NHS Digital Data Release Register - reformatted

Great Ormond Street Hospital For Children NHS Foundation Trust projects

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

Mortality Differences in Children of different Sexs' Admitted to UK Critical Care Units — DARS-NIC-188901-P9M0S

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Yes, Identifiable (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(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (NHS Trust)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-09-17 — 2023-08-16 2021.06 — 2021.12.

Access method: One-Off

Data-controller type: UNIVERSITY COLLEGE LONDON (UCL)

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care
  4. MSDS (Maternity Services Data Set)
  5. MSDS (Maternity Services Data Set) v1.5
  6. Civil Registrations of Death - Secondary Care Cut
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)
  8. Maternity Services Data Set (MSDS) v1.5

Objectives:

This research is part of a Doctoral Research Fellowship at the Population Policy and Practice programme, at the University College London (UCL) Great Ormond Street Institute of Child Health (ICH). It uses information collected from administrative sources (such as admissions to critical care, hospital episode statistics, and maternity records) to conduct research in order to understand the impact of critical illness on children.

Every year, more than 20,000 children are admitted to Paediatric Intensive Care Units (PICUs) in the UK. Previous small studies have showed that baby girls may have higher mortality rates than baby boys in PICU. In 2017, an analysis was completed of all babies (0-12 months old) who were admitted to PICUs over an 11-year period.Anonymous records from PICANet of 86,000 babies were obtained and the rates of death between girls and boys during their admission to PICU were compared. The records were anonymous as no personal identifiers (e.g. DOB, postcode) were contained in these records. The data did contain the variable ‘sex’. It was shown that girls had higher death rates than boys. This is different to what is seen in the general population where boys have higher death rates than girls for children of all ages. Careful examination were carried out of whether this difference could be due to differences in age, disease severity, infections, and a number of other factors. None of the factors could explain why girls died more than boys in PICU. The purpose of this research project now is to examine these findings in greater detail as this could have implications for the care of critically ill children generally.
The lawful basis for using information collected routinely for administrative purposes for research is the ‘public task’. This is part of the University’s commitment to integrate research and innovation for the long-term benefit of humanity. The public task basis may be found in Article 6(1)(e) of the General Data Protection Regulation, which states:
“Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller”

The processing also falls under Article 9(2)(j), which states:
“processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical Purposes”

Aims and Research Questions:

1. Why do infant girls have a higher mortality rate than infant boys in PICU?
2. Are there similar sex differentials in mortality rate at older ages for children admitted to PICUs in England?
3. After discharge from PICU, does the mortality for girls remain higher than boys?
4. Why do infant boys have a higher admission rate to PICU than infant girls?
5. Should the Paediatric Index of Mortality currently used by all PICUs in England be sex-specific?
6. Is there a better way of modelling the mortality data for PICU to get more accurate mortality estimates?
7. How should we analyse data on length of stay in PICU?
This project achieves two overall goals:
- answer a clinical question of why the mortality for females within PICU is the reverse of what is seen in the general population.
- build research capacity within the NHS and train future research leaders. Funding has been secured from NIHR and the study has been peer reviewed by the funding body.


The outcomes expected from this study are:
Primary:
- Death occurring at PICU with 7, 30 and 90 days of admission

- Death after discharge overall (any deaths occurring after discharge from PICU within 30 days of discharge, within 5 years of discharge).

Secondary:
Time to discharge from PICU (Length of Stay)

Child and infant mortality is an important indicator of child health and overall development in countries. The September 2010 United Nations Summit set the target to reduce mortality rate of children under five by two thirds. Similarly, the United Nations 2011 report titled “Sex Differentials in Childhood Mortality” investigated if recent improvements in child survival linked to the fourth millennium development goal had benefited the sexes equally, examining sex differentials in childhood mortality for 149 countries and regions from the 1970s to the first decade of the 2000s. The following link provides further insight:
(https://www.un.org/en/development/desa/population/publications/mortality/sexdifferentials.asp)
Under circumstances where boys and girls have the same access to resources such as food and medical care, boys have higher mortality rates than girls during childhood, showing that as overall childhood and infant mortality declines, the survival advantage of females over males is maintained. Thus, in developed countries, one expects (and sees) a relative survival advantage for females over males in infants, and children up to the age of five.

Although females have an overall biological advantage in childhood survival, some research suggests that the two sexes have variable immune responses to infections as mediated by sex hormones. This motivated a preliminary analysis of UK admissions due to severe infections to PICUs. The results showed greater male infant admissions to PICU over a two year period, but a greater female infant mortality over the same period, with the mortality difference not reaching statistical significance. A follow up to this analysis was carried out over a five-year period showed and similar results.

This motivated a larger study to find out if the conclusions from these preliminary analyses were also seen across all infants admitted to PICU regardless of diagnosis. In 2017 and after gaining ethical approval, UCL used data from the Paediatric Intensive Care Audit network (PICANet), which collects demographic and basic clinical data on all admissions to PICU in the UK and Ireland and analysed the entire cohort of infants admitted to all UK PICUs from January-2005 to December-2015 (final sample included over 70,000 infants within 35 PICUs). Here, UCL anaylsed all 35 PICUS, including Ireland, however, the researchers could not identify which unit the babies were from, as only an indicator was provided. The results of the survival analysis confirmed a higher hazard ratio (HR) of death for infant girls over infant boys, with strong evidence for a higher female mortality than male and this challenges conventional orthodoxy. A number of selected confounders were selected, none of which explained this HR. Thus, this study will be the first to address the questions of: what mechanisms drive the sex disparity in PICU mortality; what mechanisms drive the differential PICU admission rates for males and females, and what are the long term life trajectories and survival outcomes for children after an admission to PICU.



Data Sets Required
The datasets requested from NHS Digital are:

1) Reuse of an existing HES - civil registration cohort for children and their mothers (where mothers and children’s data are already linked using probabilistic linkage by UCL), held by UCL (DARS-NIC-393510-D6H1D), which is an existing and approved data sharing agreement also held by UCL.
2) Maternity services data set (MSDS) for the available 5 years (2015 – 2019) from NHS Digital
3) Reuse of civil Registration mortality data for children (those identified by PICANet cohort only) held by UCL (DARS-NIC-393510-D6H1D)
Section 5b (Processing Activities) clearly outlines the details of dataset linkage.
These datasets will provide the longitudinal cohort to study the course of the patients before, during and after admission to PICU. After linkage, this longitudinal cohort will provide the required data on the children admitted to PICANet; i.e. data prior to their admission and data after their discharge form PICU. Pre and post PICANet data is necessary to build a complete picture of all the factors that could be involved in the mechanisms leading to admission to PICU, discharge from PICU, and long term survival after PICU. The PICANet cohort data only provides a snapshot of what happens inside PICU and cannot offer mechanistic explanations for the disparity in sex admission rates mortality, hence the need to link it to the above datasets.
The linked data will provide a longitudinal cohort that starts before admission to PICU (mother and baby HES datasets), during admission to PICU (PICANet dataset), and follows the children up to five years post discharge from PICU (Civil Registration (deaths). There will be no requirement nor attempt to re-identify individuals from the data.

The required data is patient level data, and will be pseudonymised by NHSD before transferring to UCL’s data safe haven. Some identifiers will be retained for analysis (date of birth [DOB], date of death, city, sex, occupation, ethnicity. These have been detailed and justified in the CAG application form and have received full approval (19-CAG0164 CAG approval). DOB and Date of death will be used to calculate number of days of life as the main outcome is mortality estimated using survival analysis. Cause of death is also one of the objectives of the analysis.
Occupation as a field is required as certain occupations can lead to different health/lifestyle outcomes, which may have an impact on families and their children. For example, exposure of a mother to occupational factors during pregnancy (such as night shifts or chemicals) could contribute to our understanding of outcomes in children.

Ethnicity is one of the main factors which has shown to be of great importance in explaining differences in mortality, both in UCL’s previous analysis and in literature in general. Ethnicity will also be in five broad categories to minimise the sensitive nature of the variable.
These sensitive fields have been detailed and justified in the CAG application form and have received full approval. There is no requirement at all to re-identify any subject as a result of this analysis, thus no attempt will be made for any re-identification of subjects.
The requested number of years is the minimum to achieve the sample size required (see below in cohort details) The calculated sample size ensures that we have a precise and meaningful answers. To conduct this research without the required sample size would not offer a meaningful contribution to the body of evidence and a waste of resources. The number of years requested (2010-2019) will allow a sufficient geographical spread from the variety of PICUs involved and this means the research will be far reaching and have higher levels of generalisability.
Data Minimisation, as follows:
- restricted to 10 years only (the minimum required to achieve the calculated sample size)
- restricted to children with an admission to PICU within the study period (2010 – 2019)
- MSDS data restricted to women, of child bearing age (15 to 50 years of age), who had children during the study period (2010 – 2019). MSDS is currently only available from 2015.
- restricted geographically to England.
- postcode will not be requested, instead Lower Layer Super Output Area (LSOA) and Index of Multiple Deprivation (IMD) will be used.


Recruitment and Cohort Details

There is no active recruitment for research participants. UCL plan to create a retrospective cohort study using data from PICANet covering the periods 2010-2019 and ages 0 to <18 years. With 20,000 admissions per year over the whole of the UK (16,000 from English sites), this will give a sample of approximately 160,000 cases from English sites alone over a ten-year period. Allowing for any exclusions, a sample size of at least 140,000 is expected. All children 0 to <18 years of age who had an admission to a PICU in England between January 2010 and December 2019 are eligible for inclusion. Currently there are no plans to have any additional phases to this project. Sufficient data will be requested to ensure the research questions are answered. The sample size has also been calculated to give a meaningful answer.

Seeking consent for linkage from approximately 140,000 children admitted to PICU would not be feasible without further disclosure (a need to obtain up to date address details). Further, particularly relevant for the outcome of death within PICU, it may be deemed insensitive to contact parents of non-survivors. The outcome is a rare event and is needed to capture data on all participants to carry out meaningful analysis. Due to the long time elapsed since the outcomes of discharge from PICU or death in PICU, families may have moved away or are un-contactable, which could introduce substantial bias into analyses due to a potentially high non-response rate.


Storage/Security Assurance Details
The pseudonymised data will be released to a safe haven at University College London. The Data Safe Haven has been certified to the information security standard (ISO27001) and conforms to NHS Digital's Information Governance Toolkit.
Toolkit Organisation Data Service (ODS) code EE133902-SLMS.

Storage of data on the UCL Data Safe Haven, with access restricted to authorised users, who are required to have certified training in the use of the safe haven and in data governance. Authorised users require a personal PIN, a dual identification token device, and a personal password to access the safe haven. Access to the project data set will be
restricted to three members from the research team.

Standard operating procedures are followed for the destruction of data at the end of the study.

The sole data controller is UCL, with joint processors being UCL and Great Ormond Street Hospital ICH.

Role of PICANet and other collaborators

The sole data Controller will be UCL, where the data will be stored and processed in the Data Safe Haven and processed. Under this agreement, the only organisation permitted to access and process the data provided by NHS Digital is UCL.

PICANet are based at the University of Leeds and use data from the national project audit data. This audit is commissioned by the Healthcare Quality Improvement Partnership (HQIP) and University of Leeds is a data processor for the audit data. HQIP approval has been obtained for the purpose of this research (reference HQIP332). PICANet only hold the cohort of data to be linked and sent into NHS Digital, and will not have any influence over the means by which the data NHS Digital releases. PICANet have Health Research Authority Confidentiality Advisory Group (CAG) and ethical approvals granted by the Trent Medical Research Ethics Committee, reference 18/EM/0267. CAG approval in place (19CAG0164) to enable identifiable PICANet data to be released to NHS Digital for linkage with Hospital Episode Statistics data by NHS Digital. PICANet have ethics approval to collect and use patient data for the purpose of research. Collection of personally identifiable data has been approved by the Patient Information Advisory Group. .

Thus, PICANets involvement in this project will be to provide the cohort to NHS Digital and to co-supervise the PhD candidate. The supervisor is the Principle Investigator for the PICANet project (from the University of Leeds). PICANet will not have access to the final linked dataset once released to UCL from NHSD.

The PhD supervisors at Imperial NHS Trust (St Mary’s Hospital) and University of Leeds will not have access to the data at UCL and will be acting in clinical and statistical advisory roles. They will not be involved in decisions on data control or data processing.

This project is funded by the National Institute for Health Research. The funding award is a Clinical Doctoral Research Fellowship for the lead applicant.

Expected Benefits:

As a result of this research, the benefits to health and social care will include:

1. Improved patient care. This work will identify to clinicians and commissioners individuals who are at greatest risk mortality after PICU admission; this will enable follow-up practices to be tailored to patient needs, help identify potential health problems early and intervene so that patient wellbeing is maximized and NHS burden minimised. An example of tailoring practices to patients’ needs is where the research identifies the characteristics of children who have the highest risk of mortality after discharge from PICU, thus enabling practitioners and funders to target their needs. This can achieve maximum benefits for the patients and their families whilst ensuring that NHS resources are used efficiently.
For example, those individuals identified from the characteristics (such as certain aetiologies, or for example maternity illnesses during pregnancy) that lead to:
- higher risk of PICU admission, therefore either preventing admission altogether or avoiding emergency admissions which are known to have a higher risk of mortality
- Higher mortality in PICU, and focusing on interventions that are appropriate for the level of risk for each individual
- Higher mortality post discharge from PICU, therefore targeting them for appropriate care and support as explained above

2. Evaluation of treatments to identify best practice and guidance. This research project will work towards understanding the reasons for PICU admissions and in particular the higher rate of admission for males, so researchers can identify whether certain treatments are associated with an increased risk of PICU admission and disseminate this information through scientific journal articles. Critical illness of a child is a time of great anxiety for parents and families. Understanding factors that contribute to admission to PICU can help address and alleviate some of the clinical and family needs.

3. Evaluation of service provision. The research will highlight any inequalities in access to specialist critical care services, particularly in various socioeconomic areas, so that all patients have an equal chance of obtaining the best care irrespective of their personal circumstances and thereby having the best chance of treatment. The work will be written up in the form of reports to journal articles so that clinicians and commissioners can use this information in order to make any necessary changes to service delivery with the help and involvement of Paediatric Intensive Care Society (PICS) and the patient groups such as PICS families, UseMyData, and COSMIC.

As a results of the outputs, there will likely be discussions around how to improve on the current risk of mortality score, and if there should be an ongoing score thought the PICU admission to ensure better outcomes for both sexs', and to reduce the apparent inequality.
A revision of the index of mortality score will have an impact on an average of 20,000 PICU admissions per year UK wide. This means ensuring that patients are treated according to the severity of their disease not just on admission but through their PICU stay, which will result in more focused management strategies for patients.

The benefits will entirely be for patients and their families all over the UK. And if adopted externally to the UK, then further benefit to PICU patients beyond the UK may also be achieved in the future. UCL anticipate the benefits will be achieved once any management strategies have changed as a result of the available evidence from this project. Typically such changes (UK wide) will take between 3 to 5 years from availability of results to imbed and show benefit. Furthermore, to measure any benefits of this research, further mortality benchmarking can be made through the routine data collection of the PICANet project.

This research is in support of a PhD doctoral fellowship project .

Outputs:

Reports

There will be a PhD thesis to be completed and submitted to the UCL examination board by May 2022. This is in fulfilment of the lead applicant’s doctoral training. Other reports will also be prepared for dissemination to members of the public. Specifically, the groups involved with this project: Children of St Mary’s Intensive Care (COSMIC) and useMYdata. The project has a PAG (project advisory group) which are two members of the public, one of whom is a member of the national group UseMyData. Additionally, YPAG (young persons advisory group) and PCAG (parent and carer advisory group) have regular meetings and input into the project. Some dissemination has taken place via COSMIC charity (Children of St Mary’s intensive care, https://cosmiccharity.org.uk/). Members of PIC Families, who are part of PICANet will also be involved in sharing these findings (https://www.picanet.org.uk/about/people/pic-families/). Representatives from these groups will assist in the format and content reports for dissemination of these results to the correct public forums, such as ESPNIC (European Society of Neonatal and Paediatric Intensive Care) and PICs (Paediatric Intensive Care society). The results will also be shared with the NIHR who are the funding body and during any NIHR events.

UCL also aim to produce submissions to peer reviewed journals. The findings from the analyses (see research questions 1 to 7) will be published in peer-reviewed journals such as Lancet adolescent and child health, or British Medical JournalArchives of Disease in Childhood (BMJ ADC). There is also the aim to submit abstracts for presentations at conferences such as ESPNIC and ADR (administrative Data Research Conference). There will also be presentations at UCL, Imperial NHS Healthcare, Great Ormond Street Hospital and other relevant forums. Publications in peer reviewed journals will follow the thesis submission and are expected to be no later than 2024 (should there be any queries resulting from the analysis that need to be addressed).

Recommendations to inform any clinical guidelines arising out of the research will be published and disseminated to professional societies concerned with the care of children presenting with acute illness, including PICS and the Royal College of Paediatrics and Child Health. One such recommendation would be findings from the reassessment of the Paediatric Index of Mortality (PIM) score, before the end of 2023

All publications, abstracts and presentations will be in summary forms and will not have any individual-level or identifiable data. The identity of the PICUs will also be kept confidential and not published. Only summary statistics and aggregate data with small numbers supressed will be included in the outputs, in line with HES analysis guidelines.

Dissemination and communication approach

The findings of the research will be shared within the critical care community via multiple platforms:
- Scientific: this will be through PICANet and PICS, peer-reviewed journals (funding available for open access) , and other scientific platforms such as ESPNIC and PICs. Any change in practice or change in policy will be communicated via the PICs community.
- Public engagement: in addition to COSMIC and useMYdata, PICANet also engage with the public by having lay members on their PICs families’ forum. These findings will be shared and discussed within the forum where the lay members can input further onto plans for disseminations. There is ongoing PPI/E activity throughout the duration of this project and members of the public will be able to share their thoughts at any time during the project.
- Other: This project is publicised through the UCL and PICANet websites and any findings will also be communicated through these websites.

Processing:

All admissions to PICU between 01/01/2010 and 31/12/2019 will be identified through the PICANet project principal investigator. The PICU cohort will be provided to NHS Digital for further linkage.

There is HQIP approval for the use of PICANet data in place (HQIP332).

There is CAG approval in place (19CAG0164) to enable identifiable PICANet data to be released to NHS Digital for linkage with Hospital Episode Statistics and civil registrations mortality data by NHS Digital (referred to as Set A – details below).

The identifiable PICANet data needed for linkage are:
Date of birth [DOB], date of death, sex and postcode (unit level). These have been detailed and justified in the CAG application form and have received full approval (19-CAG0164 CAG approval). NHS number and postcode will be used for linkage by NHS Digital, but not released to UCL. DOB and Date of death will be used to calculate number of days of life as the main outcome is mortality estimated using survival analysis.

Using the PICANet data identifiers, NHSD will link individuals' records from the PICU set to the already linked HES APC and Civil Registration (deaths) HESIDS records under NIC-393510 and NHSD will provide the HESID (via a bridge file) to enable UCL to link the PICANet data to their existing HES cohort. This will form pseudonymised set A. NIC-393510 already contains linked children and mothers and the PICANet set will identify a subset of NIC-393510.

The PICU cohort will also be linked to the mothers’ data of the individuals within PICANet. NHSD will identify the Maternity Services Data Set (MSDS) from 01/01/2015 to 31/12/2019 and link the MSDS to HES and civil registrations mortality (mortality for children only, not mothers) and transfer the linked, pseudonymised MSDS data plus a link key so that UCL can link MSDS with their existing HES cohort. MSDS is only available from 2015. This will form set B.

Set A (relating to PICANet individuals HES and civil registration mortality) and Set B (relating to PICANet individual’s mothers HES and MSDS data) will be housed at the data safe haven at UCL, where these data will be merged with the already linked HES/Civil Registration extract held under NIC-393510. This forms set C.

Data Flows
To generate set A:
1. NHSD receive PICANet identifiers (identifiable data)
2. NHSD match the PICANet cohort to existing HES APC and civil registrations mortality (HES: Civil Registration Bridge held under NIC-393510),
3. NHSD flow back ‘set A’ which is PICANet study ID, linked to HESID of NIC-393510, (HES: Civil Registration)
4. UCL will merge the PICANet-HESID linkage key from step 3, with the HES data held by UCL under NIC-393510, to identify data for the children in the PICANet cohort that are already held by UCL (pseudonymised data, plus a number of CAG agreed variables: sex, DOB, date of death, occupation of the mothers).

To generate set B:
1. NHSD receive PICANet identifiers (identifiable data).
2. NHSD use NHS number to link mothers in MSDS to the children in PICANet.
3. For mothers in MSDS from step 2, NHSD add the HESID from NIC-393510.
4. NHSD produce set B, which is PICANet children (from step 1) linked with MSDS mothers (from step 2) and mother’s HESID from NIC-393510 (step 3)
5. NHSD flow back everything in step 4 above plus the data held in MSDS which is linked to PICANet (pseudonymised data, plus a number of CAG agreed variables: sex, DOB, date of death, occupation)

To generate the final dataset; set C
1. Set C will be generated at UCL
2. HESID from the pseudonymised NIC-393510 is the key to generating set C
3. The NIC-393510 HES data extract already contains details for the mothers and children from the PICANet Cohort . In NIC-393510 mothers and children have already been linked using probabilistic linkage.
4. UCL have permission to use data from NIC-393510.
5. UCL will merge set A to the data held by UCL using HESID NIC-393510. This will use just the relevant subset of NIC-393510 that match PICANet children.
6. UCL will use HESID NIC-393510 to merge set B to step 4 above.
7. UCL will obtain PICANet data from HQIP and merge with step 5 using study ID number.

Set C will be a longitudinal cohort following children from pre-birth (to account for parental factors), through to PICU admission, and up to five year post discharge. This will allow UCL to study the reasons for different admission rates for males and females, and the survival trajectory of children after discharge from PICU.

There will be no requirement nor attempt to re-identify individuals from the data at any of the above stages of data flow and linkage.

The data analysis will be primarily done by the lead applicant currently registered as a PhD student at UCL and has a substantive contract with Great Ormond Street Hospital. Thus, GOSH have been named as a processor to incorporate this arrangement. The Primary supervisor and secondary supervisors who are substantive employees of UCL will have access to the data. The data will only primarily be accessed by these people, but other members of the research team who are also substantive employees of UCL can also access the data. All UCL staff have undertaken training on Information Governance both at UCL and the NHS, and training on GDPR.

PICANet’s involvement in this project will be to provide the cohort to NHS Digital and to co-supervise the PhD candidate. The supervisor is the Principle Investigator for the PICANet project (from the University of Leeds). PICANet will not have access to the final linked dataset once released to UCL from NHSD.

The PhD supervisors at Imperial NHS Trust (St Mary’s Hospital) and University of Leeds will not have access to the data at UCL and will be acting in clinical and statistical advisory roles. They will not be involved in decisions on data control or data processing.

Storage of data on the UCL Data Safe Haven, with access restricted to authorised users, who are required to have certified training in the use of the safe haven and in data governance. Authorised users require a personal PIN, a dual identification token device, and a personal password to access the safe haven. Access to the project data set will be restricted to only members from the research team.

Using National Congenital Heart Diseases Audit data to explore the impact of non-medical risk factors on late post-operative outcomes for children with complex congenital heart defects. — DARS-NIC-219359-T5B0V

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Yes, Identifiable (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), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (NHS Trust)

Sensitive: Sensitive

When:DSA runs 2020-05-28 — 2023-05-27 2020.11 — 2020.11.

Access method: One-Off

Data-controller type: UNIVERSITY COLLEGE LONDON (UCL)

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. Civil Registrations of Death - Secondary Care Cut

Objectives:

University College London (UCL) requires pseudonymised data of life status and age at life status for use in a new study that uses National Congenital Heart Diseases Audit (NCHDA) data, to explore the impact of nonmedical risk factors on late, post-operative outcomes for children with complex congenital heart defects. This research is referred to as the Long Term Outcome (LTO) project.

UCL are the sole data controller who also process the data.

Operative mortality for paediatric cardiac surgery represents the predominant outcome measure for service evaluations and registry based research. This is now very low (2.5%) in the UK despite an increasingly large and complex congenital heart disease (CHD) population, which undermines its relevance as an outcome measure. Late mortalities occur in CHD, particularly during infancy and in complex conditions that require a series of operations and life-long multi-disciplinary care. However, these later events such as deaths and unplanned re operations are not currently analysed and reported given there is focus on early 30-day mortality rates post-operations. This situation needs to change and move forwards.

Population based studies of longer-term CHD outcomes are scarce and single centre or historic data lack relevance given the rapid evolution's in management. Apart from pilot work undertaken by the research group, there are no recent population-based analyses of longer-term outcome for complex CHDs from the UK.

Using routinely collected National Congenital Heart Diseases Audit (NCHDA) data representing procedures undertaken in the last 18 years, the proposed research will characterise longer-term outcome, in terms of survival and re-interventions, for selected individual complex CHDs.

For individual, complex CHDs, the research will then use survival models to explore the relationship between the longer-term outcomes of survival and unintended re-operations, and key non-medical risk factors of ethnic group and socio-economic deprivation, as well as the key service delivery factors of centre case volume and access to antenatal diagnosis. A greater understanding of these issues is required in order to leverage future care improvements for this growing population of children and young people with complex health needs.

The proposed research will use survival models to explore whether children from minority communities or deprived backgrounds experience worse outcomes than other children. This is important to understand since both children from a South Asian background and those living in addresses represented by the most deprived quintile are over represented amongst congenital heart patients. Further, the research intends to explore whether service provision in terms of antenatal diagnosis and case volume within children’s specialist cardiac centres (hospitals) are linked to improvements in these specified outcomes for complex congenital heart conditions.

The activity is compliant with the principles of General Data Protection Regulations (GDPR). Based on guidance, as this is for University research, the lawful basis for processing data is GDPR article 6(1)(e): Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller, also referred to as Public Task. 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 GDPR article 9(2)(j), which details that processing is necessary for scientific and research purposes, subject to appropriate safeguards.

At the time of planning this research study and applying for ethical and CAG approval, it was estimated that there would be around 120,000 records of procedures involved in the study. As analysis of the NCHDA data has commenced related to procedures that meet the inclusion criteria, it has been ascertained that the total number is 155,281 records corresponding to procedures between 1 April 2000 and 31 March, 2018, and these procedures are recorded for 102,056 individual patients. These figures might change slightly over the course of the analyses, as a small number could be of poor data quality and cannot be used.

To minimise data use, included will be patients who have had at least one intervention for congenital heart disease that has generated at least one entry in NCHDA after a first appearance in the dataset after the year 2000, with final data capture in 2018 according to UCL's agreement held with the Health Quality Improvement Partnership (HQIP) for the NCHDA dataset (the most recent data available). The year 2000 is the first year in which capture of interventions was reliably undertaken by NCHDA (as known from previous research on data quality and capture). Therefore, the study will capture interventions and outcomes between infancy with a maximum span of up to 18 years of age. Although limited to capturing interventions and outcomes for patients when they are babies, children and young people, this still goes much further than any previous studies and provides much more insight than what is offered at present which is up to 30 days post operation. National data is required to enable a population-based analysis that will be more generalised to future patients in any of the UK's heart centres.

The study research dataset will be generated by linking pseudonymised NCHDA data (English and Welsh centres) to the Death registrations (Civil Registration, Deaths). UCL has received authorisation from HQIP to transfer personal identifiers (from patients of English and Welsh centres) from NICOR (which collects the NCHDA dataset) to NHS Digital. UCL has received authorisation from HQIP to receive the pseudonymised clinical information at University College London, from NHS Digital. UCL has Ethics (18/LO/1688) and CAG (18/CAG/0184) approval for the study to process the data and to link the datasets.

The final pseudonymised dataset containing record level clinical data from NCHDA and life status information from NHS Digital will be stored within UCLs secure data safe haven.

Receiving the data about civil registration deaths is vital for this study, providing insight about which patients have died later on after they were discharged home following an operation. This unfortunately can happen, and it will not be possible to work out accurate survival figures for the different types of complex CHD without taking these later deaths into account.

The LTO study was instigated and is led by the Principal Investigator based at the Institute of Cardiovascular Science at UCL and co investigators at the Clinical Operational Research Unit (CORU) at UCL. University College London will be the only organisation to require access to the record level data supplied from NHS Digital.

The principle investigator of the study is an employee of Great Ormond Street Hospital (GOSH) and holds an honorary contract with UCL as associate professor: they will be working on this study entirely within their UCL role.

This is a standalone study funded by the British Heart Foundation and this study commenced in July 2019. The sole funder, The British Heart Foundation, are involved in the study only to provide the award, as grant-funding. They will also oversee progress of the project through annual reports and award meetings. The British Heart Foundation have no ability to suppress any of the study findings or the outputs produced. They are not permitted to access any record level NHS Digital data.

Expected Benefits:

The goal of the proposed research is to use information collected about every heart operation undertaken in the UK in the form of national audit data. This will help to better understand what happens over childhood, in terms of longer-term survival and operations that were not part of the planned treatment pathway, for babies born with specific complex heart conditions. This represents a novel use of the procedure based on national audit dataset, and represents a complex undertaking since records will need to be linked together and patient trajectories mapped out over time based on individual diagnostic and surgical codes.

The proposed research will use survival models to explore whether children from minority communities or deprived backgrounds experience worse outcomes than other children. This is important to understand since both children from a South Asian background and those living in addresses represented by the most deprived quintile are over represented amongst congenital heart patients. Further, the research intends to explore whether service provision in terms of antenatal diagnosis and case volume within children’s specialist cardiac centres (hospitals) are linked to improvements in these specified outcomes for complex congenital heart conditions.

The information generated will be of value to a range of stakeholders including most importantly the parents of children born with complex heart disease who make decisions for their child, since it will form the basis of accurate data driven information about meaningful and important clinical outcomes over childhood. UCL are already working with the main user group for parents of children with complex CHD and have a plan in place to work with them to use the study findings to generate parent information leaflets. These would be read and used by parents who are expecting a baby with CHD who want information about the condition, by parents of babies and children who are born with CHD and also they might be used by clinicians undertaking consultations. These data are not yet available and they are very much needed.

The findings of the research, in terms of any emerging links between ethnic origin, deprivation, and service provision factors of antenatal diagnosis and centre case volume, could help hospitals to organise their services so as to provide better treatment for patients. For example, if it were found that children from a particular ethnic group had a greater chance of experiencing late mortality after discharge to home, this might mean these children need extra surveillance and checks on their wellbeing. Or, if it were found that hospitals that treated very few patients with complex CHD had worse survival rates than hospitals that treated larger numbers of patients with complex CHD this knowledge might help NHS England to review where they recommend children are treated. Such longer-term data are currently lacking from service reviews despite being widely sought, and one reason for this is that the analyses required are complex and to date have not been undertaken.

Outputs:

The results of the study will be disseminated extensively. The research team has strong links with the Congenital Heart Services Clinical Reference Group, The National Audit, NHS England and clinical bodies including the British Congenital Cardiac Association, the Society for Cardiothoracic Surgery and the Royal College of Surgeons of Edinburgh. Given that UCL already hold strong links with these organisations, and have worked with them before to introduce methods of monitoring and auditing clinical practice, it is expected that this will help UCL to put into practice any learning that comes from the current study. For example, UCL hope it will be possible to introduce new ways to monitor the rates of unplanned reoperations using the current project’s work. If rates of unplanned reoperations are monitored in future within reports issued each year by the National Audit, this might help clinical practice to improve. It is anticipated that the results of this research will be in use by the National Audit, the Clinical Reference Group and the NHS by Summer 2022, the end of the project.

UCL also have strong links with CHD charities including The Children’s Heart Federation, The British Heart Foundation (the funder of the project) and Little Hearts Matter (a patient user organisation which supports parents of children with complex CHD). The project team is already in contact with Little Hearts Matter, working together to find ways to present the study outputs in the most accessible format for parents of children with CHD: the patient user organisation Little Hearts Matter would like to use the results of this study for children with single ventricle disease for the patient information leaflets that they are preparing for Summer 2020. These leaflets would be read and used by parents who are expecting a baby with CHD who want information about the condition, by parents of babies and children who are born with CHD and also they might be used by clinicians undertaking consultations. These data are not yet available and they are very much needed. The British Heart Foundation expects annual progress updates to be submitted each spring 2020 to 2022.


Outputs will involve between five to ten publications in peer-reviewed Medical and Scientific Journals by Summer 2022, as well as oral and written presentations at national and international conferences such as the British Congenital Cardiac Association annual conference and the American Heart Association Conference in 2021 and 2022. Target journals for the papers are Circulation, Heart, The Annals of Thoracic Surgery, and Archives of Disease in Childhood. The final outputs will only contain aggregate results with small number suppression, in line with the HES Analysis Guidelines.

The project team will disseminate to key stakeholders including national audit bodies, the Care Quality Commission, HQIP, commissioners and local hospitals through meetings and short briefing documents. UCL will disseminate via social media (Twitter @UCL_CORU) and blogs. UCL will ensure that lay summaries are provided (reviewed in collaboration with patients and parents on their Advisory Committee). The patients and parents on the advisory committee attend annual advisory group meetings will receive updates and can provide feedback on any aspect of the study.

Processing:

The Long-Term Outcome project has the necessary research ethics and section 251 approvals. A favourable opinion has been obtained from a Research Ethics Committee, reference number (18/LO/1688) . Section 251 support has been received to ensure that the accessing, linking and processing of the datasets is in line with the common law duty of confidence (Ref:18/CAG/0184). Data will not be handled by any additional third party organisations. Data will not be accessed outside England and Wales.

Patient identifiers, as approved by the Confidentiality Advisory Group (CAG), will be sent to NHS Digital from the NCHDA database ( NHS number, hospital ID, date of birth, ethnicity and postcode). UCL are requesting that NHS Digital match the identifiers from the NCHDA dataset to Civil Registration Deaths and extract the requested fields. NCHDA will provide a record level LTO ID which should be transferred to each pseudonymised Civil Registration Deaths record that matches. UCL are requesting that NHS Digital includes the study patient’s age at death where any patient has died. For cohort patients that are alive, UCL are requesting that NHS Digital lists these as ‘alive’, and records the study patient’s age at the time of verifying their life status as alive.

The reason that age at life status (whether living or deceased) is required is to fulfil the main objective of assessing long-term survival in children who were born with complex heart disease. To assess long-term survival, the method of analysis employed is called survival analysis. To undertake this type of analysis, for statistical reasons, an age is needed at last known status for patients who are alive, as well as the age for deceased patients. Both sets of ages are inputted for analysis. All of the survival times, considering both deceased and living children are used to make estimates of overall survival within a group, for example, a group of children with the same heart conditions. The survival analysis cannot be done without both living and deceased children’s data, based on inaccuracies and biases.

UCL are requesting age at life status (alive/deceased) to four decimal places for statistical accuracy and consistent. However, it is integral to note that UCL will not be receiving the dates that NHS Digital ran the extract for life status (for those alive and deceased) or date of death (for those deceased), so that date of birth cannot be calculated.

The data is to be securely transferred with the record level study numbers to University College London.

The planned data flows are as follows:
1) Data flows to NHS Digital
National Institute for Cardiovascular Outcomes Research (NICOR) will securely transfer a file to the NHS Digital. This file will contain patient identifiable information as shown on the section 251 support (NHS Number, postcode, date of birth, local hospital patient ID) for all patients in the study cohort from National Congenital Heart Disease Audit (NCHDA), and unique study ID (NCHDA record-level LTO Study ID).
2) NHS Digital will identify common records between NCHDA data and Civil Registration Deaths data, including the requested derived fields.
3) The linkage strategy is that NICOR will provide the personal identifiers NHS number, hospital number, date of birth and postcode to NHS Digital, from the NCHDA data. NHS Digital will identify in their dataset which records pertain to those CHD individuals and return to UCL the requested data they hold on the matched individuals (UCL will not receive data for patients that do not match), pseudonymised with the LTO ID record level ID (which also is held by NICOR and the research team).
4) Data flows from NHS Digital. Civil Registration Deaths derived fields for all individuals in the NCHDA cohort will be returned to University College London. The unique study ID (LTO record level study number) will be appended to the end of every record.

The research team will only receive the pseudonymised clinical data of the NCHDA dataset with the LTO ID and pseudonymised life status from NHS Digital not will not receive any personal identifiers. UCL will use the record level LTO study ID in case of any queries about specific records with NHS Digital.

The data is stored and processed within the UCL Identifiable Data Handling Solution (IDHS) called the Data Safe Haven (DSH). The data will be held within a secure environment where all statistical analyses will be undertaken. Access to this record level data will be limited to only specific members of the LTO team, who are substantive employees at UCL and the Principal Investigator (PI) who is a permanent associate professor of UCL, holding an honorary contract, and an employee of Great Ormond Street Hospital, and will be working on this study entirely within their UCL role. Staff accessing the UCL data safe haven attend training in its use and security procedures. Staff are also required to complete mandatory annual Information Governance and GDPR training. Each study working on the data safe haven has what is known as its own share where the study specific data is kept. Access to this share is granted only by the UCL data share owner who is a substantive employee of UCL, and who requests access for each user. Any team member leaving the study has their access revoked. The storage location is not in any physical location: the storage location is a cloud based secure data haven that is run following strict guidelines and access is only possible for approved authorised users who can access using three separate security checks.

Re-identification is not permitted under this data sharing agreement. Any linkage that could identify an individual is not permitted under this agreement. No linkage, other than that described within the agreement is permitted and no further data linkage will be undertaken.

As is common in many studies now, there are a number of collaborators providing an advisory role. Only UCL substantive employees and the PI work with the data. The organisations involved given that study advisors are their employees are Royal Brompton NHS Foundation Trust, Great Ormond Street Hospital NHS Trust, Leeds Teaching Hospitals NHS Foundation Trust, University of Southampton NHS Hospital Trust. These organisations / advisors will not have access to the data. UCL researchers make all the final decisions as data controllers. The remit of these organisations is that they employ clinicians: these clinicians are experts in congenital heart disease (surgeons and cardiologists) and they will provide clinical advice about operative treatments of congenital heart disease such as descriptions of best practice or descriptions of unplanned re-operations. These clinicians will have no control or influence on the means by which the data are being processed. Specifically, they will not have access to or see any of the data involved in the study.

The requested Civil Registration Deaths derived fields of life status, age at life status to four decimal places and place of occurrence of death (home/hospice/hospital/care home/other communal establishment/elsewhere), are vital to complete the patient trajectories.

Methods of analysis for the study will include:
1. Data cleaning and descriptive analysis of the dataset. This is required in order to detect any records that are unusable due to major errors.
2. Develop and update clinical coding maps. Coding maps are used to identify patients who have the various types of complex CHD and also to ascertain what types of heart operation patients have had.
3. Establish and examine variations in longitudinal patient outcomes. Survival rates will be worked out for the different important complex CHD along with unplanned re operations within different subtypes of complex CHD.
4. Explore non-medical risk factors for adverse outcomes including deprivation, ethnicity and centre volume. This is needed to find out whether children who are less well off or are from certain ethnic minority communities do worse than others. It also helps to explore whether getting a defect diagnosed before birth or whether being treated at a hospital that cares for larger numbers of similar types of patient helps children do better.

The results of all analyses will be published in aggregate form, with small numbers suppressed in line with HES analysis guidelines.

No identifiable data will be held by University College London as no identifiable data will be released by NHS Digital.

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).

All outputs produced will have small numbers suppressed inline with the HES Analysis guide.