conferences (e.g. the Canadian Institute for Military and Veteran Health Research, the International Symposium on Epidemiology in Occupational Health, Society for Longitudinal and Life course Studies conference, 2019-2021).

Stakeholder engagement:

Reports of findings in lay language will be disseminated to veterans by means of a specially-convened meeting and via the newsletters of veterans’ organisations and relevant websites, e.g. of veterans’ organisations and of the collaborating universities. Policy-relevant findings will be presented to official bodies e.g. the Ministry of Defence veterans’ section and Public Health England.

Project report for funder:

Reports will be provided to the MRC in accordance with MRC terms and conditions.
Any future data processing not covered in this application will be preceded by an amendment application to NHS Digital.


Academic publications from the original study:

Venables KM, Carpenter LM. Epidemiological studies to explore the health of the Porton Down veterans. Report on pilot phase: April 2003. Report to MRC.

Allender S, Maconochie N, Keegan T, Brooks C, Fletcher T, Nieuwenhuijsen MJ, Doyle P, Carpenter LM, Venables KM. Symptoms, ill-health and quality of life in a support group of Porton Down veterans. Occup Med 2006;56:329-137.

Keegan TJ, Nieuwenhuijsen MJ, Fletcher T, Brooks C, Doyle P, Maconochie NES, Carpenter LM, Venables KM. Reconstructing exposures from the UK chemical warfare human research programme. Ann Occup Hyg 2007;51:441-450.

Keegan TJ, Walker SAS, Brooks C, Langdon T, Linsell L, Maconochie NES, Doyle P, Fletcher T, Nieuwenhuijsen MJ, Carpenter LM, Venables KM. Exposures recorded to participants in the UK chemical warfare agent human research programme, 1941-89. Ann Occup Hyg 2009;53:83-97.

Venables KM, Brooks C, Linsell L, Keegan TJ, Langdon T, Fletcher T, Nieuwenhuijsen MJ, Maconochie NES, Doyle P, Beral V, Carpenter LM. Mortality in British military participants in human experimental research into chemical warfare agents at Porton Down: cohort study. BMJ 2009: Mar 24;338:b613. doi: 10.1136/bmj.b613.

Carpenter LM, Linsell L, Brooks C, Keegan TJ, Langdon T, Doyle P, Maconochie NES, Fletcher T, Nieuwenhuijsen
MJ, Beral V, Venables KM. Cancer morbidity in British military veterans included in chemical warfare agent experiments at Porton Down: cohort study. BMJ 2009: Mar 24;338:b655. doi: 10.1136/bmj.b655.

Keegan TJ, Carpenter LM, Brooks C, Langdon T, Venables KM. Sarin exposures in a cohort of British military participants in human experimental research at Porton Down 1945-1987. Ann Work Expo Health. 2017;62:17-27. doi: 10.1093/annweh/wxx084.

Processing:

Original sources of data:

The Porton Down cohort is already assembled and no new participants will be sought. The original data was obtained from three sources:

1) Porton down records: Chemical exposure data for the Porton Down veterans was collected in the original study from records held at Porton Down. This data was used to generate the ‘exposure’ database, which includes data on name, military service number, and chemical exposure information (e.g. date of test, type of exposure).

2) Military personnel files: The list of veterans assembled from the Porton Down records (n=18441) was sent to military personnel archives for verification of military personnel data, e.g. military service number, branch of service, military rank. A comparison group (n=18103) was generated within military personnel archives by choosing veterans with adjacent military service numbers who had not attended Porton Down. This data was used to create the ‘personnel’ database, which includes data on sex, date of birth, military rank, date of enlistment, date of discharge, and date and cause of death (if recorded).

3) National registry data (outcome data): Study members were originally flagged by ONS and mortality and cancer registration data provided to the researchers up to 31/12/2004. This was the ‘outcome’ database, and includes sensitive personal data including cause of death, type of cancer, and date of death and cancer.

Consent:

In the original study there have been extensive consultations with the Porton Down Veterans Support Group and with other stakeholders. It was concluded that it was not practicable to seek individual consent because it was a historical study; addresses in military personnel records were outdated, and due to the advanced age of the cohort by the end of 2004 approximately 40% had already died; using national age-specific mortality rates, it is estimated that by mid-2019 approximately 60% will have died. . This was recognised by the Patient Information Advisory Group who gave ethics approval on the grounds that the public interest in completing the research outweighed the usual requirement for individual consent. The same arguments hold for not seeking consent now, especially as, with the passage of time, more cohort members have died and addresses in the military personnel records are further out-of-date.

Conditional support from the Confidentiality Advisory Group (CAG) and the Health Research Authority (HRA) for Section 251 approval under the National Health Service Act 2006, to process identifiable data without consent, has been granted.

Data flow:

1) Transfer of original study data from Oxford to King's College Military Health Research (complete):

Under a legal Data Transfer Agreement, all physical and electronic data was transferred from Oxford to KCMHR, King’s College London using a secure courier service. The chemical ‘exposure’, military ‘personnel’, and ‘outcome’ (cancer and death) data is classified as identifiable. Paper files are stored securely at KCMHR offices and in an off-site archive, and electronic databases are stored on an encrypted external hard drive.

2) KCMHR separate personal identifiers and de-identify databases (in progress):

KCMHR will remove personal identifiers from the electronic data and store these securely in the KCMHR main office safe. Electronic ‘exposure’, ‘personnel’, and ‘outcome’ databases will contain a unique study ID number.

3) Transfer of data from KCMHR to NHS Digital/NHS Scotland/NISRA:

After the necessary permissions are obtained, KCMHR send NHS Digital/NHS Scotland/NISRA the minimum personal information necessary to re-flag the cohort for deaths and cancers to the latest available date, namely, unique study ID, name, initials, sex, NHS number, date of birth, postcode (district level). The same identifiers will be sent to NHS Digital, NHS Scotland, and Northern Ireland. These identifiers are identical to those used in the original study, and necessary to re-flag and validate matches.

4) NHS Digital/NHS Scotland/NISRA transfer updated outcome data to KCMHR:

The updated mortality and cancer data is sent securely from NHS Digital/NHS Scotland/NISRA to KCMHR, which will include cause and date of death, and type and date of cancer registration. We will also request back the unique study ID number and date of birth.

5) KCMHR link the updated and original outcome data:

The updated and original outcome data will be linked using a unique study ID number, and linkage will be validated using date of birth. Date of birth will be used to derive a person-years variable, and dates of death and cancer registration will be used to create time-to-event variables, as per the original analysis.

6) KCMHR separate personal identifiers and de-identify the outcome database:

Once time-to-event and person-years have been derived, date of birth, and dates of death and cancer registration will be removed from the outcome database and stored separately on encrypted external hard-drives in the KCMHR study safe.

7) Data analysis at KCMHR (linkage of the ‘exposure’, ‘personnel’ and ‘outcome’ data):

KCMHR will create an analysis file by linking the exposure, personnel, and outcome databases using the unique study ID. Due to the combination of variables, data will treated as identifiable, and stored on an encrypted external hard drive in a locked filing cabinet in the study office. The data will be analysed on a networked University managed PC; data will not be saved to a computer or any other electronic device.

The data from NHS Digital/NHS Scotland/NISRA will not be shared with third-parties, and will not be used for benchmarking against peer groups. There will be no requirement nor attempt to re-identify individuals from the data.

Justification for processing identifiable data (CAG approval obtained):

Cause and date of death, and type and date of cancer registration is required to create time-to-event data so that the original analyses (which covered 1941 to 2004) can be updated. Access to date of birth data is required in order to i) calculate person-years as per the original analysis, and ii) validate linkage between the original and updated outcome data. Once time-to-event and person-years have been derived, date of birth and dates of death and cancer registration will be removed from the analysis file and stored separately.

Physical security arrangements at KCMHR:

The KCMHR offices have a higher level of physical security than standard as they store sensitive military data. The offices are situated within a building which is manned by a security team on a 24-hour basis. To enter the KCMHR building an individual must have a swipe card ID and must present this on the ground floor to security guards and at a card reader to enter the main building.

The study office at King’s Centre for Military Health Research at King’s College London is alarmed, and the door is secured with both a key lock and a digital coded lock, and there is CCTV in the corridor. Paper-based files will be stored in a locked cabinet in the study office, and in King’s secure archive at Guy's campus. De-identified electronic data will be stored on an encrypted external hard-drive in a locked drawer in the study office. Personal identifiers will be stored separately on an encrypted external hard-drive in a Ministry of Defence approved safe in the KCMHR main office. Only the KCMHR Data Manager and study Research Associate study will have access to the data.

KCL network drives are backed up at JISC datacentre in Slough; however the study data will be stored on encrypted external drives at the KCMHR offices. No data will be saved to university servers.

MRC guidelines on the holding and archiving of data in relation to cohort studies will be abided by. As recommended by the MRC, if no update of the study is forthcoming, the data will be electronically and physically destroyed.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).


MR1182 - Genetic Longitudinal Study of Ageing — DARS-NIC-147955-M8D2Q

Opt outs honoured: No - consent provided by participants of research study, Identifiable, Yes, No, Anonymised - ICO Code Compliant (, Section 251 NHS Act 2006, , Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Informed Patient consent to permit the receipt, processing and release of data by NHS Digital, , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c); Health and Social Care Act 2012 – s261(7)

Purposes: No (NHS Trust, Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2010-07-28 — 2020-07-20 2016.06 — 2020.03.

Access method: Ongoing, One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Flagging Current Status Report
  5. MRIS - Members and Postings Report
  6. MRIS - Personal Demographics Service
  7. Cancer Registration Data
  8. Civil Registration - Deaths
  9. Demographics
  10. Emergency Care Data Set (ECDS)
  11. Hospital Episode Statistics Accident and Emergency
  12. Hospital Episode Statistics Admitted Patient Care
  13. Hospital Episode Statistics Critical Care
  14. Hospital Episode Statistics Outpatients
  15. Mental Health Minimum Data Set

Objectives:

Genetic Longitudinal Study of Ageing

1. To assess the extent to which age-related deterioration is correlated between different organ systems (cardiovascular, muscle, bone, respiratory function, and vision).
2. To assess how much of variation in longitudinal rates of physiological deterioration is due to genetic and environmental variation.
3. To investigate genetic associations with the five organ systems using candidate gene and genome wide association studies
4. To determine the relative influences on biological ageing (as measured by loss of function/tissue) of environmental factors such as marital status, socio-economic status (income, education, occupation), levels of physical exercise, smoking and alcohol intake, number of children.
5. To investigate the value of putative biomarkers of ageing: serum vitamin D, DHEAS, C-reactive protein, creatinine, retinal vascular calibre, and white cell telomere length


Outcomes after hip fracture by duration, frequency and type of rehabilitation — DARS-NIC-274251-H0G6M

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Yes (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), , Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-04-01 — 2022-03-31 2019.12 — 2019.12.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. HES:Civil Registration (Deaths) bridge

Objectives:

King’s College London (KCL) requires HES data from NHS Digital for the purpose of research which will use the National Hip Fracture Database (NHFD) linked to Hospital Episode Statistics (HES) and the Patient Episode Database for Wales (PEDW) to determine whether poor outcomes after hip fracture surgery were less frequent among patients exposed to more frequent, longer duration, and more comprehensive rehabilitation controlling for characteristics of patients, their injuries and healthcare.

More specifically, the aims are to:

1. estimate the odds of return to preadmission residence, readmission and survival at 30-days post-discharge, and recovery of mobility at 120-days, overall and by duration, frequency, and type of rehabilitation after adjustment for potential confounders;
2. estimate the probability of discharge by time after surgery overall and by duration, frequency, and type of rehabilitation after adjustment for potential confounders and the competing risk of death;
3. determine whether estimates vary across subgroups defined by patient and care factors;

The purpose and aims are justified under Article 6 (1) (e) and Article 9 (2) (i). This project will address an evidence gap with a view to complete analysis performed in the public interest of informing quality improvement in rehabilitative care for patients with hip fracture (Article 6 (1) (e)). This project will also help to reduce unwarranted variation in current rehabilitative care to ensure high standards of quality and safety of rehabilitative health care (Article 9 (2) (i)).

KCL has determined that there are no moral or ethical issues raised by the proposed dissemination and there is no risk of potential harm to the public by the dissemination.

UK hospitals admit 75,000 men and women with hip fracture annually. Patients with hip fracture and their carers describe rehabilitation as key to their recovery. Yet, the optimal rehabilitation remains unclear. This is highlighted by: the detail in the NICE guidance being limited to daily mobilisation and regular physiotherapy review; the absence of recent Cochrane systematic reviews; the conclusion that there is insufficient evidence to recommend practice change from earlier Cochrane reviews, and uncertainty among physiotherapists with respect to the appropriate management of patient subgroups.

The National Hip Fracture Database (NHFD) is a clinically led, web-based quality improvement initiative commissioned by the Healthcare Quality Improvement Partnership (HQIP) and managed by the Royal College of Physicians (RCP). The NHFD audit demonstrated marked national variation in the duration, frequency, and type of acute rehabilitation delivered by physiotherapists during a fixed period in 2017. The audit recommended longer, more frequent, and more comprehensive rehabilitation. The audit was not resourced to evaluate the association between duration, frequency, and type of rehabilitation with outcomes, or possible variation in associations for different patient subgroups.

The requested data will provide essential outcome data (readmission and survival at 30-days) as well as rich information on ethnic category, deprivation, comorbidities and complications for regression adjustment and subgroups in the proposed analyses. The aims will inform quality improvement initiatives to reduce unwarranted variation in rehabilitation after hip fracture.

The data subjects will consist of all patients 60 years of age or older who underwent hip fracture surgery in England or Wales between May 1st and June 30th 2017. KCL requires HES Admitted Patient Care data for the years 2015/16 to 2017/18 linked to this cohort. KCL also requires the survival status at 30 days post discharge from care.


KCL require pseudonymised data to address the aims outlined above which allows ‘the processing of personal data in such a way that the data can no longer be attributed to a specific data subject without the use of additional information’ (GDPR 2018). The additional information required to identify an individual will not be available at King’s College London.

The NHFD collected data related to rehabilitation duration, frequency, and type for patients admitted with hip fracture between May 1st and June 30th, 2017. KCL require data for 2017/18 to capture the care spell related to hip fracture and any readmission within 30-days of discharge from the care spell. KCL also require data for care spells in the years prior to the hip fracture care spell (2015/16 & 2016/17) to identify comorbidities not coded in the hip fracture care spell for regression adjustment.

KCL require data for England and Wales. KCL require this geographical spread to capture patients who underwent surgery at a NHFD site participating in data collection related to rehabilitation duration, frequency, and type which is required to address our study aims.

KCL has determined that there are no alternative, less intrusive ways of achieving the purpose.

The data is minimised to the cohort of patients whose care spell related to hip fracture between May 1st and June 30th, 2017. Care spells in the year prior to the care spell related to hip fracture, and Readmission within 30 days of discharge from the care spell related to the hip fracture. Survival status at 30-days derived from the civil registration mortality dataset will be the only mortality information requested.

Kings College London is the data controller and also processes the data for this study. No other organisations process the data for this purpose.

NHS Wales Informatic Service (NWIS) is a public service organisation which manages requests for access to administrative data including the PEDW. KCL will request similar data fields from NWIS as from NHS Digital to enable similar data fields for the analysis for patients in both England and Wales.

The NHFD is a clinically led, web-based quality improvement initiative commissioned by the HQIP and managed by the Royal College of Physicians (RCP). Crown Informatics are RCP's data processor who will be sending in the cohort to both NHS Digital and NWIS for linkage. The Healthcare Quality Improvement Partnership (HQIP) is a joint Data Controller for the NHFD data but not for the HES data being released by NHS Digital or PEDW data being released by NWIS. RCP and HQIP will have no access to the data and will play no part in the processing of the data for this study.

Researchers at the University of Oxford, University Hospital of Wales and University of Bristol will contribute to the interpretation of results, and preparation of materials for dissemination. They will have no access to the data and will play no part in the processing of the data for this study.

This research is funded by the Chartered Society of Physiotherapy Charitable Trust. The funder has no role in the design of this study, execution, analyses, data interpretation, or overall dissemination plan. The applicants are required to present the results of the study at the annual Chartered Society of Physiotherapy conference as a condition of the funding award.

Expected Benefits:

This project will help to inform a reduction in unwarranted variation in current rehabilitative care to ensure high standards of quality and safety of rehabilitative health care and in turn promote patient health. This will be achieved by addressing the aims outlined above which will identify and report health inequities in access and delivery of rehabilitation after hip fracture and the impact of those inequities on outcomes, and dissemination of the findings to stakeholders involved in the receipt, delivery, and organisation of rehabilitation after hip fracture, as outlined in the outputs section.

75,000 people incur hip fracture each year. On average, these patients spend 15.5 days in hospital at £400 per day. If a reduction in unwarranted variation in rehabilitation duration, frequency, or type led to one less day in hospital for half of all admissions this would reflect a cost saving of £15,000,000 each year.

It is therefore in the public interest to ensure high standards of quality and safety of rehabilitative health care for these people. It is appropriate for the proposed analysis to be completed and results disseminated as they will inform quality improvement initiatives to reduce unwarranted variation and improve the standards of quality and safety of rehabilitative health care.

In 2017, the National Hip Fracture Database audit demonstrated marked national variation in the duration, frequency, and type of acute rehabilitation delivered by physiotherapists. The audit was not resourced to evaluate the association between duration, frequency, and type of rehabilitation with outcomes. The outputs will address all aims outlined above and therefore determine the association between duration, frequency, and type of rehabilitation and outcomes. Moreover, the outputs will be disseminated to all stakeholders to facilitate implementation of quality improvement initiatives to reduce unwarranted variation.

The requested HES data contributes a significant impact to the aims outlined above. First, it will enable KCL to determine the association between rehabilitation duration, frequency and type and readmission and survival at 30-days. These outcomes are key to informing future quality improvement initiatives. Second, without these data, the analyses will fail to control for potential confounders for the putative association between rehabilitation duration, frequency, and type on outcomes. Third, without these data, KCL will not be able to determine whether different subgroups of patients respond differently to rehabilitation duration, frequency, and type.

These analyses are likely to inform a reduction in unwarranted variation in access and delivery of rehabilitation to improve outcomes by identifying and reporting health inequities (as they relate to outcomes).

Patients and the NHS will achieve the benefit through improvements in standards of quality and safety of rehabilitative health care.

The benefit will be measured through successful completion of the dissemination strategy outlined in ‘Specific outputs expected, including target date’.

The analysis will be completed and dissemination 24 months after release of data.

Outputs:

An interim report on the progress of the research will be sent to the funding body (Chartered Society of Physiotherapy Charitable Trust) in June 2020. A final report to the Chartered Society of Physiotherapy Charitable Trust will follow in June 2021. This will cover results to address all aims outlined above.

Planned academic papers submitted to open-access peer reviewed journals:

1 - the odds of return to preadmission residence, and recovery of mobility at 120-days, overall and by duration, frequency, and type of rehabilitation after adjustment for potential confounders (December 2019);

2 - the odds of readmission and survival at 30-days post-discharge overall and by duration, frequency, and type of rehabilitation after adjustment for potential confounders (January 2020);

3 - the probability of discharge by time after surgery overall and by duration, frequency, and type of rehabilitation after adjustment for potential confounders and the competing risk of death (May 2020);

4 - variation in the odds of return to preadmission residence, and recovery of mobility at 120-days, overall and by duration, frequency, and type of rehabilitation after adjustment for potential confounders across subgroups defined by patient and care factors (August 2020);

5 - variation in the odds of readmission and survival at 30-days post-discharge overall and by duration, frequency, and type of rehabilitation after adjustment for potential confounders across subgroups defined by patient and care factors (December 2020);

6 - variation in the probability of discharge by time after surgery overall and by duration, frequency, and type of rehabilitation after adjustment for potential confounders and the competing risk of death across subgroups defined by patient and care factors (May 2021);

A lay version of the findings of each paper will be disseminated to patients and the public interested in research on hip fractures through the Royal National Osteoporosis Society.

For each paper published, briefing papers and PowerPoint slide decks will be developed to summarise the findings for a range of stakeholders including healthcare professionals, policymakers, patients and their caregivers.

Findings will be presented at the Fragility Fracture Network 2020 and 2021, the British Geriatric Society 2020 and 2021, as well as the Chartered Society of Physiotherapy 2021.

All publications and conference presentations will be promoted on twitter via the Kings School of Population Health and Environmental Sciences account (>1000 followers), the Falls & Fragility Fracture Audit Programme account (>1500 followers) and study personnel (>2000 followers).

All outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide.

KCL will publish outputs in peer-reviewed open-access journal articles and in reports for the Chartered Society of Physiotherapy Charitable Trust.

In the UK KCL will work with the Chartered Society of Physiotherapy to disseminate findings to the national community of physiotherapists through their website and publication Frontline. KCL will communicate findings nationally through the FFFAP, the British Orthopaedic Society, the British Geriatrics Society, and the Royal College of Occupational Therapists to substantiate their position on access to therapy.

KCL will present findings locally (London, Bristol, Bath, Cardiff, Oxford, Norwich hospitals), nationally (Physiotherapy UK, British Geriatrics Society and British Orthopaedic Society conferences), and internationally (Fragility Fracture Network conference).

KCL will continue to partner with the National Osteoporosis Society to disseminate findings to the public via their various media streams: updates/articles in their quarterly membership magazine Osteoporosis News (23,000 readership); their Bone Matters e-newsletter (21,000 readership); and on the research section of the website (www.nos.org.uk/research).

KCL will provide briefing papers and PowerPoint slide decks to policymakers who influence hip fracture quality care indicators for Best Practice Tariffs such as Public Health England, FFFAP, and NHS Improvement. KCL will also present briefing papers and slide decks to NICE in preparation for future updates to the NICE Hip Fracture guideline (CG 124).

Internationally, KCL will work with the Fragility Fracture Network physiotherapy and rehabilitation special interest groups. KCL will disseminate findings to the International Coordinating Council for the Bone and Joint Decade, the International Osteoporosis Foundation, and the European Geriatric Medicine Society.

All publications and conference presentations will be promoted on twitter via the Kings School of Population Health and Environmental Sciences account (>1000 followers), the Falls & Fragility Fracture Audit Programme account (>1500 followers) and study personnel (>2000 followers).

The dissemination of research outputs outlined above includes communication activities to target all stakeholders including patients and the public, clinicians, researchers, and policymakers. KCL will also work with the School of Population Health and Environmental Sciences communication team to develop press releases for media engagement.

Processing:

Crown Informatics (RCP’s data processor) will send the following identifying details for the cohort to NHS Digital:
- Study ID
- NHS number
- Date of Birth
- Surname
- Forename
- Postcode
- Date of Admission

NHS Digital will receive the cohort identifiers detailed above. NHS Digital will identify the relevant care spells for patients in HES data and will extract the data for the care spell related to hip fracture and any readmission within 30-days of discharge from the care spell. They will also extract the same data for care spells in the year prior to the hip fracture care spell. Fact of Death sourced from the Civil Registration Mortality dataset will also be extracted for the cohort and will only be used to indicate the survival status at 30 days following discharge from the care spell.

NHS Digital will send the following pseudonymised fields to King’s College London:
- Study ID
- [ADMIDATE] Date of admission,
- [ADMISORC] Source of admission,
- [DIAG_NN] All Diagnosis codes,
- [DISDEST] Destination on discharge,
- [ETHNOS] Ethnic category,
- [IMD04 IMD] Index of Multiple Deprivation,
- [IMD04HD IMD] Health and Disability Domain,
- [IMD04RK] IMD Overall Rank,
- [STUDY_ID] STUDY_ID
- [DISDATE] Date of discharge
- Survival status at 30-days (Calculated from Date of Discharge)
- Indicator of readmission within 30-days

There are no subsequent flows of data.

The flow of data from Crown Informatics into NHS Digital will include personal data with identifying details. The flow of data from NHS Digital to KCL will not contain identifying details.

Kings College London will process data from NHS Digital, as well as data received from NWIS and Crown Informatics. This data is personal data and will not contain identifying details.

Crown Informatics is processing data that will flow to NHS Digital, NWIS, and Kings College London.

Crown Informatics will identify the study cohort as all patients 60 years of age or older who underwent hip fracture surgery in England or Wales between May 1st and June 30th, 2017. Crown Informatics will then extract the cohort data detailed in this purpose statement and send to NHS Digital for England, and NWIS for Wales. Crown Informatics will then remove the identifying data except for the Study ID. Crown Informatics will also minimise the audit data requested to variables relevant to the stated purpose. Crown Informatics will send pseudonymised audit data including the Study ID to KCL.

NWIS will also receive the cohort details from Crown Informatics. NWIS will identify the relevant care spells for patients in PEDW data. NWIS will extract the data for the care spell related to hip fracture and any readmission within 30-days of discharge from the care spell, including survival status at 30 days. They will also extract the same data for care spells in the year prior to the hip fracture care spell. NWIS will send pseudonymised audit data including the Study ID to KCL.

KCL will link the data received from NHS Digital and NWIS to the data received from Crown Informatics using the Study ID. KCL will then process the pseudonymised data to meet the purpose and aims outlined above while enabling ‘the processing of personal data in such a way that the data can no longer be attributed to a specific data subject without the use of additional information’ (GDPR 2018). The additional information required to identify an individual will not be available at KCL. There will be no requirement/attempt to re-identify individuals.

The data processing at KCL will only be carried out by substantive employees of KCL who have completed KCL’s GDPR training and NHS Level 1 Data Security Awareness Training and who have confirmed in writing they have read and understood the protocols outlined and referred to in the Data Security and Protection Toolkit.

The data will be held as an encrypted file on KCL’s secure network drive. The encrypted file will be held in an access-controlled area of the network drive and the data will be accessible to authorised study personnel only, by means of a password or a recovery key. All users have their own username and password, and these will never be shared. Access to the data for the study will be cancelled as soon as a user leaves the study, KCL, or if they are absent for a long period.

Data will be stored on servers owned and managed by KCL, within the JISC Southern Data Centre. Only individuals with the administrative rights to those servers will be able to access data stored on them. The only individuals with those administrative rights are KCL’s IT Computer & Storage team. JISC is a United Kingdom not-for-profit company whose role is to support post-16 and higher education, and research, by providing relevant and useful advice, digital resources and network and technology services, while researching and developing new technologies and ways of working.


Project 25 — DARS-NIC-134027-L9T9J

Opt outs honoured: Yes - patient objections upheld (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7)

Purposes: ()

Sensitive: Non Sensitive, and Sensitive

When:2019.12 — 2019.12.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Civil Registration - Deaths
  3. HES:Civil Registration (Deaths) bridge

Objectives:

The purpose of the current project is to investigate the longer-term outcomes of treatment engagement and A&E attendance among adolescents accessing South London and Maudsley Children and Adolescent Mental Health Services (CAMHS) who received a 'Therapeutic Assessment' (TA) versus 'Assessment as Usual' (AAU) when they initially presented to A&E for self-harm.

This is an 8 year follow up study from an original randomised controlled trial which demonstrated that TA, a brief, psychotherapeutic intervention for adolescents who present with serious self-harm, significantly improves engagement with follow-up treatment (Ougrin et al., 2011). This model has been independently replicated by a US research group with remarkably similar results (Asarnow et al., 2011). The first follow-up study showed that the impact of TA on engagement persists at least 2 years after the initial intervention (Ougrin et al 2013). This had led to a recent update with a recommendation for TA in the NICE guidelines for self-harm in adolescents (https://arms.evidence.nhs.uk/resources/hub/964618/attachment). There is significant interest in training and implementation of TA both in the UK and around the world. The chief investigator’s research group developed the model of TA and undertook its evaluation.

An aim of the current study is to further investigate whether the treatment engagement benefits observed at 2 years follow up still exist at 8 years. In addition, the research wishes to identify whether the use of TA had any positive effect on A&E presentations for self-harm in the longer-term. Outputs provided from NHS Digital will therefore feed into a larger study which also explores the level of treatment engagement among individuals who have continued to access South London and Maudsley NHS services.

Both South London and Maudsley NHS Foundation Trust (SLaM) and King’s College London are hosting this research project in order to collect the relevant patient information and analyse the aggregate data, respectively.

No elements of the work will be taking place outside the UK. The same applies for existing data collected by the team.

Aggregate-level data will be published in a peer reviewed journal.

Expected Benefits:

The data provided will contribute to research which aims to identify whether there are any long-term benefits to using a therapeutic assessment model for self-harm in adolescents accessing mental health services. This will yield additional insights to the findings already observed at short and medium-term time points. To date, the existing research has led to a recent update with a recommendation for TA in the NICE guidelines for self-harm in adolescents (https://arms.evidence.nhs.uk/resources/hub/964618/attachment).

Given that this study is the first of its kind to investigate long-term outcomes for self-harm focused intervention, the research team hope that the research will be of benefit in the following ways:
- To help inform psychosocial assessment protocols for this group of patients
- To contribute to a 3-year programme of work which seeks to improve the quality of patient care within the trust
- To update and inform further training in Therapeutic Assessment for mental health professionals both within the UK and worldwide.

Outputs:

Outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide.

Aggregate level data will shared in the following ways:

- Publishing in an open access peer reviewed journal. The original study has been published in Archives of Disease in Childhood. This will therefore be accessible to academics, clinicians and members of the general public
- Self-harm research meetings within South London and Maudsley NHS Foundation Trust (open to Children & Adolescent Mental Health Service academic and clinical staff)
- Quality Improvement meetings within South London and Maudsley NHS Foundation Trust. Led by senior clinicians as part of a three-year programme aiming to introduce improvements that will drive up the quality of patient care

Deadlines: data on treatment engagement was collected in September 2017. The research team aim to collate all data by the end of 2018.

Processing:

SLaM will submit identifiers of the cohort to NHS Digital for linkage to pseudonymised HES and Civil Registration (mortality) data.

Data on the cohort's A&E attendance rates will be obtained from NHS Digital containing the Study ID which will be received by a member of the research team based in the Supported Discharge Service (Maudsley Hospital) where it will be stored securely on South London and Maudsley NHS computers. The data received will be linked with the existing patient data on basic demographics and treatment engagement. For this reason s251 approval has been sought and granted by CAG. Any identifiers will then be removed before the data is transferred to members of the research team and statisticians within King’s College London for analysis. Data will be aggregated for publishing. No identifiable information shall be stored outside of NHS trust computers.

Collection of data via this means has been approved by the Research Ethics Committee with section 251 support (REC reference: 16/EE/0308). Data will be kept securely in accordance with South London and Maudsley NHS Foundation Trust’s and King’s College London’s data protection policies, which research staff have knowledge of from mandatory training. All researchers working on the study are directly employed within King’s College London or South London and Maudsley NHS Foundation Trust.

Taking the short to medium-term findings observed from the original study and two year follow-up, it would be important from the scientific and clinical points of view to find out if the dichotomy between treatment engagement and A&E attendance rates remains in the longer-term or if the improved engagement leads to changes in A&E attendances.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

All outputs will only contain results in highly aggregated format and as statistical summaries and measures of association. Small numbers will be suppressed in line with the HES Analysis Guide. Record level information will not be released to any third party.


End of life care outcomes for adults with serious mental illness — DARS-NIC-144761-Y3X9Y

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-08-26 — 2020-08-25 2019.11 — 2019.11.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Civil Registration - Deaths
  3. Hospital Episode Statistics Admitted Patient Care
  4. HES:Civil Registration (Deaths) bridge
  5. Civil Registration (Deaths) - Secondary Care Cut

Objectives:

King’s College London (KCL) requires the data necessary for its research project ‘End of Life Care Outcomes for Adults with Serious Mental Illness (SMI)’.

The aim of this work is to explore the end of life care circumstances of adults with a diagnosis of serious mental illness (SMI). End of life care outcomes are measured by hospital admissions and A&E visits at the end of life and place of death. The project aims to achieve a clear picture of where patients with SMI die and their health care utilisation at end of life and assess what demographic and/or clinical factors are associated with place of death in this patient group. The objectives are as follows:
• To describe the acute care service use (including hospital admission, the length of hospital stay, A&E visit) in the last year of life, and place of death in people with SMI
• To evaluate factors associated with acute care service use and place of death in those with SMI and their relative importance
• To explore the relationship of the acute care service use and place of death.

This project is in the public interest as KCL believes it is making a valuable contribution to science and, with the results, KCL hopes to demonstrate whether or not patients with SMI face inequalities in care at end of life. Ethical approval has been obtained. There is minimal risk of harm as data will be pseudonymised, stored securely and summary data only will be reported in dissemination.

The data requested are required to meet the following three aims:

1] To describe the acute care service use (including hospital admission, the length of hospital stay, A&E visits) in the last year of life, and place of death in people with SMI.

To meet this aim KCL requires the following items from HES data: the dates of admission and discharge to generate measures of number of admissions/A&E visits and the length of hospital stays in the last year of life, and mortality data, which includes individuals’ place of death. Place of death can be summarised as hospital, home, hospice, care home and other, if the place of death could potentially identify an individual (e.g. a residential address). These data will enable KCL to describe the outcomes of interest for this project.

2] To evaluate factors associated with acute care service use and place of death in those with SMI and their relative importance.

This aim will identify the demographic and clinical factors associated with the outcomes of interest: acute care at end of life and place of death. Patient demographics and clinical factors, available from MHDS and mortality data, are required to explore associations with the outcomes derived from HES and mortality data.

3] To explore the relationship between acute care service use and place of death.

To meet this aim, KCL will use the derived measures of number of admissions and length of hospital stay and number of A&E visits (generated from HES data) and the categorical measure of place of death (from mortality data) to explore bivariate associations between these outcomes.

One member of the research team applied for and secured funding from KCL to undertake this project. This was to continue and expand upon previous working carried out at a local level. Previous work by the research team has explored end of life care outcomes in adults with SMI in a south London dataset (Wilson et al, 2019*). This work identified inequalities in end of life care in this localised patient group; the purpose of the proposed project is to assess end of life care at a national level.

The research team have also conducted a systematic review (unpublished, currently under review) assessing the current evidence base for the end of life care outcomes for people with SMI. This review found that more focused, rigorous research is needed in this area.
*Wilson et al. 2019. “Place of Death and Other Factors Associated with Unnatural Mortality in Patients with Serious Mental Disorders: Population-Based Retrospective Cohort Study.” BJPsych Open 5(2): e23.

This project builds on an ongoing project assessing end of life care in patients with SMI in South London, which uses a linked dataset from the South London and Maudsley Trust. For clarity, this project will not involve linkage with or any other use of data from that other project.

Under this Agreement, KCL requires data from a one-year time period. If this project proves an efficient way of demonstrating end of life care outcomes in patients with SMI and highlights inequalities in this population, the research team may request data from a long period of time to perform longitudinal analysis and explore time trends. The results of this project may contribute to/inform the development of a post-doctoral fellowship application.

This is a cross-sectional observational study including a cohort of people with SMI. The sample are adults (18 years+) who died with a diagnosis of schizophrenia, schizotypal or delusional disorder (ICD 10 F20-F29), bipolar disorder (F31), depressive episode (F32) or recurrent depressive disorder (F33). There will not be a control group.

KCL requires Hospital Episode Statistics (HES) and mortality data for use in the study, End of Life Care Outcomes for Adults with Serious Mental Illness. Linked data for eligible observations are required at an individual level for individuals that died within one calendar year (the latest year for which all linked data are available). Data will be pseudonymised.

Mortality data are required to assess place of death and cause(s) of death. HES data are required to identify patients with a diagnosis of SMI (defined above) who died within the HES 2018/19 year. HES data (admissions and A&E) are also required to measure acute service use in the last year of life. Data are required for one year to measure admissions and A&E visits in the last year of life, the time frame considered to capture health care use at the end of life. National data are required as this proposed project is a continuation of a previous project that explored end of life care outcomes in patients with SMI in south London (data were provided by a south London mental health trust, SLAM). National data are required to expand on this localised project. Data are requested for patients with the following psychiatric diagnoses: schizophrenia, schizotypal or delusional disorder, bipolar disorder, depressive episode or recurrent depressive disorder.

Date of birth fields are to be provided in Month/Year format for pseudonymisation.

Data are requested only for eligible individuals (those with an eligible diagnosis). KCL are requesting data for just individuals who died within HES year 2018/19.

KCL is the only organisation involved in this study and the sole organisation responsible for determining how and why the data will be processed. All researchers involved in the study are employed by KCL as research or academic staff.

Expected Benefits:

Dissemination in peer reviewed journals and at conferences and the dissemination of the results through the KCL network (which includes collaboration with the South London and Maudsley NHS Trust, Europe’s largest provider of mental health care) is intended to change policy and directly influence adult health care for adults with SMI.

Dissemination of results is in the public interest and the study team intend to use the data to show whether or not there are inequalities in care for people with SMI.

The study team will be submitting our results to open-access high impact journals. Open-access is crucial for dissemination of the study results as KCL hopes to reach as wide an audience as possible. Publishing in high impact journals is also important to represent the value of the work. The main target journal will be the British Journal of Psychiatry, as a high impact journal within the field of psychiatry (impact factor 5.9; 10 out of 142 for psychiatry) and the primary journal for psychiatrists in the UK. Failing publication in the British Journal of Psychiatry, alternative journals to consider would be The Lancet Psychiatry and the Journal of Psychiatric Research.

The results will be presented to psychiatrists and members of mental health teams at the Institute of Psychiatry at King’s and share our results with other clinical teams. the study team will pursue opportunities to present the results at clinical forums, such as the European Psychiatry Association congress and the European Association of Palliative Care annual conference. The study team will produce policy briefs summarising the results of the study. These will be used to respond to any relevant calls for information put out by MPs, health care committees, task forces or special interest groups. The study team will proactively look for any individuals or groups (in policy) with an interest in mental health and health care. The study team will also disseminate our policy briefs at study days and events held in our department, which are regularly attended by policy makers.

The outputs (peer reviewed publications, presentations at scientific forums, policy brief) achieve the purpose of the project by disseminating the results we find from the data.

The benefits of the dissemination plan include targeting and reaching the most relevant individuals. Papers will be sent to psychiatry journals and abstracts to psychiatry and social science conferences. Policy briefs and results summaries will be shared with relevant charities and third sector groups.

The outputs from this project will show, for the first time as far as the study team are aware, what acute health care adults with SMI in the UK receive in the last year of life and where they die, demonstrating whether there are inequalities in place of death compared to the general population. KCL will also be able to show if other factors (e.g., age, diagnosis, gender, ethnicity) are associated with inequalities in health care access. This evidence is needed for change (in the provision of care for this patient group). The results. Through publishing in a psychiatry journal, health care professionals are more likely to see these results and be made more aware of the end of life care issues faced by their patients, this could help to change practice. If the results of the project are picked up by policy makers, they could potentially inform policy around the provision of end of life care for patients with SMI.

The benefits will be measured in several ways. First, the reach of the results will be measured by summarising and evaluating the dissemination of the work, including readership of the journal in which the results are published, number of downloads, online readers and retweets.

The approximate size of audiences to which the results are presented will be measured. Impact of the results will be measured initially by engagement with clinicians and policy makers. Raising awareness of end of life care in patients with SMI in clinicians (palliative care, psychiatry and general medicine), though not measurable, is an essential benefit for initiating change in the provision of end of life care for patients. The goal of this work is to raise awareness of patients’ end of life care needs in clinicians working in psychiatry and to raise awareness of an underserved population (patients with SMI) in palliative care for relevant health care professionals. Discussion between partners and collaboration between palliative care and psychiatry will be an indicator of education and awareness of the project and research goals. It will be possible to measure direct benefit for patients when changes are made to reflect the increased awareness of the need for high quality end of life care, although this is likely to take time. These changes will include more focus of advanced planning for patients with SMI and recording end of life care preferences, less emergency care at end of life (which will be a marker of better end of life care planning) and more patients accessing high quality palliative care at the end of life. These outcomes will be measurable in future years when data are available to depict what end of life care patients are receiving. In future years, KCL will be able to perform time-trend analysis to explore if outcomes have improved over time.

KCL hopes that its research ultimately improves end of life care for people with SMI in 2014 0-3.3% of the population in England are estimated to have a diagnosis of SMI (roughly 1.0m people). This is an under-researched area of health care provision. There are concerns that people with SMI have received worse health care at end of life and this work will demonstrate whether these patients experience health care inequality at the end of life. If the data shows that people with SMI have worse health care experiences, this provides evidence of inequality and support for improvement of services (including better end of life care) for patients with SMI. Change in provision of services or prioritisation of a vulnerable patient population is not possible without robust evidence to demonstrate need.

Outputs:

The following outputs will be produced:
Progress reports will be provided to the funders (King’s College London) throughout the project. These will describe the progress of the work (e.g. having received the data, analysis, manuscript writing) and will not divulge any data/results.

The first output will be a short report, published in a psychiatric journal, by the end of the year (December 2019). This output will report descriptive statistics for the cohort, including place of death and cause of death and other demographics.

The main results of the paper will be published in a psychiatric journal in 2020. This paper will report the factors (demographic and clinical) associated with place of death in patients with SMI. It is hoped that this will demonstrate the pathways by which various demographic variables are associated with health care and end of life care. By publishing in a psychiatric journal, psychiatrists and mental health professionals are the target audience, thus the aim of this work and targeting this audience is to highlight the importance and needs for good end of life care in this vulnerable patient group.

Additional outputs will include abstracts of the main results to one or more of the following: the European Psychiatric Association in 2020, the European Association for Palliative Care in 2020 or the Society for Social Medicine 2020.

Results of the study will also be disseminated to patient and carer groups, including Mind and MQ Mental Health and to followers of the work of the Cicely Saunders Institute, through Twitter, PPI groups, etc. KCL will also write a policy brief, which will summarise the work and the main results in a policy brief and will be disseminated to relevant groups and individuals.

Outputs will always be aggregate with small numbers suppressed.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

NHS Digital will create the cohort using HES filters and extract relevant records and pseudonymise the data.

There will be a single flow of linked and pseudonymised record level data from NHS Digital to King’s College London (KCL), with pseudonymised ID and no identifying data. There will be no further flow of data.

KCL will be the sole organisation involved in processing the data. As per the application purpose section, researchers at KCL will manage the storage, cleaning, analysis and interpretation of the data.

The data will not be linked with any record level data or be matched with publicly available data. There will be no requirement or attempt to re-identify individuals from the data.

Data will only be accessed by individuals within the Cicely Saunders Institute, KCL who have authorisation from NHS Digital to access the data for the purpose described, all of whom are substantive employees of KCL.

KCL will store the data on a secure server at the Cicely Saunders Institute, KCL, which can only be accessed within the department (located at Denmark Hill campus, KCL) by researchers named on the project. Data analysis will be conducted by role based access, limited to researchers working in the study team, on the departmental computer on which the data are stored (ie, analysis will not be conducted remotely). Data will be accessed by employees on a secure server on a desktop computer within the department (Cicely Saunders Institute, KCL).

The data will not be made available to any third parties.
Results will be presented at an aggregate level in research outputs. All data will remain anonymous. Small cell counts will be suppressed (N<10).


Cognitive Behavioural Therapy for Dissociative (Non-Epileptic) Seizures: A Randomised Controlled Trial (CODES Study) (LREC LO/13/1595) — DARS-NIC-68229-Y5J6V

Opt outs honoured: No - consent provided by participants of research study, Identifiable, No (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-03-18 — 2022-03-17 2019.08 — 2019.08.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON, SOUTH LONDON AND MAUDSLEY NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Outpatients
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Accident and Emergency

Objectives:

King’s College London (KCL) and South London and Maudsley (SLaM) NHS Foundation Trust requires HES data for the purpose of a research study called The Cognitive Behavioural Therapy for Dissociative (Non-Epileptic) Seizures (CODES).

About 12-20% of patients who attend neurology or specialist epilepsy clinics because of seizures do not in fact have epilepsy but instead have dissociative (non-epileptic) seizures (DS). A high percentage of people with dissociative seizures will have other psychological or psychiatric problems and may have other symptoms. It is generally thought that people with dissociative seizures will benefit from psychological treatments. However, studies on this have been small or have not compared the psychological therapy with the treatment people normally receive (there is no standardised medical care (SMC)). There is some evidence that cognitive behavioural therapy (CBT) may lead to a reduction in how often people have dissociative seizures. CBT is a widely accepted psychology therapy that focuses on the person's thoughts, emotions and behaviour, and considers the physical reactions and sensations that may occur in their body.

KCL has previously developed a CBT package for people with dissociative seizures. In a relatively small previous study, people receiving CBT overall showed greater reduction in how often they had their seizures. KCL is now leading on a larger study across several different hospitals, to obtain more definite results. The data processed by KCL is processed under Articles 6(1)(e) and 9(2)(j) as necessary for scientific research that is in the public interest. This is in line with KCL’s charter as an institution carrying out research in the public interest.

KCL and SLaM do not consider there to be any moral or ethical issues raised by the dissemination of the data. The processing of personal data was clearly explained to participants who provided written consent for the research team to have access to health related records including records held by the Information Centre, the General Register Officer and other health related databases. At the time of recruitment, NHS Digital was known as the NHS Information Centre. Therefore, KCL/SLaM feel that participants have given them permission to access their data for the purpose described in this Agreement.

The CODES study is a large multi-site study being funded by the National Institute of Health Research Health Technology Assessment programme (NIHR HTA). The study was submitted in response to a call from the NIHR HTA in 2012 to create a study to examine a treatment for this condition and to examine the health care costs to individuals and the NHS. The study is ‘co-sponsored’ by South London and Maudsley NHS Foundation Trust (SLaM) but SLaM does not determine any purposes of the study. The project is managed by staff at KCL and all patient data remains vested in KCL when the project completes. SLaM is provided with a small amount of research capability funding to facilitate the research because it requires NHS sponsorship. The only roles SLaM has is to process the grant funding and also an individual employed at SLaM is a co-investigator in the trial.

Individuals from SLaM, the University of Sheffield, the University of Edinburgh and Royal Edinburgh Hospital are named as co-investigators in the study protocol. These individuals are part of the trial management group meaning they are equally responsible for the grant and collectively form one of the decision-making bodies of the trial. However, within the clinical trial there are different levels of decision-making. The decision to process HES data from NHS Digital was taken solely by the Chief Investigator from KCL and the decisions about how that data is analysed are taken by the Professor of Health Economics, also of KCL. The co-investigators are not data controllers.

As co-sponsors for the trial, KCL and SLaM are joint data controllers for the purpose of this Data Sharing Agreement.

The trial has 3 significant centres where organisations have contributed materially to the trial but are not processing the data: The University of Edinburgh, NHS Lothian and the University of Sheffield. They were recruitment sites but had dedicated trial staff who managed recruitment at the many trusts around these institutions. 45 NHS trusts took part in recruiting participants, a smaller number of these, 19, were treatment centres as well. Recruitment began in July 2014 and continued until May 2018 with 368 total participants consenting to be randomised across the UK. Of these, 284 participants consented in England and were not withdrawn at the end of the study. The data requested is for these participants only.

All participants in the trial have provided a significant amount of data about their condition, how it impacts their lives and the lives of those who care for them, how their general health is, how they feel about their emotions, if they avoid things because of their seizures and many other facets of their lives. They did this up to three times during the trial period (baseline, 6-month follow up and 12-month follow up). 30 participants, just under 10% of the 368 who were randomised, also provided qualitative data by participating in a semi-structured interview with one of the researchers exploring their treatment, medical history, and experiences on the trial. The data KCL is requesting from NHS Digital contributes to a small part of the outcomes listed in the protocol.

One of the trial's outcome measures, per the protocol, is to examine and cost participants' service use and KCL originally intended that this would come only from participants. However, in addition to the self-report, the funder (NIHR HTA) advised including a more objective measure of service use and identified centrally-recorded data on hospital admissions, routine attendances and emergency department attendances as the best measure of this service use from a non self-report measure.

Participants who consented to the study were randomised to one of the two treatments. Service use for 6 months prior to each participant’s randomization will be requested and used as a baseline and the data from the 6 months prior to the end of each participant’s follow up period will be also be requested. In effect this means 6 months of data ending on the day of randomisation, followed by a six-month gap during which no data is requested from NHS Digital, and then another 6 months of data ending on the day the participant finished in the study. The dates for most participants will differ depending upon what day they were randomised.

The primary outcomes for the trial are all measured 1 year after randomisation representing the beginning of treatment. The data will provide an objective measure of service use, without relying on the participant's memory. Furthermore, participants who suffer from dissociative seizures tend to have costly and inappropriate medical use, especially before a diagnosis is made (Mellers, 2005). Therefore, the use of this data will allow KCL to see whether diagnosis and treatment of dissociative seizures reduces service use - a question very important to answer when the NHS services and resources are stretched. Furthermore, health economics analysis will be carried out to assess the cost of service use in KCL’s sample, and to see if this cost is reduced during the study.

The same analyses will be run on both the self-reported data and the data from NHS Digital. The findings of both analyses will be compared. The data will not be compared at individual participant level. Ideally, the analyses of both datasets should show the same levels of service use. If so, having two corroborating sources will make the findings more robust. If there are differences, the findings will be presented objectively and KCL will attempt to account for the differences. For example, there may be data entry bias in the HES data from NHS Digital or memory bias in the self-reported data. For the credibility of the study, it is important to present any differences and explain what they were attributed to.

The data will only be accessible to the CODES study team at King's College London. The CODES team involves the Trial Manager, and the Professor of Health Economics and Junior Health Economist. All have computers based at King's College London, and data will only be stored on these computers. No other organisation will have access to the data.

Expected Benefits:

The overall aim of the CODES study is to determine whether being given a diagnosis of dissociative seizures and receiving one of two types of treatment reduces participants’ seizures, as well as their psychological distress symptoms and healthcare service use. The information KCL are requesting is in line with the information KCL have asked of the participants already, but this measure comes from system wide usage and will help avoid any forgotten, mis-remembered, or unreported data to provide an accurate and real reflection of cost and service usage. This use of this data from NHS Digital will enable KCL to conclude whether or not certain treatments reduces healthcare service use in patients with dissociative seizures. If it does, in the long term it will mean less money is being spent by the NHS which is very important as the NHS is currently financially strained. The outputs are expected in late 2019-20. The outcome of the health economics findings will be included in these outputs.

Policy makers, CCGs, and other materially interested parties will be invited to a conference about the results with any health economics outcomes being extremely important. These outcomes, if sufficiently robust, could form the basis of any recommended changes to the health care system around this diagnosis and the treatment of people who have it. For example a CCG might decide to fund CBT therapy treatments for the condition because it is associated with better outcomes for the patient and a reduction on unnecessary A&E visits. The most significant change to the health care system and to patients in general would be a recommended standard care pathway for patients with this diagnosis. These changes rely in part on the outcomes from HES about the service usage. These changes could be incorporated into the health care system within a few years.

Outputs:

Findings for KCL’s baseline data, which would include data from HES, will be submitted by the middle of 2019, and KCL’s final outcome paper would come in late 2019 in a journal such as the Lancet or Journal of the American Medical Association. KCL will also publish results in the HTA's own journal which will include HES data. KCL are committed, as is KCL’s funder, to open access journals so that this information is available as freely as possible.

Findings from the study will be communicated back to CODES participants through a specially written document posted to them after KCL’s analysis is complete. KCL will also be including an alternative infographic version of the findings where possible to convey the information as succinctly and easily as possible to the participants.

The findings will also be reported on the trial website (http://www.codestrial.org/) which contains information for patients (not limited to trial participants) and health professionals (see: http://www.codestrial.org/information-booklets/4579871164).

As the CODES trial is a first trial of its kind and the largest ever done with people who have dissociative seizures, KCL’s work will be of interest to many conferences. KCL will submit presentations to the following conferences, which would include results from KCL’s analysis of the data provided by NHS Digital. British Neuropsychiatry Association, International League Against Epilepsy- British Chapter- annual conference, American Epilepsy Society annual conference, European Congress on Epileptology,

International Congress on Epileptology, Annual Conference of the British Association for Behavioural & Cognitive Psychotherapies, and the Annual meeting of Association of British Neurologists.

All outputs will be in aggregate form only with small numbers supressed in line with the HES analysis guide.

Processing:

KCL will submit the NHS number, study ID (Participant Identification Number or PIN), and two dates to NHS Digital for each participant. The dates for each participant are the date six months prior to randomisation and the date six months prior to completion of follow up for each individual. All participants have consented to this information being passed to NHS Digital for this purpose. The information KCL is requesting has also been requested from the participants through a self-report measure but receiving the HES data from NHS Digital will provide an independent measure. The information KCL receives from NHS Digital is not going to be directly compared to the individual’s self-report. Instead both self-report and the data provided by NHS Digital are summarized and compared on an aggregate level.

Using the NHS Number, NHS Digital will extract and provide the HES data requested for each participant. The data requested relates to HES outpatient, admitted patient care and A&E visits only. The returned data will contain no directly identifying details but will include the participants unique study ID. The linked data will be provided by NHS Digital to the study team and downloaded by the Trial Manager onto the highly encrypted secure hosting environment provided through KCL’ s protected digital network storage. It will be stored, processed and linked only through the server hosted by KCL which can only be accessed by substantive employees of the university: the Trial Manager, Chief Investigator, Professor of Health Economics and the Junior Health Economist. All individuals with access to the data are substantive employees of King’s College London. All processing activities will take place within KCL.

The data set will be kept and stored separately to the identifying details and will include the study ID number. The data will not be linked to other data held by KCL, with the exception of a treatment identifier indicating whether the participant received CBT and SMC or SMC Alone. These are the two treatments the trial is comparing.

The data from HES will contribute to a health economics analysis which is interested in average costs and service use in patients. The data provided from HES will be compared at an individual level to see if participants’ service use (and the costs associated with this service use) changed during the study. This will contribute to an understanding of whether or not CBT and SMC or SMC alone are related to a decreased use of services, and if so how much savings that translates to taking into account the cost of the treatment. The HES data will not be directly compared to the self-report data on an individual level. Instead the aggregates of service use change within the HES data will be compared at aggregate level to the self-report data to see if they both show similar trends. All reports/outputs will be aggregated with small numbers suppressed in line with the HES analysis guide.


Modelling small-area rates of self-harm in London — DARS-NIC-174740-C0H0L

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-02-18 — 2022-02-17 2019.07 — 2019.07.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON, SOUTH LONDON AND MAUDSLEY NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

Objectives:

South London and Maudsley NHS Trust and King’s College London require HES Admitted Patient Care (APC) data for use in a project entitled ‘Understanding variations in self-harm rates between deprived areas in London’.

This study forms the final part of a PhD project examining variations in the rates of self-harm between small-areas in London. The applicant is employed by King’s College London (KCL) and registered as a PhD student within the Department of Psychological Medicine at KCL. They also do clinical work as a psychiatrist for South London and Maudsley NHS Foundation Trust (SLaM) and has a clinical addendum to their contract with KCL which establishes an honorary contract for this work.

The National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre (BRC) is part of SLaM and works in partnership with the Institute of Psychiatry, Psychology & Neuroscience at King's College London. Together they aim to develop more individualised treatments and support advances in the prevention, diagnosis, treatment and care of mental ill health and dementia. To do this, they bring together researchers, clinicians, allied health professionals and service users from across the University/Trust partnership to work together better in order to meet the challenges of finding better treatments and improved care for patients. Staff working within the BRC are SLaM employees, all data for BRC projects is held on the SLaM network and owned by SLaM and individuals employed outside SLaM who access BRC resources have to hold honorary contracts with SLaM.

The earlier studies within the PhD project have used non-NHS Digital data held by SLaM. The applicant has worked with this data within the SLaM network. Within the Maudsley BRC, SLaM has expertise, security and information governance frameworks in place for hosting clinical data. For this reason, it is proposed that the data requested for this study will also be held by SLaM. No data will be stored by KCL and it will not have access to any record level data supplied by NHS Digital. Hence, SLaM will be the sole data processor.

The study was devised by the applicant as part of the work towards the PhD they are completing at KCL. The PhD is funded through a clinical research training fellowship awarded to the applicant by the Wellcome Trust.

This study forms the final part of a PhD project examining variations in the rates of self-harm between small-areas in London. Work prior to this study is currently using a clinical dataset already held by the Maudsley BRC, of non-NHS Digital data, covering an area of South East London. This work is testing associations between area exposures and rates of hospital admission for self-harm for people aged 11 and over living in four London boroughs. Subsequent work will build a model that aims to predict rates of self-harm based on area-level variables.

The study this application relates to aims to
1) Describe the distribution of self-harm hospital admission rates across small-areas of Greater London and over time and compare them to the distribution of all admissions to identify any self-harm specific spatial patterning.
2) Explore the impact of using different definitions of self-harm, for exampling including injuries and poisonings coded as of undetermined intent or accidental, on associations with self-harm rates and the geographical patterning of self-harm rates.
3) Test the validity of a model using area and population level exposures to predict areas with high and low rates of self-harm.

Data for this study has not been provided by NHS Digital before.

The data required from NHS Digital is pseudonymised Hospital Episode Statistics Admitted Patient Care data. This will be used to identify the outcome of interest for the study: admission to hospital for self-harm. The NHS Digital data will not be linked with any other data sets and there will be no attempt to identify individuals. Data is required for individuals living in Greater London at the time of admission, for the years 2008-2017 as this is the study area and period of interest. Data for all individuals aged 11 or older is being requested so that the dataset the model is being tested on matches the clinical data that was used to build the model in this regard. Data for younger individuals is not being requested as incidents of self-harm are rare prior to adolescence. Data would be at admission level to allow the calculation of admission rates. Fields required include age in years and sex to allow standardisation of rates, lower super output area (LSOA) of residence to allow small area rates to be calculated, ethnicity, date of admission, hospital of admission and ICD-10 diagnostic codes.

Expected Benefits:

Self-harm results in over 100,000 admissions to hospital in England each year. For individuals, self-harm requiring medical attention represents mental distress and usually disorder, damage to physical health and is the strongest single risk factor for future suicide. For health care services it represents a substantial proportion of presentations for emergency care, especially among young people.

At a population level, preventing and responding to self-harm and enhancing community based support have been identified as key priorities within Public Health England’s suicide prevention strategy. Local authorities’ public health departments are tasked with drawing up local suicide prevention plans based on these priorities. Targeting of preventative interventions and support services for self-harm at a local level could be enhanced by a better understanding of where areas of increased risk are likely to be. However, statistics on service use for self-harm are not routinely available at a small area level, and the statistical techniques required to reliably interpret spatial patterns across areas with relatively low counts are complex. Furthermore, area-level factors that are known to be predictive of self-harm rates nationally, especially deprivation, have been shown to be less strongly predictive of self-harm rates within London, making them less useful as a basis for targeting services.

This project aims to validate a model to predict areas likely to have higher or lower than average rates of self-harm within Greater London. Such a model would provide benefits to local authority public health departments in informing their local suicide prevention plans and the targeting of preventative interventions. It could also help inform decision making by mental health service providers, community support organisations and commissioners in selecting the most appropriate locations for services working with individuals who self-harm. A model based on area characteristics available through publicly available data would enable such users to characterise the level of need in an area quickly and without having to set up local data collection systems or access more sensitive clinical data for an area.

As outlined under the outcomes section, the PhD student aims to submit a paper describing the development and testing of the predictive model including the use of data being applied for to a peer reviewed journal by May 2020. The project has established contacts with the public health departments local to KCL and with local community groups working in mental health who are keen to make use of data such as this in their local suicide prevention plans. Further dissemination more broadly across London public health teams and mental health services is planned between March and September 2020, with support from local contacts and by using Public Health England London Mental Health Network, to ensure these benefits are realised.

Outputs:

The proposed project forms part of a larger PhD project examining the reasons for variations in the rates of self-harm between small areas in London, and area level factors that may be associated with them. It arose from a literature review that found that the rates and predictors of self-harm in London appear to differ from those in England as a whole. The project described above aims to test the validity of a model being developed by preceding work using data from South East London on data for all of Greater London. The model will use routinely available area-level data to predict which small areas within London have above or below average rates of self-harm. The validity testing described above will result in a model that can be applied to the whole of Greater London.

Outputs from the project will include peer reviewed papers in academic journals. The project aims to submit the final paper of the PhD project, which will describe the development and testing of the predictive model including the use of data being applied for, by May 2020. Target journals for this paper are journals with a wide audience in general and public health, for example the British Medical Journal or Journal of Public Health. Any paper will be available as open-access.

The work will also be described in the applicant's PhD thesis, which will be submitted in September 2020. Conference presentations to academic, policy and practitioner audiences within public and mental health are planned between November 2019 and September 2020. Target academic conferences include the European Public Health Conference and the Society of Social Medicine. In addition, the project plans to share findings with local mental health services, which work with individuals presenting with self-harm, and with public health departments, who write local suicide and self-harm prevention plans and commission mental health services, through seminars and presentations at team meetings and more widely across London through the Public Health England London Mental Health Network between March and September 2020.

In addition, lay summaries of the research will be disseminated to a wider lay audience. This dissemination will take place in collaboration with community organisations with an interest in mental health, who the PhD student is working with during earlier work as part of the PhD project, and through the Health Inequalities Research Network (HERON) engagement events and website and through the Maudsley BRC’s engagement events and website. This work will take place throughout the PhD project, with results relating to the data requested in this proposal being disseminated between March and September 2020.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Data flows:

The data requested is pseudonymised and will not be linked to any other data. Hence there will not need to be any data provided to NHS Digital. HES APC data will be provided by NHS Digital to SLaM. It will be stored within the SLaM network and there will be no subsequent flow of data from there. No data will be received or stored by KCL and KCL will not have access to the data. Data will not be transferred to other locations and will not be made available to others within SLaM who are not working on the project described in this application. SLaM will not link the data disseminated by NHS Digital to any other data they may already hold.

The HES data being requested will be hosted by SLaM within the Maudsley BRC. Data will be downloaded from NHS Digital with an anonymous, study specific ID and no identifiable information. It will be stored on the SLaM server in an SQL server database on a storage area network and secured using an active directory user group, with access restricted to named individuals according to SLaM’s security policy. Remote access to the database is permitted, but only via a virtual private network accessed using a secure token, such that actual data processing is still carried out on site. Local downloading and printing of data is disabled when it is being accessed via VPN.

Who can access the data:

Technical assistance with data downloading and processing will be provided by staff within the Maudsley BRC with expertise in database management and information governance who are authorised to access the data for the purpose(s) described, all of whom are substantive employees of SLaM.

All other processing activities will be undertaken by the applicant only. The applicant is employed by King’s College London (KCL) and registered as a PhD student within the Department of Psychological Medicine at KCL. They also do clinical work as a psychiatrist for SLaM and has a clinical addendum to their contract with KCL which establishes an honorary contract for this work. It includes provisions to allow sharing of information regarding their performance, conduct and health between SLaM and KCL, a responsibility on the applicant to comply with all relevant NHS policies and procedures and provision for their employment with KCL to be reviewed or terminated if they are in breach of this.

Only staff that have received information governance training will be permitted access to the data.

What will be done with the data:

Analyses will be performed, and results reported at lower super output area (LSOA) level. This is a standard census geography available within the HES data and defined by NHS Digital as a non-identifiable field. Individual level data will be used to allow the standardisation of the LSOA rates calculated for age and sex, both of which are strongly associated with rates of self-harm.

Data for analyses will be extracted from the SQL database aggregated into age, sex and year strata within individual LSOAs. The data extracted will be filtered by age and individual diagnostic codes to define cohorts of interest. Similar control/comparison cohorts may also be established.
Extracted data will be imported into R, a programme for statistical analysis, from which OpenBUGS, a programme required for the planned Bayesian analyses, will be called. Analyses will be conducted at LSOA level and will involve the calculation of spatially smoothed rates of admission with and without standardisation for age and sex, and adjustment for area level exposures of interest as described in the purpose section above.

No record level data will be linked to this dataset, but it will be combined with publicly available data at LSOA level including demographic data to provide denominators for age and sex standardisation, and data relating to the exposures of interest, for example area-level deprivation, area level exposures calculated from census data and area level environmental measures such as air pollution measurements.

All outputs are aggregated with small number suppression in line with the HES Analysis Guide. The output of analyses will be descriptive tables for the cohort as a whole, estimates of standardised admission ratios for areas, estimates of the probability that area rates differ from the overall rate for the study area and estimates of the effect sizes for the association between the exposures of interest and self-harm (rate ratios). Thus all will be based on aggregate data. Descriptive statistics will be reported in line with the HES analysis guide, suppressing results if necessary due to cells having low counts. Area-level outputs will be imported into ArcMap, a geographical information system, in order to visualise the results. This will be done at area level with no individuals being identifiable from any of the reported output.

Planned analyses:

1) Indirectly 5-year-age and sex standardised rates of all-cause admission and admission for self-harm (ICD-10 codes X60-X84) will be calculated for each LSOA using Bayesian spatio-temporal disease mapping models. The distribution of rates across the Greater London area and over time will be described and compared using overall model parameters, tests for space-time interactions and by mapping rates for different time periods.
2) Sensitivity analyses will be performed for the effect of using broader definitions of likely self-harm. Standardised rates will be calculated for the standard definition of self-harm (ICD-10 Cause codes X60-X84) and broadened definitions including ‘Event of undetermined intent’ (ICD-10 cause codes Y10-Y34), and accident codes that relate to similar mechanisms of injury to those seen in self-harm (e.g. X40-X49, Accidental poisoning by and exposure to noxious substances). Standardised rates , associations with individual and area-level measures and spatial distribution of rates will be calculated and compared using the methods described in 1).
3) Areas with above and below average rates of self-harm admission, before and after adjustment for deprivation will be identified.
4) Predicted rates for the LSOAs will be modelled based on findings from previous work, using publicly available area and population level exposure data. Predicted rates will be mapped and areas predicted to have above or below average rates of self-harm admission identified.
5) Performance of the model in predicting self-harm admission rates will be checked against the clinical data. Reasons for any discrepancies between the model and the clinical data will be explored.


What will not be done with the data:
* The data will not be linked with any record level data.
* There will be no requirement nor attempt to re-identify individuals from the data.
* The data will not be made available to any third parties except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

Data required:

Only HES APC data is being requested because other datasets do not contain sufficiently accurate and complete coding of self-harm to be used for the study aims.

Data is being requested for a 10 year period from 2008-2017. This will allow trends in rates of self-harm by area over time to be examined.

Data is only being requested for individuals who were resident within the Greater London region at the time of hospital admission, as this is the study area of interest.

Data is only being requested for individuals aged 11 or older at the date of admission in order to match the age range in the data that will be used to build the model being tested. Data for younger individuals is not being used as incidents of self-harm are rare prior to adolescence.

Filters have not been applied to specific conditions in order to allow sensitivity analyses of different ways self-harm may have been coded to be carried out, for example how the inclusion of acts coded as of undetermined intent, or accidents affects the results seen and to allow comparison to be made to rates of all-cause admission.

No identifiable or sensitive data items have been requested.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).


The Mental Health and Treatment needs of UK ex-serving personnel — DARS-NIC-142790-C1J9J

Opt outs honoured: Anonymised - ICO Code Compliant, No (, Does not include the flow of confidential data, )

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2018-05-01 — 2021-04-30 2018.07 — 2018.07.

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON

Sublicensing allowed: No

Datasets:

  1. Adult Psychiatric Morbidity Survey
  2. Improving Access to Psychological Therapies Data Set

Objectives:

It is estimated that 20,000 personnel leave service every year, with King's College London (KCL) data suggesting that up to 20% of these veterans will experience a mental health problem. As of yet there has been no formal evaluation of the efficacy of generic NHS treatment outcomes for those who have served in the Armed Forces.

The aims of this project are (i) to examine the prevalence and socioeconomic determinants of mental health in veterans compared to non-veterans; (ii) to investigate whether the sociodemographic, welfare and clinical needs of veterans differ from non-veterans who access psychological treatment at Improving Access to Psychological Therapies (IAPT) services; (iii) to explore whether the psychological treatments provided are as effective among veteran compared to non-veteran service users; and (iv) to establish whether the sociodemographic, welfare and mental health characteristics of veterans who seek help through NHS IAPT services differ to veterans from a large representative UK military sample who have reported a mental health problem.

To meet these aims, KCL will analyse the following datasets:
1. Improving Access to Psychological Therapies (released 2016/2017)
2. Adult Psychiatric Morbidity Survey (released 2017)


Objectives:

The NHS Digital data will be utilised to:

a. Compare sociodemographic, welfare and clinical characteristics of veterans and non-veterans who have accessed IAPT services.

Comparisons will be made across veterans and non-veterans who access treatment at NHS IAPT services in England regarding welfare needs, diagnoses and mean scores on baseline psychological measurement tools; specifically using the Patient Health Questionnaire (PHQ9); Generalised Anxiety Disorder (GAD 7); Impact of Events Scale- Revised (IES-R) and Work and Social Adjustment Scale (WSAS). The sociodemographic characteristics (age, gender, ethnicity, marital status) of veterans and non-veterans will also be described and compared.

b. Compare pre-and post-treatment outcome measures between veterans and non-veterans.

Analyses will be carried out to examine the association between veteran status and individual diagnosis and caseness status, i.e. patients who scored above the caseness cut-off scores on the most relevant mental health outcome measures (e.g. PHQ 9, GAD 7) at baseline. The proportion of those with co-existing disorders (e.g. both PTSD and depression) will also be calculated and compared across both groups, with further analyses examining whether sample (i.e. veteran or non-veteran) predicts the total number of mental health conditions. All analyses will take account of sociodemographic differences between the two groups

Caseness status (i.e. case or non-case) will be assigned pre-and post-treatment for those who have completed two or more treatment sessions. Sociodemographic factors associated with ‘recovery’ (i.e. transition from case to non-case) will be explored. The association between veteran status and recovery will be explored taking account of sociodemographic differences between veterans and non-veterans. The impact of diagnosis and type of psychological intervention on recovery rates will also be examined.

c. Compare sociodemographic and clinical characteristics of veterans with a mental health disorder from the King's Centre for Military Health Research (KCMHR) military cohort study to veterans from the IAPT data.

This is to ascertain if those who seek help from the IAPT services are representative of veterans who i) reported a mental health need and ii) sought help in a representative UK military sample. Descriptive analyses (which will not require the datasets to be appended or linked) will compare the sociodemographic and clinical characteristics of those who are found to have a mental health problem in the KCMHR military cohort with those who sought help through IAPT services. Further analyses will be undertaken to determine if the differences across samples are significant.

Expected Benefits:

Improving mental health services for veterans:
The findings from this research will address an urgent priority for both NHS England and the Department of Health and will be of key interest to these government bodies and third sector veteran mental health services. This will be the first study to compare the mental health and treatment needs of veterans with those of civilians, seeking out any key differences. The findings from this study will help NHS England and the service deliverers who plan and provide for the mental health needs of veterans to identify effective and timely treatments to aid ex-Service personnel suffering from mental health issues in their civilian life.

Understanding the mental health problems experienced by veterans:
Little is known about whether the severity of common mental disorders differs in help-seeking veteran groups compared to non-veterans, or whether they are more likely to have PTSD symptoms or experience problems with alcohol. There is also a lack of research that compares the mental health of veterans and non-veterans while also accounting for important factors such as employment and socioeconomic status, which would provide a clearer picture of whether veterans have a ‘disadvantaged’ status.

This research aims to redress any potential disadvantages that veterans may face compared to non-veterans by identifying the characteristics associated with veterans with mental health problems who are less likely to seek treatment. Such findings would be invaluable to initiatives designed to ensure that all veterans who experience mental health problems during their civilian life are supported via the provision of appropriate mental health treatment. Ensuring that all veterans receive appropriate and prompt treatment will in turn positively affect their wellbeing and that of their families.

Informing military charities and the national veterans mental health network:
This study will be conducted at a time when there is optimal opportunity to shape the relevant services and when strong scientific evidence can most easily be translated into clinical practice and policy. KCMHR’s work is already supported by several veterans’ charities; including RBL and Combat Stress. These collaborations will provide a ready opportunity for dissemination of the findings within these and other charities. RBL and Combat Stress have partnered together and are currently working on a programme focussing on the mental health needs of service personnel and veterans. Both regularly lobby the MoD and DH.

Outputs:

All outputs will only contain data that is aggregated in line with NHS Digital guidelines.

Academic papers:
1. “The prevalence, severity and co-occurrence of mental health problems in veterans and non-veterans” (to be submitted to LancetPsych in 2018);
2. “Are generic psychological treatments effective for ex-military personal with mental health needs in the UK?” (to be submitted to BJPsych in 2018);
3. “Veterans with mental health needs: do IAPT services meet the needs of this population?” (to be submitted to LancetPsych in 2019);

Booklets for dissemination:
Booklet providing a summary of the research findings and the implications. These will be distributed to the Department of Health, Ministry of Defence, NHS England and third sector organisations (e.g. Royal British Legion or Combat Stress) through existing King's Centre for Military Health Research (KCMHR) links. [Published before the public engagement event at the end of the project.]

Stakeholder event:
KCL will hold an initial stakeholder event to share the initial findings with veterans and families (including those involved in the study) and relevant NHS services, Armed Forces charities (as well as Forces in Mind Trust) and interested NHS England and Government departments. The views of attendees will be sought to aid the interpretation of the data, in order to ensure the final report properly addresses the mental health and treatment needs of veterans.

Public seminar:
To be held at the Denmark Hill campus at KCL at the end of the project. A range of public sector professionals (e.g. from Ministry of Defence, Department of Health and NHS England) and third sector professionals (e.g. from Royal British Legion (RBL) and Combat Stress) will be invited to this event. [February 2019]

Project report for funder:
Towards the end of the project, a thorough report of KCL's findings will be compiled and passed on to the funders, the Forces in Mind Trust (FiMT). [FiMT will be updated on all project findings and dissemination by December 2018]

A project advisory group has been established. This is formed of representatives from RBL, Combat Stress and Walking with the wounded. This group will not only be briefed regularly on the findings and provide feedback to improve the study, but will also to ensure that these findings can be disseminated appropriately.

Processing:

The IAPT and APMS datasets will be received in a pseudonymised form so there will be no storage of directly identifiable data at any point. Data will be securely stored by KCL, and accessed only by authorised personnel. No data will be linked to record patient level data, nor will it be passed onto other organisations. There will be no requirement nor attempt to reidentify individuals from the data.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

Variables will be categorised where feasible to reduce any risk of identification. After initial data processing, the original dataset received from NHS Digital will be securely archived and the reformatted dataset will be used for the main analyses. Small numbers will not be reported in any publications or presentations.

In order to protect patient confidentiality in IAPT publications, any figures based on a count of less than 5 referrals must be suppressed by replacing the number with an asterisk (*).
In order to prevent suppressed numbers from being calculated through differencing other published numbers from totals, all sub-national counts must be rounded to the nearest 5.
Sub-national rates (percentages) must be rounded to the nearest whole percent to prevent disclosure. National rates must be rounded to one decimal place.

In order to protect patient confidentiality in publications resulting from analysis of APMS data users must:
- guarantee that any outputs made available to anyone other than those with whom this agreement is made, will meet required standards, including the guarantee, methods and standards contained in the Code of Practice for Official Statistics and the ONS Statistical Disclosure Control for tables produced from surveys;
- apply methods and standards specified in the Microdata Handling and Security Guide to Good Practice for disclosure control for statistical outputs.


Project 30 — DARS-NIC-15530-P7L1F

Opt outs honoured: N ()

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2017.06 — 2017.08.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Improving Access to Psychological Therapies Data Set

Objectives:

The DoH (2011) strategy document “No Health Without Mental Health” stated that “A priority action for securing improved outcomes is to achieve routine local monitoring of access to services, experience and outcome by sexual orientation”. Assessing referral, access to assessment / treatment, experience and outcomes will help to determine whether service provision is equitable and appropriate for LGB patients. Identifying specific areas of need will highlight where changes are required.

This project, conducted by King’s College London (KCL), aims to evaluate treatment access and experience for lesbian, gay and bisexual (LGB) individuals with common mental health problems in relation to Improving Access to Psychological Interventions (IAPT) services in England. The objective is to establish whether there is equitable access and experience for this minority population, and if not, to identify areas are important targets for improvement.

Expected Benefits:

Sexual minority individuals suffer excess rates of mental health problems such as anxiety and depression and are more likely to self-harm or attempt suicide (e.g. Chakraborty et al., 2011; Elliott et al., 2014; King et al., 2008). The NHS Constitution for England states that the NHS "has a wider social duty to promote equality through the services it provides and to pay particular attention to groups or sections of society where improvements in health… are not keeping pace with the rest of the population". The DoH (2011) report “No Health Without Mental Health” identified monitoring of access to services, experience and outcome by sexual orientation as a priority.

This project will undertake the evaluation of whether there is equitable access and treatment experiences for lesbian, gay and bisexual individuals in primary care psychological therapies services. This is the first such evaluation of IAPT service provision across England. If inequalities of access or treatment outcomes are identified, the authors will make recommendations about the next steps needed to help improve these health services.

The nature of the recommendations will depend on the findings – for example it is possible that particular subgroups, such as sexual minorities who are older or who are also from a minority ethnic background, have reduced access or poorer treatment outcomes. It may be that particular outreach activities to target these groups or additional staff training may be required.

The recommendations will be fed back to the National IAPT team who oversee IAPT services in England and the authors will liaise with them about how recommendations may be implemented. They will also be able to assist with dissemination to the local IAPT services. As mentioned above, the findings and recommendations will be disseminated at national conferences attended by IAPT therapists.

Outputs:

KCL plan to publish the results of this analysis in a peer-reviewed journal and disseminate to the relevant health service providers, including the HSCIC. The health services for which it will be most applicable will be Increasing Access to Psychological Therapies services in England. The paper will be published on KCL’s website, subject to any copyright / publishing restrictions by the journal.

KCL plan to present the findings at a conference relevant to the health professionals working in these healthcare services, e.g. the annual conference for the British Association of Behavioural and Cognitive Psychotherapies. It is not possible to specify an exact target date as this depends on the time taken to prepare the dataset, analyse the complex data and write up for publication.

In all cases, all outputs will be at aggregated level and small numbers will be suppressed in line with NHS Digital guidelines.

Processing:

The data will be used to investigate whether, compared to heterosexual individuals, do LGB people show similar referral levels / pathways, presenting symptoms, treatment access, patient experience and treatment outcomes. KCL aim to investigate whether there is variation depending on the intersection between sexual orientation and other characteristics (e.g. gender, ethnicity or disability, employment status, religion? A further question concerns the disclosure of sexual orientation. This is only recently being collected in IAPT services and KCL will investigate whether willingness to disclose sexual orientation varies according to factors such as age, ethnicity, gender, religion and so on.


HES data for the analysis of alcohol related frequent attenders to hospitals — DARS-NIC-44383-L6C0X

Opt outs honoured: N, Anonymised - ICO Code Compliant, No (, Does not include the flow of confidential data, )

Legal basis: Health and Social Care Act 2012, Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Other-Health and Social Care Act 2012 s261 (2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (NHS Trust, Academic)

Sensitive: Non Sensitive, and Non-Sensitive, and Sensitive

When:DSA runs 2017-02-01 — 2020-01-31 2017.03 — 2017.05.

Access method: One-Off

Data-controller type: SOUTH LONDON AND MAUDSLEY NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. HES:Civil Registration (Deaths) bridge
  4. HES-ID to MPS-ID HES Admitted Patient Care

Objectives:

The purpose of processing the data is to ascertain "The nature, natural history and characteristics of alcohol-related frequent attenders", by exploring data held within hospital episode statistics to understand this group of patients better including their health and social care needs. The project has 2 specific aims:
Aim 1: Explore in a sample of hospital attenders, which medical and socio-demographic characteristics are associated with alcohol-related frequent attendance and different patterns of health service utilisation.
Aim 2: Explore costs of health service use by Alcohol Related Frequent Attenders (ARFAs).

The two aims are explored by two separate studies outlined below.
Study 1: Natural history of ARFAs
From national Hospital Episodes Statistics (HES) 2011/12 service use pattern of a pseudonymised cohort of ARFAs during 2015/16, 2014/15, 2013/14, 2012/13, 2011/12. This will yield data on natural history of ARFAs including: co-morbidities (ICD 10 code), mode of admission, length of stay, readmissions, age, gender and geography. The researcher will compare ARFA findings to 3 other groups of patients from 2015/16-2011/12 national HES: non-alcohol-related-frequent attenders, non-alcohol-non-frequent attenders and alcohol-related-non-frequent attenders.
Data on the characteristics of frequent attenders and non-frequent attenders will be analysed using STATA SE. A logistic regression approach will be used to explore the variables derived from HES; demographics, diagnosis and attendance frequency.
The analysis of HES will produce a list of characteristics which are generic to ARFAs eg average age, average level of income deprivation etc which will be used to populate a risk stratification model initially for South London and then nationally. The risk stratification model will then be used to calculate the number of people (ARFAs) who could potentially benefit from accessing ARFA services such as 'assertive outreach' (specialist mental health services) treatment both nationally and locally

Study 2: The cost burden associated with ARFAs
Costs of health service usage by the 2015/16 ARFA cohort will be calculated per capita (on the basis of 2015/16 tariffs and occupied beddays) and compared to the costs of non-alcohol related frequent attenders. Total costs of ARFAs will be scaled up to national costs based on epidemiological results from study 1. Costs will be calculated from the health service perspective and will not explore full costs of ARFAs to society.
Sensitivity analysis- Using different assumptions and scenarios, how costs vary based on the definition of an ARFA used will be investigated ie comparing the costs to Kings Health Partners (KHP) of ARFAs with varying number of visits per year. Current literature documents multiple ARFA definitions and impact of ARFAs on health services may be important in finalising a definition going forward.

Expected Benefits:

Excess alcohol consumption is a growing public health problem, causing 5.3% of deaths worldwide in those aged under 60 years. In the UK, alcohol use is the fourth greatest risk factor for years lived with disability and is second only to tobacco as the leading preventable cause of ill health, costing the NHS £2.7 billion annually, with 78% on hospital based care.

Alcohol related hospital admissions have doubled in the last 8 years in England and reducing this burden is a key priority of government public health strategy. It is estimated that 1-2% of attendances to UK A&Es are made by ‘frequent attenders’. Studies show that ‘frequent attenders’ to A&E are also frequent users of other health and social care facilities. There has been a recent call for further research into the predictors of frequent use of healthcare services, supporting the notion that these subgroups are not adequately defined.

Alcohol related frequent attenders (ARFAs) are thought to account for 6.7% of frequent attenders. With no singularly defined way of recording and monitoring ARFA hospital admissions/attendances it is difficult to understand the true burden of ARFAs on the NHS. 21 hospitals in England run programmes for ARFAs , with no common method of identifying patients for treatment. By better understanding the characteristics of ARFAs and their patterns of usage of health services through this study, it is hoped it may become possible to identify preventative interventions to avoid further harms to their own health and prior to assimilating high costs to health services.

This study will benefit patients and the Trusts within the Kings Health Partners through the development of the risk stratification. This will ensure that ARFAs can receive the specialist treatment that they require, affording them direct health benefits in a setting that is more suited to their needs than in an A&E department, but will contribute to a reduction in hospital admissions with concomitant savings to the NHS.

Outputs:

The proposed project directly informs the design and purpose of services for ARFAs at Kings Health Partners hospitals (Guys and St Thomas', Kings College and South London and the Maudsley NHS Trusts). The analysis of HES will produce a list of characteristics (at aggregated level and will not contain data pertaining to individuals) which are generic to ARFAs eg average age, average level of income deprivation etc which will be used to populate a risk stratification model initially for South London and then nationally. The risk stratification model will then be used to calculate the number of people (ARFAs) who could potentially benefit from accessing ARFA services such as assertive outreach treatment both nationally and locally, informing commissioning of services.

This population risk stratification project is part of a wider project to optimise services for ARFAs at KHP, which includes setting up an assertive outreach services (specialist mental health services) to specifically meet the needs of ARFAs.

The project is directly supervised by 2 Professors of Addictions at the National Addictions Centre based at KCL, one of whom leads the alcohol strategy for Kings Health Partners hospitals (Guys and St Thomas', Kings College and South London and the Maudsley NHS Trusts). The alcohol strategy steering group includes lay members, service users and other researchers and clinicians working on alcohol-based projects across South London. The principal investigator reports project progress to the alcohol strategy steering group.

The principal investigator and Professor/alcohol strategy lead are also part of the ARFA clinical network for South London, which meets every 6 weeks. The group consists of practitioners and clinicians working with ARFAs so provides direct insight in to the day-to-day treatment and issues for this particular patient group. The principal investigator reports project progress to this group.

Finally, the principal investigator’s project progress is also monitored on a quarterly basis through King's College London. Project findings are due to be reported November 2018 but due to the close working arrangements with clinicians described above, will inform service design from the outset.

The outputs from all of the projects will include peer reviewed papers in academic journals which will be submitted for publication by May 2018. In addition, lay summaries such as newsletters and blogs (on behalf of the South London Academic Health Science Network and Collaboration for Leadership in Applied Health and Care will be produced (March 2017-April 2018). Conference and seminar presentations to academic, policy, professional in the fields of public health and addiction sciences and public audiences will be made between March 2017 and November 2018. All reports and presentations will be produced containing aggregate results with small numbers suppressed that show trends over time, differences across providers, commissioners, geographical areas and by patient subgroups and patient characteristics. The results will contain estimated correlations showing associations between patient outcomes and patient characteristics, hospital, institutional, geographic and environmental factors.

Information about this study and its use of data will be made available to the general public through the South London CLAHRC website. 

Outputs will contain only aggregate level data with small numbers suppressed in line with the HES analysis guide.

Processing:

The applicant will be undertaking processing activities for this project. The applicant (Consultant in public health medicine/innovation fellow) is trained in health care analytics and epidemiology and is up to date with NHS information governance training (last update June 2016).

The applicant holds an employment contract with Guy’s and St Thomas’ NHS Trust which is part of King’s Health Partners (together with King’s College Hospital NHS Trust, King's College London and South London and the Maudsley NHS Trust). As part of the Guy’s and St Thomas’ employment contract,the applicant holds a King’s Health Partners’ “research passport” to enable her to conduct research from any other of the NHS Trust sites within King’s Health Partners. The applicant will be conducting the proposed research from South London and the Maudsley (SLAM) NHS Trust site, as firstly this is where she is geographically based for work; and secondly, because SLAM currently host HES data, having the necessary IT infrastructure and ability to meet information governance requirements.

In terms of the data processing pathway:
- The inpatient HES data is downloaded from NHS Digital and stored on South London and the Maudsley NHS Trust’s server. The server is held on-site at SLAM, and access is restricted to named individuals according to SLAM’s security policy.
- Storage will be on a storage area network and secured by active directory user group.
- Remote access to the database is permitted, but only through terminal Services via secure token (so processing is still carried out on site), and with local printing and downloading disabled.
- Only staff who have signed a confidentiality agreement and have received IG training are permitted access.
- All access to individual files is recorded, and a sample audited to investigate the existence of any adverse incidents, and ensure that appropriate access has been maintained.
- The HES data is imported into STATA SE. Once held in STATA, The applicant will view the data and select a specific cohort for each individual study. Commonly a process will initially take place to define the particular cohort of interest in terms of e.g. individual diagnostic codes or procedure codes. The researchers will use routinely available filter definitions where possible, but may amend these based on the nature of each study’s group of interest. Depending on the research a similar control group may be established.
- The applicant then analyses the data, before applying the relevant disclosure controls to any output. Software used will be STATA SE; typically this will involve analysis on several outcome measures, risk adjustment and the construction of control groups.
- No record level data would be linked to this dataset, but it may be combined with publically available demographic or geographic data, for example in relation to local Trust performance
- Outputs are thus produced which consist of aggregate data (or indicator/statistical data) only with small numbers suppressed in line with the HES analysis guide.

The applicant will be the only person who will access the data. They are a substantive employee of Guys and St Thomas' which includes in the employment contract a research passport for the other sites in the Kings Health Partners. The data requested will only be used for the purposes described in this document.

South London and Maudsley NHS Foundation Trust will not link the data disseminated by NHS Digital to any other data they may already hold.


Project 32 — DARS-NIC-309328-R9V1C

Opt outs honoured: Y ()

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Non Sensitive

When:2016.04 — 2016.08.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - List Cleaning Report

Objectives:

Data will allow King’s College London (KCL) to locate patients and invite them to participate in a study called STRATA.

The patients were originally involved in a study called AESOP and were recruited into the study in 1998-1999 at one of two sites (Nottingham and South East London). AESOP recruited first episode psychosis studies to investigate the epidemiological factors relating to first episode psychosis in a cohort representative of the local population. Informed consent was taken for AESOP, and while it was not standard practice at that time to take consent for re-contact, the Section 251 approval permits KCL to contact patients who did not explicitly give consent to be contacted about future studies.

The objective of STRATA is to explore the predictors of treatment-resistant schizophrenia. Previous studies examining treatment-resistance have recruited patients with chronic schizophrenia and have therefore been biased towards more treatment-resistant patients. STRATA includes only first episode patients to minimise this bias. STRATA will therefore have proportions of treatment-resistant and treatment-responsive patients who reflect those found in the general population of schizophrenia patients. However, as it can take an average of four years to determine whether a patient is treatment-resistant, STRATA is including first episode studies where the patients have been followed up for some time.

The most recent AESOP follow up time point was 10 years. Some patients were unable to be traced and staff issues at the time meant that blood samples were not collected from all the patients who were traced. Since a key hypothesis of STRATA is that genetic factors will be able to predict which patients are resistant to antipsychotic medication and which will respond to antipsychotic, all patients included in the study must have DNA data extracted from a blood sample.

Expected Benefits:

While the use of list cleaning data will not have any immediate benefits to health and/or social care, the data obtained from patients who consent to take part in the study could lead to considerable advancements in the care of patients with schizophrenia within 5-10 years. Identifying a stratifier of treatment resistance in schizophrenia could allow clinicians to identify medication more suited to their patients, far more quickly than current clinical practice. This could save some patients many years in hospital on medication which has considerable side effects and is not the best medication strategy for them.

Outputs:

If patients, contacted using this data, consent to participate in the study they will provide a blood sample and history of their medication use. This data will be pseudonymised and combined with other data to form part of a wider analysis to examine treatment-resistant schizophrenia. Patient data will be connected to a unique ID number. This ID number will also be on patients’ consent form, which is the only place their name, address, and identifiable details will be stored.

The data from these patients will be combined with data from other patients who have taken part in in multiple first episode studies from around the world. In this final dataset, totaling approximately 3000 patients, patients will only be identified by a unique ID number (please note that this will be different to the ID number used when ex-AESOP patients are seen). STRATA will receive no identifiable patient information (names, addresses) other than date of birth.

This dataset is the combined output which will be shared with other researchers working on STRATA. It will also be combined with a separate part of STRATA, which is approved under a separate ethics application, which is recruiting patients with chronic schizophrenia for an imaging study. Combined, the imaging study results and results from the sample of 300 first episode patients who have been followed up will be used to develop a stratifier of treatment response. This stratifier will be a method (imaging, genetics, or a combination of the two) which can be used in clinical practice when a patient first presents with psychotic symptoms to determine whether they will respond to conventional antipsychotic medication or not. STRATA is planning a clinical trial, which will be pre-registered and is due to start in 2017, to test this stratifier in a clinical setting.

Other parts of STRATA are working on the socioeconomics of using such a stratifier and patient’s opinions of the acceptability of such a stratifier (the latter of which has been published; Service user's and carer's views on research towards stratified medicine in psychiatry: A qualitative study. Rose, D., Papoulias, C., MacCabe, J. & Walke, J. 28 Sep 2015 In : BMC Research Notes. 8, 1, 489).
The results produced by STRATA will be published in peer review journals (for example, Biological Psychiatry, Schizophrenia Research, etc.) and presented at conferences (for example, the Schizophrenia International Research Society Conference, the World Congress of Psychiatric Genetics, etc.)

Processing:

The details on patients who were originally recruited at the Nottingham site will be sent via secure transfer to a specified user at Nottingham University. The details on patients who were originally recruited in South London will be retained by a specific user at KCL.

Addresses or GP addresses will be used to send letters to patients. Or, if phone numbers are available, patients will be contacted by telephone using the telephone script which has been approved by the ethics committee. In all cases, the researchers will attempt to consult with the patient’s responsible clinician or care coordinator about whether the patient is well enough to be contacted. The study will be explained to the patients over the phone and they will then be given at least 24 hours to think about participating and discuss the study with family and friends.

The patients will then be seen by the specified user at either Nottingham University or KCL and the study will be explained again, informed consent will be taken, a blood sample will be taken, and the patients will be asked to fill in a few questionnaires. This informed consent includes consent for re-contact regarding any future studies and up to date contact details.

Once a patient has been seen, the information received from the HSCIC will be destroyed.
The data will not be stored, processed or be in any other way accessible to a third party. Co-investigators based at other organisations (as mentioned in the study protocol) will only have access to aggregated outputs.