NHS Digital Data Release Register - reformatted

Swansea University projects

• Predictive Risk Stratification Models: Assessment of Implementation Consequences (PRISMATIC 2)
• TRIM: What Triage Model Is Safest & Most Effective For The Management Of 999 Callers With Suspected COVID-19? A Linked Outcome Study
• NIHR HS&DR 18/03/02 STRETCHED (Snooks)
• GPs-in-EDs (Phase 2) NIHR HS&DR 15/145/04

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

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Predictive Risk Stratification Models: Assessment of Implementation Consequences (PRISMATIC 2) — DARS-NIC-681645-M2G8X

Type of data: information not disclosed for TRE projects

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(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-08-09 — 2027-08-08 2024.09 — 2024.09.

Access method: One-Off

Data-controller type: SWANSEA UNIVERSITY

Sublicensing allowed: No

Datasets:

1. Civil Registrations of Death - Secondary Care Cut
2. Emergency Care Data Set (ECDS)
3. Hospital Episode Statistics Accident and Emergency (HES A and E)
4. Hospital Episode Statistics Admitted Patient Care (HES APC)
5. Hospital Episode Statistics Critical Care (HES Critical Care)

Objectives:

Swansea University requires access to NHS England data for the purpose of the following research project:
Predictive Risk Stratification Models: Assessment of Implementation Consequences (PRISMATIC 2)

The following is a summary of the aims of the research project provided by Swansea University:

PRISMATIC 2 aims to determine the effects of the introduction of Emergency Admission Risk Stratification (EARS) tools across all patients and in subgroups including those with Ambulatory Care Sensitive (ACS) conditions (conditions where effective community care and person-centred care can help prevent the need for hospital admission) on:
• Emergency admissions
• Emergency Department (ED) attendances
• Admissions to Intensive Care Units (ICU)
• Time spent in hospital (bed days) and ICU
• Deaths
• NHS costs

PRISMATIC 2 is a stand-alone research project that consists of 4 separate work packages. The data requested in this Agreement concerns Work package 1 only.

The PRISMATIC 2 Work packages are described below:

> WP1: Pseudonymised routine linked data analysis - Using routine data sources (HES supplemented by ONS & ECDS, via NHS England), Swansea University will analyse routine anonymised data on emergency admissions, ED attendances and days spent in hospital and in ICU at study site (CCG) level between 2010 and 2021, linked to the dates of introduction of predictive risk stratification

> WP2: Investigation of mechanisms of change using routine anonymised primary care data - effects on thresholds for emergency admission decisions and case mix by examining characteristics (demographic and clinical) will be explored, and, in particular, severity of condition of patients admitted before and after introduction of the software, across the population and in subgroups

> WP3: Semi-structured interviews with practitioners - Swansea University will undertake qualitative work at 8 practices, selected from the original sample of 16, to investigate whether practitioners perceive that primary care clinicians’ attitudes to risk and/or decision-making behaviour changed with introduction of predictive risk software.

> WP4: Focus groups and interviews with patients - Swansea University will undertake qualitative work with patients (n=32), split between focus groups and interviews, to explore how they perceive that communication of individual risk scores might affect their experiences and health seeking behaviours.

The following NHS England Data will be accessed:
> Hospital Episode Statistics (HES)
- Admitted Patient Care (APC) – necessary to assess trends in emergency admissions pre vs post EARS implementation by obtaining data on admissions, diagnoses, as well as treatments and investigations (linked to the severity of cases).
- Accident & Emergency (A&E) and Emergency Care Data Set (ECDS) – necessary to assess trends in A&E attendances pre vs post EARS implementation. A&E attendance data will facilitate the study evaluation to whether the implementation of EARS tools was associated with intended or unintended changes in emergency department utilisation across England.
- Critical Care (CC) - necessary to assess trends in admissions to intensive care units and length of ICU stay pre vs post EARS implementation, which are important study outcomes related to the severity of illness.
> Civil Registration Mortality – necessary to assess trends in deaths pre vs post EARS implementation, which is an important study outcome, given that EARS tools aimed to reduce risk of adverse events such as mortality.

The level of the Data will be:
> Pseudonymised

The Data will be minimised as follows:
> Limited to data between 2009/10 and 2020/21; this data period is required as it covers the period in which software tools were introduced across some CCGs in England (~2012/13 – 2016/17; varies across regions), plus three years before and four years after their implementation. This is to allow Swansea University to study the trends in data before and after the intervention was introduced.
> Data required on the whole of England. By analysing data for the whole of England, the large number of former Clinical Commissioning Group (CCG) areas that implemented EARS tools at different times will provide greater statistical power for the Multiple Interrupted Time Series (MITS) analysis. Analysing data for the whole of England facilitates evaluation to whether the effects observed in their previous single-site PRISMATIC trial (conducted in South Wales) are replicated more broadly across England over a longer follow-up period.

Swansea University is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
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;

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - 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.

Emergency admissions and acute healthcare utilisation place a significant burden on the NHS and have major cost implications. Assessing interventions aimed at reducing unnecessary emergency admissions, such as EARS tools, is in the public interest as it can inform more efficient and effective use of limited NHS resources. The findings from this study, concerning the impacts of implementing EARS tools across England, is expected to provide much needed evidence to inform future policy decisions by NHS England. Additionally, the study findings could be used to inform policy and practice regarding the continued use or refinement of EARS tools across the UK.

The funding is provided by the National Institute for Health Research (NIHR). The funding is specifically for the project described.

The funder(s) will have no ability to suppress or otherwise limit the publication of findings.

Swansea University are strongly committed to the involvement of patients and the public in PRISMATIC 2. The UK Standards for Public Involvement will be followed throughout the study. Patient/public contributors and study co-applicants were substantively involved in the development of the study design and two risk stratification focus groups were held with members of the SUPER (Service Users for Primary and Emergency care Research) group and the SAIL (Secure Anonymised Information Linkage) Consumer panel.

Expected Benefits:

The findings of this research study should give policy-makers, healthcare professionals, patients and carers, a better understanding of the effects and costs related to the introduction of emergency admission risk stratification (EARS) tools in England. The use of the requested NHS England Data will:
• enable assessing the effects of the introduction of EARS tools across all patients and in subgroups (including those with Ambulatory Care Sensitive conditions) on: emergency admissions, Emergency Department attendances, admissions to Intensive Care Units (ICU), time spent in hospital (bed days) and ICU, deaths and NHS costs;
• advance understanding of the effectiveness of using preventive care measures such as the implementation of risk stratification tools and provide evidence about the processes and outcomes of their use;
• inform decision making on future policy decisions.

The use of the data could:
> help the system to better understand the health and care needs of populations.
> advance understanding of regional and national trends in health and social care needs.
> advance understanding of the need for, or effectiveness of, preventative health and care measures for particular populations or conditions such as obesity and diabetes.
> inform planning health services and programmes, for example to improve equity of access, experience and outcomes.
> inform decisions on how to effectively allocate and evaluate funding according to health needs.
> provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.
> support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

From the patients' perspective, it is important to reduce emergency admissions to hospital. Emergency admissions are generally unwelcome to the patient; they can be associated with adverse outcomes including death, frailty and difficulties regaining independence; and are challenging to manage in terms of quality and safety (e.g. exposure to hospital acquired infections). Although predictive risk stratification has been advocated as one tool to help support reductions, its impact and worth as a policy option remains unclear. This research study will investigate effects (including those unexpected and unintended), on emergency admissions to hospital, Emergency Department attendances and days spent in hospital, associated with the introduction of predictive risk stratification software.

Through publication of findings, including peer-reviewed journal articles and health service research and policy events, this research is expected to provide policy-makers with the evidence needed to inform future policy decisions on the use of predictive risk stratification tools in primary care.

Outputs:

The expected outputs of the processing will be:
> Submissions to peer reviewed journals, specifically the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research (HS&DR) journal
> Briefing papers
> Presentations at relevant conferences (e.g. Society for Academic Primary Care, Royal College of General Practitioners, British Journal of General Practice, Health Services Research UK)
> A public facing lay summary of findings
> A logic model describing the intended and unintended effects of predictive risk stratification tools, the mechanisms by which these effects might be achieved, and the inputs (context and resources) which lead to these effects
> Two dissemination workshops: one aimed at policy and practice stakeholders, and a second aimed at public/patient stakeholders, in partnership with the SUPER PPI group and the Patients and Public Participation Groups (PPGs) Network
> A publication and dissemination plan will be developed within the Research Management Group, including the assessment of stakeholder needs and communication activities and milestones, and results will be actively published throughout the research funding period. The plan seeks to maximise stakeholder interest and understanding of the study and outputs. This plan will inform ongoing engagement with patients, clinicians, managers, commissioners and policy makers, using appropriate communication messages and platforms. PPI collaborators will be worked with to ensure patient-focused materials are widely understood

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived

Outputs are expected to be produced within 12 months of data receipt.

Processing:

No data will flow to NHS England for the purposes of this Data Sharing Agreement (DSA).

NHS England will provide the relevant records from the HES, ECDS and mortality datasets to Swansea University. The Data will
> contain no direct identifying data items. The Data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

The Data will not be transferred to any other location.

The Data will be stored on the UK Secure e-Research Platform (UK SeRP), a Trusted Research Environment (TRE), at Swansea University. The Data will be stored in isolation from other datasets held by UK SeRP, as per UK SeRP policy.

The Data will be accessed by authorised personnel via remote access.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:

- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Remote processing will be from secure locations within England and Wales. The data will not leave England or Wales at any time.

Access is restricted to employees of Swansea University who have authorisation from the Chief Investigator.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will not be linked with any other data.

There will be no requirement and no attempt to reidentify individuals when using the Data.

Researchers from Swansea University will analyse the Data for the purposes described above.

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TRIM: What Triage Model Is Safest & Most Effective For The Management Of 999 Callers With Suspected COVID-19? A Linked Outcome Study — DARS-NIC-387965-T2B5D

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-06-08 — 2025-06-07 2022.07 — 2024.05.

Access method: One-Off

Data-controller type: SWANSEA UNIVERSITY

Sublicensing allowed: No

Datasets:

1. Civil Registration - Deaths
2. Emergency Care Data Set (ECDS)
3. Hospital Episode Statistics Admitted Patient Care
4. Hospital Episode Statistics Critical Care
5. Civil Registrations of Death
6. Hospital Episode Statistics Admitted Patient Care (HES APC)
7. Hospital Episode Statistics Critical Care (HES Critical Care)

Objectives:

Ambulance services cannot and should not attend and convey every patient with COVID-19 symptoms to hospital. There are two stages of triage: to decide 1) who to dispatch a response to, for face-to-face assessment and care; and 2) who to convey to hospital. This triage is key to identifying people who need to be treated in hospital. Under-triage will result in patient harm, in this case, avoidable serious illness and deaths. Over-triage will result in unnecessary conveyance to the Emergency Department, exposing patients to risk of infection, diverting resources from those in need and overburdening already pressurized services.

Different triage models are used by different ambulance services, and are changing over time as call patterns and understanding of the pandemic evolve. It is not clear which of these approaches (if any) works best, or which elements lead to a successful triage model.

TRIM (“What TRIage model is safest and most effective for the Management of 999 callers with suspected COVID-19? A linked outcome study”) will investigate these models by looking at outcomes for 999 callers in four ambulance services during the first wave of the pandemic (March to August 2020). These ambulance service areas are the East of England Ambulance Service, the East Midlands Ambulance Service, the West Midlands Ambulance Service, and the Yorkshire Ambulance Service.

TRIM is a stand-alone research project funded by the National Institute for Health Research and UK Research and Innovation joint COVID-19 rolling funding call in June 2020. It is not part of a wider or ongoing programme of work or collaboration.

The primary study outcome is the proportion of patients conveyed to hospital (i.e. those who are conveyed and then admitted). Study outcomes will also consider further 999 calls; emergency department presentations; hospital admissions; intensive care unit admissions; and mortality. All outcomes are assessed at 1 month and 3 months following the initial contact.

TRIM will look at patients admitted to hospital with suspected or confirmed COVID-19, and check whether they made a 999 call in the preceding 7 days. This will provide data on any missed opportunities and under-triage.

The research team at Swansea University hope that, by identifying which triage models were most successful, future policies and practices can be better informed during the current and future pandemic situations.

Swansea University recognise that the pandemic response has evolved since TRIM was funded in June 2020, the initial enquiry to NHS Digital in December 2020, and also since the application was submitted to NHS Digital in September 2021. However, it is still useful to review the circumstances of this unprecedented scenario, and whether there are any lessons that can be learnt. In that regard, Swansea University believe it is critical that these lessons are learnt based on recent experience, in the event of any future pandemic situations. While it is impossible to accurately assess the broader relevance of research findings until Swansea University have conducted the statistical analysis, Swansea University anticipate the evidence will still be useful in a broader sense - for example, in the context of peak 999 call times or winter pressures.

Study sites and PPI representatives remain engaged and active research partners in the TRIM study, and are keen to see the results of the work that have already been undertaken (e.g. in preparing the ambulance service data).

DATA SUMMARY

The data requested from NHS Digital includes information on mortality, hospital attendances and admissions for 3 months following the initial contact with suspected or confirmed COVID-19. This will identify which people were at greatest risk from their suspected COVID-19 infection, and therefore should have been conveyed to hospital. The data requested will also identify which patients were brought to hospital and immediately discharged, and therefore may have been safe to leave at home. This data is crucial to understand whether ambulance service triage models successfully managed this patient group. Swansea University have applied for and received Health Research Authority (HRA) Confidential Advisory Group (CAG) approval (Reference - 21/CAG/0106) under section 251 of the NHS Act 2006 as a valid legal basis to cover the linkage and flow of patient identifiable data without consent.

Pseudonymised record-level data are required. A Study ID will be used to link hospital attendance and mortality data from NHS Digital with ambulance service 999 calls and ambulance dispatch data. This will provide a complete picture of NHS contacts following the initial contact with suspected COVID-19 and therefore whether patients were under- or over-triaged.

Data obtained for TRIM through this Agreement will only be used for TRIM and will not be utilised in any other research project. This is also true for 999 call and ambulance dispatch data obtained for TRIM directly from the East of England Ambulance Service, the East Midlands Ambulance Service, the West Midlands Ambulance Service, and the Yorkshire Ambulance Service.

Swansea University are requesting access to the following datasets from NHS Digital:

Emergency Care Dataset (ECDS): Date; reason for contact (COVID/not); outcome of presentation; admission date (where applicable). This will provide data on the outcomes of patients brought to hospital by ambulance, including whether they were admitted to hospital or discharged home. Patients who were not conveyed may also present themselves to hospital. It is vital to understand the proportion of these who do, and whether they were admitted, as this is a key indicator of cases that were under-triaged.

Hospital Episode Statistics for Admitted Patient Care and Critical Care: these datasets will provide data on whether the initial contact was admitted to hospital within the follow-up periods; reason for and length of stay; and outcome of stay and discharge date. This will support the ECDS data in identifying whether patients were appropriately triaged or not.

Civil Registration (Deaths): Date of death will indicate whether any given death falls within the 1 month and 3-month follow-up period. It will also allow survival curves to be generated, showing the proportion of patients who survive for at least N days, where N is the number of days following triage, for the whole follow-up period and how this varies by study arm. Cause of death will indicate whether the death is COVID-related or not for subgroup analyses.
The Civil Registration (Deaths) product does not allow for data to be filtered to a specific time period, as requested by Swansea University. Swansea University will therefore be supplied with all mortality data relating to the cohort submitted. They will however be required to delete all data which does not fall within the specified period - 3 months after each patient’s initial contact for the period 1 March 2020 – 30 November 2020.

DATA MINIMISATION

The data requested covers the period of the first wave of the COVID-19 pandemic (March – August 2020) plus 3 months follow-up. This means the full dataset must span the period 01-March-2020 to 30-November-2020. Data outside this period are not required.

The data request is limited to the areas covered by the four participating ambulance services (East of England Ambulance Service, East Midlands Ambulance Service, West Midlands Ambulance Service, and the Yorkshire Ambulance Service). Data outside these areas are not required. A wide geographical spread is necessary to capture the richness of data on triage models used during the pandemic, and to make sure that any conclusions regarding triage models are broadly applicable to the rest of England and Wales. Although the data requested is restricted to England only, due to the similarity of the triage systems and processes employed in Wales, Swansea University expect findings to be applicable to Wales as well.

The study cohort is estimated to be around 80,000 people, however this is neither a target nor a cap – all callers who meet the above criteria will be included. It is anticipated that the number of 999 callers will be similar in each ambulance service area. It is not viable to perform this research without relying on routinely collected data. Patient level data is required to determine whether each 999 caller was appropriately conveyed to hospital or not.

Data cannot be narrowed by demographics as the coronavirus pandemic affects people of all backgrounds. Demographic factors, including age, sex, and ethnicity, are likely to be important in the triage, management, and outcomes of people with suspected COVID-19, particularly where they relate to an increased chance of death.

People will only be included in the study cohort if they called 999 and were flagged as having suspected or confirmed COVID-19, or were admitted to hospital with suspected or confirmed COVID-19. All-cause mortality data will be considered in the analysis, as well as COVID-specific mortality. Date of death is required to determine if the death fell within a 3-month follow-up period after the initial 999 call or hospital admission with suspected COVID-19.

There is no control group as this is not possible. Instead, the four ambulance services will be compared with each other to investigate which triage system gives the best outcomes for patients.

All patient episodes in the requested datasets are required to understand what happens to patients following their initial triage for suspected COVID-19. Patient outcomes may not be known for some time after the initial triage, and patient's conditions may change over time.

LEGAL BASIS FOR PROCESSING

Data are processed under GDPR Article 6 (1) (e) – task in the public interest. Correct triage models for 999 callers in an unprecedented pandemic situation is of vital interest to patients, attending practitioners, ambulance services, and the wider NHS. To this end, the study meets the conditions outlined in Schedule 1 Part 1 (4) of the Data Protection Act 2018. TRIM is led by an experienced team from Swansea University, a leading UK medical school and research institution. Swansea University is a public authority as outlined under Schedule 1 of the Freedom of Information Act 2000. Power is conferred upon Swansea University by the terms of it’s Royal Charter “to provide schemes of study by teaching and by research”.

Special categories of data are processed under GDPR Article 9 (2)(j) “…scientific or historical research purposes or statistical purposes…”. The special categories of data requested are health data, age in years, gender, ethnicity, and index of multiple deprivation decile. Any/all of these factors may be important indicators of which patients should or should not be conveyed to hospital with suspected COVID-19.

ETHICAL/MORAL CONSIDERATIONS

Ethical considerations include the use of patient data without consent. As the estimated cohort size is around eighty thousand it is not viable to seek consent from this many people in a timescale that would produce useful results (within the current pandemic). As aforementioned, Swansea University have applied for and received Health Research Authority (HRA) Confidential Advisory Group (CAG) approval (Reference - 21/CAG/0106) under section 251 of the NHS Act 2006. This provides a legal basis for Swansea University to link and flow patient identifiable data without consent. Patient objections will automatically apply to this data request.

The use of routine data is also the least intrusive and most reliable way to carry out the research. Many patients with COVID-19 died, and others may still be suffering longer-term effects. They may also be hospitalised from subsequent waves of the virus. Therefore, following up patients directly is likely to be more distressing than the use of routine data. Direct follow-up would also be subject to recall bias and large volumes of missing data.

PPI ENGAGEMENT

A Patient Advisory Panel was set up as part of this research study to offer lay insight into the research. The group comprises PPI contributors, who were recruited via advertisement. Interested individuals submitted expressions of interest to join the group. No specific experience was required although an interest in health services research was recommended. All aspects of the methodology have been discussed with the group and they are supportive of the research approach adopted, understanding that the use of routine data is a reliable way and unintrusive way to undertake the research and that it would not be possible to undertake the study using other methods. Separate Privacy Notices and Patient Notification Leaflets have been created in collaboration with the Patient Advisory Panel. The Patient Advisory Panel meets quarterly and advises the Research Management Group. Two members of the Patient Advisory Panel sit on the Research Management Group. One of these members has provided a letter (supplied to NHS Digital), confirming their involvement in the study design and ongoing support for this research approach.

DATA CONTROLLERSHIP

Swansea University is the sole research sponsor and data controller who will also process the data for the TRIM study.

A research management group consists of study co-applicants and representatives of research stakeholders. This includes members of the East of England Ambulance Service; East Midlands Ambulance Service; West Midlands Ambulance Service; Yorkshire Ambulance Service; the Welsh Ambulance Service; methodologists from the University of Stirling; Kingston University and St George’s, University of London; University of Lincoln; and public representatives.

The research management group is not a decision-making body. Members of the research team based in ambulance trusts have identified the study cohorts within the trust catchment areas and facilitated data submission to NHS Digital. They will not be involved in the analysis of the routine data but will contribute to interpretation of findings. Other members of the research team, including those based at other universities, will not be involved in the analysis of the routine data, but will contribute to interpretation of findings and assessing implications for policy and practice. In line with Health Research Authority (HRA) and Information Commissioner's Office (ICO) guidance, the research management group and their respective organisations (with the sole exception of Swansea University) are neither data controllers nor data processors with regards to this Agreement and will only be able to access aggregated outputs with small numbers suppressed in line with the HES analysis guide.

TRIM is funded by the National Institute for Health Research (NIHR) and UK Research and Innovation (UKRI) joint COVID-19 rolling funding call. Neither the NIHR nor UKRI have any involvement in study management, data analysis, or interpretation of findings. The NIHR and UKRI are neither data controllers nor data processors in regard to this Agreement.

Expected Benefits:

TRIM seeks to understand the triage of patients with suspected or confirmed COVID-19 during the first wave of the pandemic. It hopes to: produce evidence to enable comparison of the effectiveness and safety of triage models in place during the pandemic, both in the ambulance call centre and on-scene (key deliverable for this work package); provide evidence about effects on mortality, hospital and Intensive Care Unit/Intensive Therapy Unit admission and the accurate identification of serious COVID-19 infection; document implementation concerns; and inform decision making and policy guidance in future epidemics and pandemics future periods of acute high demand for ambulance services. Improvements in triage policies and protocols may help to: ensure that patients are treated in appropriate locations; reduce avoidable risk to practitioners; increase quality of care; and reduce pressure on hospitals.

If TRIM can help to identify the most successful triage system(s) for managing patients with suspected COVID-19, then this potentially allows UK ambulance services to improve the triage systems they use. Even if specific triage models cannot be replicated in every ambulance service area, it may be possible to identify common elements of successful triage models and implement them piecemeal. Given the extremely high volume of calls recorded for suspected COVID-19 during the pandemic, even a small improvement to triage systems may considerably improve overall patient outcomes.

TRIM’s PPI representatives and its Study Steering Committee believe study findings will have relevance despite the move to post-pandemic life and are keen that appropriate lessons from the pandemic are learned. More generally, improvements in triage systems are generally desirable - for example, appropriate triage may help to reduce ambulance waiting times outside hospitals, which has particular relevance given the recent Association of Ambulance Chief Executives report on ambulance queueing.

The cohort from four UK ambulance services within the first wave of the pandemic alone is estimated to be 80,000 people. A better understanding of the triage systems used, and their outcomes, could easily impact hundreds of thousands of people in the UK alone. Improving triage of this patient group may also free capacity to better help other patient groups. If study findings can be applied more widely, such as to winter flu pressures, this could lead to further and more sustained impact.

The benefits of this study hope to be felt firstly by the patients with suspected COVID-19 who are at the highest risk. It may also benefit low-risk patients, if they can be successfully managed at home, without the burden of a trip to hospital or the risks associated with that in a pandemic situation. These benefits will be equally applicable to future situations such as peak 999 call times and winter pressures. Finally, if a triage system is able successfully reduce the overall burden on the NHS during a pandemic situation, this would be to the benefit of practitioners in the ambulance service, and at receiving hospitals.

The study team hope to disseminate their findings on an on-going basis to be as timely and relevant as possible. Findings hope to be disseminated to relevant stakeholder groups – including all UK ambulance services - through executive summaries, scientific papers, and conference presentations.

Outputs:

Study outputs hope to include:

- A final study report submitted to the funder, National Institute for Health Research (NIHR). This hopes to be published online alongside the study protocol on the NIHR website (https://www.nihr.ac.uk/), researchfish (https://researchfish.com) and/or the UK Research and Innovation (UKRI) Gateway to Research (https://gtr.ukri.org/).
- Peer reviewed papers submitted to open-access scientific journals such as the BMJ Open (https://bmjopen.bmj.com/).
- Abstracts, posters, and presentations at conferences, such as the Health Services Research UK conference (https://hsruk.org/conferences), hope to be submitted on an ad hoc basis.
- Non-technical summaries and presentations hope to be distributed to the East of England Ambulance Service, the East Midlands Ambulance Service, the West Midlands Ambulance Service, and the Yorkshire Ambulance Service.

Any study outputs will be presented as aggregated figures with small numbers suppressed in line with the HES analysis guide.

Dissemination seeks to maximise stakeholder interest and understanding of the study and its outputs to maximise impact on ambulance service policy and practice. It aims to build on the research management group’s profile and reputation with previous studies focused on improving the quality of prehospital care. The research management group has and intends to continue to work with public contributors and co-applicants to develop a study communication plan. This plan aims to include an assessment of stakeholder needs and hopes to set out communication activities and milestones. It is anticipated to look to include engagement with patient and professional groups, NHS managers, commissioners, and policy makers. It is planned that plain English summaries will be produced where appropriate.

The target audience for dissemination includes policy makers, care-commissioning bodes, ambulance service providers and the general public.

The research management group hopes to use strong existing links with ambulance services directly, and through national bodies such as the National Ambulance Research Steering Group, National Ambulance Services Clinical Quality Group, the Association of Ambulance Chief Executives and National Ambulance Services Medical Directors.

Swansea University hope to disseminate key findings to front-line ambulance service staff via internal ambulance boards, service briefings and bulletins, and practitioner/professional publications.

The study communications, publications and dissemination plan may include media engagement such as written press coverage, online media, and social networking. Media/networking engagements hope to be via PRIME Centre Wales, the National Ambulance Research Steering Group (http://narsg.uk/), the 999 EMS Research Forum, HSR UK and similar online/face-to-face events/conferences, in addition to any others proposed by members of TRIM’s Patient Advisory Panel/Research Management Group/Study Steering Committee. This would be supported by the dedicated marketing team in Swansea University Medical School. In addition to the full study report, TRIM intends to produce an executive summary to disseminate through the Wales Centre for Primary and Emergency (including Unscheduled) Care Research network (http://www.primecentre.wales/#:~:text=Read%20the%20PRIME%20Centre%20Wales,research%20proposals%20and%20support%20researchers.). Researchers may present study findings at appropriate national and international events and will aim to ensure that wider learning from the study is disseminated to appropriate audiences.

TRIM does not include the development of any algorithms, tools, technologies, or similar. While TRIM seeks to identify which triage models lead to better outcomes of patients with suspected COVID-19, it does not seek to develop new triage models. Therefore, no exploitable intellectual property is anticipated. Should any be developed, the research management group will seek professional advice from the Research, Engagement, and Innovation Services at Swansea University.

Authorship of all reports, scientific papers, and other publications will be in line with a pre-specified authorship agreement. This will be prepared in line with the International Committee of Medical Journal Editors guidelines (http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html).

The research funding bodies will be acknowledged within any and all publications and presentations.

A paper comparing patient outcomes associated with each triage model is targeted for the end of 2022. The final report to the funder is also due around this time. Conference abstracts, posters and presentations may be submitted on an on-going basis as opportunities arise.

The data from NHS Digital will not be used for any other purpose other than that outlined in this Agreement.

Processing:

Data processing will only be carried out by substantive employees of Swansea University (the sole data controller) with appropriate training in data protection and confidentiality.

The cohort file to be submitted to NHS Digital for linkage is split into two: (1) ‘forwards’ cohort: linking 999 data from selected ambulance services with NHS Digital datasets for patients logged with COVID-19 symptoms; (2) ‘backwards’ cohort: linking hospital data from selected hospitals for patients who were hospitalised, admitted to Intensive Care Units / Intensive Therapy Units or died with a confirmed diagnosis of COVID-19 with 999 data to establish whether the patients called 999 prior to hospitalisation, whether they were logged with suspected COVID-19 and what the outcome of the call was.

Patients in the hospital admission sub-cohort (backwards) will be identified by clinicians in each participating hospital. Swansea University are interested in outcomes for 999 callers who were hospitalised but not conveyed, as these represent under-triage, and whether those calls were classified as suspected/confirmed COVID or not. Linked data for patients who did not call 999 are not required. The participating hospitals, and their corresponding ambulance services are: Norfolk and Norwich Hospital (linked to East of England Ambulance Service); Queen’s Medical Centre, Nottingham (linked to East Midlands Ambulance Service); Sandwell and West Birmingham Hospital (linked to West Midlands Ambulance Service); Northern General Hospital, Sheffield (NGH, linked to Yorkshire Ambulance Service (YAS)); and Sheffield Children’s Hospital (linked to YAS). The participating ambulance trusts will receive record-level, identifiable data for patients admitted with suspected COVID-19 from the corresponding hospital in their area.

Once identifiable data for these patients has been transferred to the participating ambulance trusts, a research paramedic from each trust will search the ambulance service database for any 999 calls made by those patients in the preceding 7 days. A large overlap between these two groups is anticipated. Those patients will then be added to the ambulance service cohort file for transfer to NHS Digital. This group will be used to identify sub-cohorts who were under-triaged by the ambulance service.

The 999 call sub-cohort (forwards) will be identified by research paramedics in each of the four participating ambulance trusts. This will be carried out by a search of 999 calls and patient clinical records for cases classified as suspected COVID-19, or for symptoms consistent with COVID-19.

The cohort identification file will then be imported into NHS Digital where the data will be used to identify hospital records and mortality data for the three months following the initial contact with suspected COVID-19. The study cohort file transferred from the four ambulance services contains record-level identifiable data. No other data will be transferred to NHS Digital.

Data items will include: study ID; name; NHS number; date of birth; postcode; and the date of the first such 999 call or admission within the study period. The estimated cohort size is 80,000 records.

Data disseminated by NHS Digital will be record-level pseudonymised data. It will include: study ID; demographics (age in years, gender, ethnic group, and English index of multiple deprivation decile); the date, reason for, and outcome of any Emergency Department attendances, hospital admissions, and Intensive Care Unit admissions; diagnosis of COVID-19 (including date of diagnosis); and mortality (date and cause of death).

Data from NHS Digital will be imported into the UK Secure e-Research Platform (Swansea University) where it will be linked with 999 call and ambulance dispatch data using study ID for analysis. Study sites have a list linking study IDs and identifiers, but Swansea University will not have access to this list. Data will not be relinked to it, or otherwise made re-identifiable. 999 call and ambulance dispatch data will be provided by the four participating ambulance trusts. They will send record-level pseudonymised data directly to Swansea University. This file will include study ID; the date (treated as index date), reason for, and outcome of any 999 calls and ambulance dispatches for patients in the cohort.

999 call and ambulance dispatch data will determine (1) the severity of the initial call and (2) any subsequent calls or dispatches made for this patient. This will indicate if the patient’s situation worsened, or if the patient did not believe they were triaged appropriately in the first instance.

In addition to the data flow into and out of NHS Digital described above; research paramedics at the East of England Ambulance Service, the East Midlands Ambulance Service, the West Midlands Ambulance Service, and the Yorkshire Ambulance Service will run a second search for any other events for the study cohort in the 3 months following their initial contact with COVID-19 (covered by CAG approval). Any such events will be included regardless of whether they are COVID-related or not. These data will be transferred securely to Swansea University and imported into the UK Secure e-Research Platform, where they will be linked with the data from NHS Digital to form the analysis dataset.

The UK Secure e-Research Platform is a safe, secure and controlled environment for data sharing, linking and analysis accredited to ISO 27001 standards. It is accessed via a two-factor authentication process involving a unique username and password, and individually issued Yubikey device. The Yubikey device is a hardware authentication device which protects access to computers, networks, and online services. User accounts are only given to authorised researchers with appropriate training in data protection and confidentiality. Access to specific projects is restricted to authorised users working on that project. The remote desktop environment has built-in measures to protect data including logging all user activity; restricting internet access; and preventing all data exports without approval.

There will be no subsequent flow of record-level data and no record-level data will be allowed to leave the UK Secure e-Research Platform. There will be no attempt to re-identify individuals. Data will be only processed on the UK Secure e-Research Platform. All study outputs, and findings from the statistical analysis, will be aggregated data with small numbers suppressed in line with the HES analysis guide.

No-one outside the East of England Ambulance Service, East Midlands Ambulance Service, West Midlands Ambulance Service, or Yorkshire Ambulance Service will have access to any list linking study IDs to identifiable people. Only the data analysis team at Swansea University, which does not overlap with the ambulance services, will have access to NHS Digital data.

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NIHR HS&DR 18/03/02 STRETCHED (Snooks) — DARS-NIC-327960-M2P9M

Type of data: information not disclosed for TRE projects

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

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(a); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(a); Health and Social Care Act 2012 – s261(2)(b)(ii); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-11-12 — 2023-11-11 2022.05 — 2022.08.

Access method: One-Off

Data-controller type: SWANSEA UNIVERSITY

Sublicensing allowed: No

Datasets:

1. Civil Registration (Deaths) - Secondary Care Cut
2. HES:Civil Registration (Deaths) bridge
3. Hospital Episode Statistics Accident and Emergency
4. Hospital Episode Statistics Admitted Patient Care
5. Hospital Episode Statistics Outpatients
6. Civil Registrations of Death - Secondary Care Cut
7. Hospital Episode Statistics Accident and Emergency (HES A and E)
8. Hospital Episode Statistics Admitted Patient Care (HES APC)
9. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

AIM

STRETCHED (“STRategies to manage Emergency ambulance Telephone Callers with sustained High needs – an Evaluation using linked Data”; IRAS ID 262419) is a study looking at the impact of multi-disciplinary case management approaches to handling frequent callers to the ambulance service. Frequent callers are defined as people who phone 999 more than 5 times in a month, or more than 12 times in three months. Frequent callers often have complex medical needs, but often do not require immediate medical attention.

Multi-disciplinary case management brings together professionals such as members of the ambulance service, primary and secondary care providers, third sector health and social care providers, the patient's GP, and mental health service providers. These professionals attend joint meetings to develop shared care plans that address the patient's needs more completely than any service could individually. As such, the nature of the case management process itself varies considerably from area to area, and from patient to patient.

STRETCHED will compare outcomes for frequent callers that do and do not receive case management according to a pre-specified statistical analysis plan to determine the safety and efficacy of this intervention. These outcomes include:
- further emergency contacts (999 calls, emergency department attendances and emergency admissions to hospital)
- effects on other services (including outpatients appointments, elective admissions, and GP contacts);
- adverse events, including patient safety (particularly mortality, but also injuries and serious medical emergencies, arrests/convictions, and complaints made by the patient about their local ambulance service);
- any associated costs/savings to the NHS.

Data from NHS Digital will enable this by providing information on dates, times, reasons for, and outcomes of non-ambulance service NHS contacts by frequent callers. These data are essential to understand the wider impact of the case management process, including whether any reduction in the number of 999 calls is a consequence of shifting demand elsewhere in the NHS.

STRETCHED has a sister project, INFORM (“Improving care for people who Frequently call 999: co-production of guidance through an Observational study using Routine linked data and Mixed methods”; IRAS ID 250693). INFORM is a Health and Care Research Wales Fellowship project looking at the epidemiology of frequent callers in Wales. INFORM will use data from the Secure Anonymised Information Linkage (SAIL) databank and qualitative interviews with stakeholders. INFORM will not use data from NHS Digital.

GDPR/Legal Basis

There is a quantitative and qualitative element to this project.
Section 251 support is in place for the Quantitative element. This element is observational, with a focus on describing the epidemiology of "frequent callers" and related outcomes,as obtained from retrospective routine data. This is the NHS Digital related part of the project.

Consent will be in place for the qualitative element - patient interviewees and focus group participants (health and allied care professionals). This is separate to the data linkage project done by NHS Digital.

Section 251 support from the Confidentiality Advisory Group (CAG) (Reference 19/CAG/0195) is in place to cover data flow and linkage to NHS Digital data. GDPR Articles 6 (1) (e) and 9 (2) (j) are the legal basis for processing of these data.

Data will be processed under Article 6 (i) (e) of the General Data Protection Regulation – “task in the public interest”. Special categories of data will be processed under Article 9 (2) (j) – “… scientific or historical research purposes or statistical purposes…”. Ambulance services struggle to manage the volume of callers, and this is likely to get more difficult in the future. STRETCHED may help ambulance services better meet the needs of frequent callers and release capacity for more urgent cases. Therefore, this project, led by an experienced team from Swansea University – a leading UK medical school and research institution - is clearly in the public interest.

Cohort members will be identified by research paramedics from frequent caller lists held by the East of England Ambulance Service, the London Ambulance Service, the West Midlands Ambulance Service, and the Welsh Ambulance Service. Cohort identification files will be uploaded directly into NHS Digital by research paramedics in the East of England Ambulance Service, London Ambulance Service and West Midlands Ambulance Service. Cohort identification files for the Welsh Ambulance Service will be sent to the NHS Wales Informatics Service, where a linking field will be generated. This linking field will be sent to the SAIL Databank (part of Swansea University), where it will be used to identify the anonymised health records of patients in Wales.

No direct patient identifiers (postcode, NHS Number) will be available to the study management team (defined below). This methodology was approved by Wales Research Ethics Committee on 14 August 2019. Section 251 approval was granted by the Confidentiality Advisory Group on 27th May 2020.


COHORT

Cohort members will be identified by research paramedics at each site (East of England Ambulance Service, London Ambulance Service, West Midlands Ambulance Service) screening the frequent callers list for people living in specific CCG areas added to the frequent callers list during 2018. If a list of frequent callers is not available from the time, frequent callers will be identified by a database search of 999 calls for individuals making 5 or more calls in a single month. Nursing/care/residential homes and similar institutions will be excluded. All adults that meet these criteria will be included in the study cohort; there are no further screening processes. The study cohort is approximately 1,264 frequent callers, aged 18 years and above. Cohort members are expected to be a mixture of ages, sex, and ethnicities, split approximately evenly across these ambulance services. Cohort members will be identified by their local ambulance service. The East of England Ambulance Service, London Ambulance Service, and West Midlands Ambulance Service, will upload data directly into NHS Digital. The Welsh Ambulance Service will upload data to the NHS Wales Informatics Service as described above.

Data items required include the date, time, reason for, and outcome of all accident and emergency department contacts, unplanned hospital admissions, and mortality, during the lead-in and follow-up periods. Patients who phone 999 might do so for any number of reasons and might contact any number of other agencies for any number of reasons. This data will determine if the case management intervention has any impact on other NHS Services (including health economics).

In addition - the pseudonymised demographic data fields required from NHS Digital are
- the study ID,
- sex of patient,
- month and year of birth

It is not possible to flag for the presence/absence of an event. Analysis will include exploratory analysis across several time periods and consider frequency of events.

All possible filtering (e.g. by time, geography, or clinical factors) etc. will be applied during cohort identification. Data cannot be obtained by less intrusive methods. Any other approach would require contacting patients out of the blue, which is intrusive and could cause distress. Data would also be less reliable due to recall bias, the aforementioned complex/sensitive needs, the potential for missing data, and the possibility the patient has died since the time period under study.

For each cohort member, Swansea University require data for 6 months each side of the date they were first added to their local ambulance service frequent callers list in 2018 (6 months to establish a baseline, and 6 months follow-up). Swansea do not require data outside this 1-year period for any given person. However, the overall dataset spans the period July 2017 to June 2019. This is 6 months before the earliest possible cohort member became eligible on 1st January 2018, to 6 months after the last (on 31st December 2018). Because HES extracts are packaged in financial years, Swansea University require data from 2017/18, 2018/19, and 2019/20 (with 17/18 data from July 2017 onwards only, and 19/20 data (April 2019 - July 2019)

DATA CONTROLLER/PROCESSOR

Swansea University is the sole data controller, who also process data provided by NHS Digital.

The participating ambulance services are East of England Ambulance Service, London Ambulance Service, West Midlands Ambulance Service, and the Welsh Ambulance Service. Research paramedics from each ambulance service will identify the study cohort from data held by that ambulance service and upload these records into NHS Digital (or to the NHS Wales Informatics Service in the case of the Welsh Ambulance Service). Each ambulance service is the sole data controller for the underlying data from which the study cohort for that service is drawn. The ambulance services are neither data controllers nor data processors for NHS Digital data.

The study sponsor is Swansea University: It's the sponsor who determines what data is collected for the research study through the protocol, case report form and/or structured data fields in a database. The sponsor therefore acts as the controller in relation to the research data.

A study management group consists of academics, researchers, methodologists and administrators from Swansea University, Cardiff University, Northumbria University, and Lincoln University; representatives of the four participating ambulance services; and two lay members. The study management group advises the sponsor (Swansea University) regarding the overall study design. The study management group will review aggregated data with small numbers suppressed from the analysis but not make decisions regarding data processing, and will not have access to record-level data. The study management group, and their respective organisations (with the sole exception of Swansea University) are neither data controllers nor data processors."

There is also a study steering committee, which provides independent oversight of the study. The steering committee consists of experts in prehospital and emergency care, methodological experts, stakeholder representatives (including ambulance services, the UK Frequent Callers Network, the police, and charities), and lay representatives. The steering committee does not make any decisions regarding data processing and are neither data controllers nor data processors. They will not see record-level NHS Digital data, only anonymous, aggregated data with small numbers suppressed from the statistical analysis.

FUNDER

The project is funded by the National Institute for Health Research (NIHR; Health Services and Delivery Research programme). The NIHR has no ongoing involvement in study management, data analysis, or interpretation of study findings. The NIHR is neither a data controller nor a data processor for the STRETCHED project.

Expected Benefits:

It is hoped that STRETCHED will benefit the provision of health care experienced by vulnerable patients. It is hoped it will improve the quality of decision making around alternative care pathways, improve information transfer between organisations to benefit patient safety and quality of care, and streamline patient flow.

There is increasing pressure on ambulance clinicians to make decisions regarding onward patient care, including when it is safe to refer the patient to community-based services instead of taking the patient to hospital. Appropriate models of care can support ambulance clinicians as their role shifts from that of pre-hospital care providers to autonomous clinical decision-makers.

If case management is shown to be effective and safe, then this will help to encourage its adoption. In turn, this will hopefully help ambulance services meet the needs of frequent callers, and release resources to help other callers. If the intervention is not safe and effective, ambulance services can focus their efforts on other approaches instead.

To demonstrate safety and effectiveness, STRETCHED needs to show a reduction in the number of 999 calls made by frequent callers and demonstrate that this does not cause the caller undue harm. Furthermore, case management may simply shift demand from one part of the NHS to another. This might affect the care provision of other patients, as well as the frequent caller, or have cost implications. Either of these could put greater strain on the NHS in the longer term. These elements can only be understood by following up frequent callers over time and comparing their NHS presentations with historical trends.

STRETCHED has a composite primary outcome including: 999 calls, ED attendances, emergency admissions to hospital, and death. These components will be analysed individually and cumulatively, according to the hierarchy of severity using multilevel generalised mixed linear models. The primary analysis will be conducted by treatment allocated; patients in case management areas will be analysed as part of that cohort regardless of whether they were offered case management. Intervention outcomes will be measured at six months from a patient’s first appearance on the frequent callers list during the study period. Historical data on prior service use and demographic information will allow adjustment for differences between cohorts as required.

Secondary outcomes include declassification and reclassification as a frequent caller (using ambulance service 999 call information), costs of service delivery, effects on other services, and details of demographics, case mix and call patterns. Screening and eligibility data will be presented as a CONSORT diagram. Descriptive baseline data on demographics and call characteristics will be presented by ambulance service, and by site.


The STRETCHED team hope that, by demonstrating whether the intervention is effective, ambulance services will be steered towards a more effective way to manage their caseloads and improve the quality of decision making towards frequent callers. This, in turn, should benefit the health of frequent callers, other ambulance service users, and hopefully relieve some of the pressures on ambulance services themselves.

STRETCHED is not in support of a PhD or post-graduate research study. It has a sister project, INFORM (“INFORM: Improving care for people who Frequently call 999: co-production of guidance through an Observational study using Routine linked data and Mixed methods”), which forms the basis of a Health and Care Research Wales Fellowship. INFORM looks at the epidemiology of frequent callers in Wales and will not use data from NHS Digital.

Outputs:

The study team engaged in strong service user involvement throughout the planning stages for this study. PPI research team members participated in discussions on study design including primary outcome selection and judgement of meaningful difference between study arms. Swansea will seek to widen PPI links during the study to better reflect the diverse patient population

Dissemination will seek to maximise stakeholder interest and understanding of the study as well as its outputs and maximise the impact of the findings on ambulance service policy, processes, practice and patients. Dissemination will build on the research management group’s profile and reputation with previous studies focused on improving the quality of pre-hospital care. From the first stage, the research management group has and will continue to work with Patient and Public Involvement contributors and co-applicants to develop communications, publications and dissemination plan including the assessment of stakeholder needs and communications activities and milestones. The plan will include engagement with patient and professional groups, NHS managers, commissioners, and policy makers. Lay summaries will be produced where appropriate.

Key audience groups for dissemination will include policymakers on emergency care, care-commissioning bodies and ambulance service providers, emergency-care practitioners, and the general public. The primary focus of dissemination efforts will reflect the importance of communicating findings regarding the effectiveness or otherwise of case management approaches for people who make high use of the 999 ambulance service to relevant policy makers and to the bodies that implement policy. The research management group will exploit existing links with UK ambulance services; they have already engaged with FreCANN (the Frequent Caller National Network; two members are co-applicants), and will, at an early stage in the study, present initial findings to the wider FreCANN network, seeking their input on identifying key messages which can then inform policy and practice.

The research management group will use strong links with ambulance services directly and through national bodies (National Ambulance Research Steering Group, National Ambulance Services Clinical Quality Group, Association of Ambulance Chief Executives (AACE) and National Ambulance Services Medical Directors. The research management group will further strengthen these links by contributing to the annual Ambulance Leadership Forum (organised by AACE). The research management group will liaise with NHS England, clinical commissioning boards in England, and Health Boards in Wales, Scotland and Northern Ireland; local authorities; social services and care/nursing home representatives to ensure findings can inform practice at a local community level. This is particularly relevant, as community-level services often share with ambulance services patients who frequently call 999.

Swansea University will seek the advice of the study management group for further dissemination of key findings to front-line ambulance service staff, this can take the form of contributions to internal ambulance boards, service briefings and bulletins, and practitioner/professional publications.

The study team will disseminate their findings through the following outputs. Outputs will be produced on an ongoing basis, with analysis expected to conclude towards the end of 2021.

1) A final comprehensive research report detailing all the work undertaken together with supporting technical appendices, abstract and executive summary. The plain English executive summary will focus on results/findings and will be suitable for use separately from the report as a briefing for NHS managers, emergency care practitioners and the general public.

2) Interim reports at intervals agreed with the funders.

3) A set of PowerPoint slides presenting the main research findings for use by the research team or others in disseminating research findings to the NHS and other stakeholders.

4) Papers for academic peer-reviewed journals such as the Annals of Emergency Medicine, Emergency Medical Journal, BMC Emergency Medicine, Social Science and Medicine and Implementation Science. This will ensure the research forms part of the scientific literature and is available to other researchers. The study team support an open-access model of research dissemination.

5) Articles for professional journals which are read by the NHS management community and which will be helpful in raising wider awareness of the research findings e.g. Ambulance UK, Health Services Journal.

6) Seminars, workshops, conferences at regional, national and international level and other interactive events, where the research team will present and discuss the research and its findings with NHS managers.

7) Guidance to inform the future care of frequent callers in order to maximise the potential to support the shift of care out of hospitals and into the community.

8) User-friendly materials for service managers and commissioners/policymakers using infographics to maximise accessibility and reach.

The study communications, publications and dissemination plan will contain media engagement, to include written press coverage, online media, and social networking, with the support of the dedicated marketing team in Swansea University Medical School. Given the implications for practice, policy, and research, the research management group will disseminate findings through the annual 999 EMS Research Forum Emergency Care Conference, which is hosted each year by a UK Ambulance service and is administered by Swansea University PRIME Research Network for Unscheduled Care and brings together academics and practitioners. In addition to a full final study report, STRETCHED will produce a summary version to be disseminated through the PRIME network. The research management group will present findings at other appropriate national and international events, such as the Health Services Research Network annual conference, the International Forum for Quality in Healthcare, and the European Society for Emergency Medicine. The research management group will ensure that the wider learning from the study (i.e. lessons which are not specific to emergency care) is disseminated to appropriate audiences.

In addition to disseminating findings through publications and through conference presentations at regional, national and international level, the research management group will:
(a) hold a dissemination workshop in collaboration with the 999EMS Research Forum and/or College of Paramedics;
(b) offer to present findings directly to the three participating ambulance services at dedicated workshop events in their area. The research management group will ensure that dissemination goes beyond ambulance services to include other key health care providers and policy makers with an interest in the wider picture of urgent and emergency care. Dissemination will also target the academic community to ensure that future research in this area takes account of and builds further upon study findings.

Conference presentations, posters and similar will be conducted throughout and following the study as opportunities arise. Scientific papers will be prepared at the conclusion of the study; this is expected to be late 2021. Study outputs will present aggregate data only with small number suppression applied in line with the HES analysis guide. Record-level data will not be shared outside the statistical team.

STRETCHED is a natural experiment looking at activities already carried out by ambulance services. No exploitable intellectual property is anticipated. Should any be developed, the research management group will seek professional advice from the Research, Engagement and Innovation Services department at Swansea University.

Processing:

DATA FLOW

Frequent callers will be identified retrospectively by research paramedics at the East of England Ambulance Service, the London Ambulance Service, the West Midlands Ambulance Service, and the Welsh Ambulance Service). Approximately 316 frequent callers will be identified by each ambulance service, giving a total cohort size of 1264. Approx 948 of these participants will be the subject of the cohort for the NHS Digital linkage.

Researcher paramedics at the East of England Ambulance Service, London Ambulance Service, and West Midlands Ambulance Service will import the following record-level data into NHS Digital.
• NHS Number,
• Postcode – District Level,
• Date of Birth,
• Sex.

Equivalent data for the Welsh Ambulance Service will instead be uploaded to the NHS Wales Informatics Service, where a linking field will be generated. This linking field will then be sent to the SAIL Databank (Swansea University) where it will be used to identify the anonymous health records for patients in Wales.

The statistical analysis team at Swansea University will not have access to patient identifiable information; the statistical analysis team at Swansea University will see study ID, month and year of birth, sex, and ethnicity. Only NHS Digital or NHS Wales Informatics Service (as appropriate) and the ambulance service providing the data will have access to any patient’s NHS number, postcode district, and full date of birth.

The East of England Ambulance Service, London Ambulance Service, and West Midlands Ambulance Service will also send the following data to Swansea University. This will be linked with the HES data that NHS Digital provide (via the Study ID).This linkage to the additional data will not be done by NHS Digital - but by Swansea.

- the date cohort members were added to, or removed from, the ambulance service frequent callers list
- the date, time, reason for, and outcome of 999 calls made by cohort members during the study period.
- the date, time, condition codes and outcome of any ambulance call-outs to cohort members during the study period
Equivalent data for the Welsh Ambulance Service will be imported into SAIL Databank instead.

Record-level data from NHS Digital and NHS Wales Informatics Service, including the ambulance service data on 999 calls and ambulance call-outs, will be imported into the SAIL Databank for analysis. The SAIL Databank is a secure data haven hosted at Swansea University. Access to data in the SAIL Databank is restricted to specific, authorised users with appropriate training as described below.

There will be no subsequent flow of record-level data. Data will not be matched to other publicly available data, and there will be no attempt to re-identify individuals. Record level data will not be shared with the research management group, the study steering committee; or the participating ambulance services (East of England Ambulance Service, London Ambulance Service, West Midlands Ambulance Service and the Welsh Ambulance Service). All study outputs, and all statistical analysis findings, will report anonymous, aggregated data with small numbers suppressed only in line with the HES analysis guide.


DATA REQUESTED

STRETCHED is investigating the impact of multidisciplinary case management on frequent callers to the ambulance service. Outcomes include:
- any change to the number of 999 calls made,
- any impact on the wider health service (including emergency department attendances, emergency hospital admissions, outpatient appointments, elective admissions),
- signs of any adverse impact on the patient (including mortality, serious medical emergencies, other injuries, arrests, convictions, and patient complaints about their local ambulance service).

The following data products from NHS Digital are required:
Hospital Episode Statistics Admitted Patient Care (2017/2018 – 2019/2020)
Hospital Episode Statistics Accident and Emergency (2017/2018 – 2019/2020)
Hospital Episode Statistics Outpatients (2017/2018 – 2019/2020)
Civil Registration (Deaths) - Secondary Care Cut – Linked to HES
HES: Civil Registration (Deaths) bridge

The research team requires date and cause of death to determine if there is any difference in mortality between frequent callers that are/are not in case management areas.

The research team require the date, time, reason for, and outcome of any emergency department attendances, emergency hospital admissions, outpatient appointments, and elective admissions to determine if there is any difference in hospital service use between frequent callers that are/are not in case management areas.

Healthcare resource group codes will allow the research team to determine the health economic impact of any differences thus observed.

The research team require lower super output area codes and index of multiple deprivation scores to determine if the impact of case management varies with social deprivation level.

The research team require month and year of birth, sex, and ethnicity to adjust for demographic factors when investigating any effect of case management, and to check that the case management process does not adversely discriminate on any of these grounds.

The research team will use data on the dates, times, reasons for, and outcomes of 999 calls and ambulance callouts provided by the East of England Ambulance Service, the London Ambulance Service, the West Midlands Ambulance Service, and the Welsh Ambulance Service to assess if there is any difference in the number of 999 calls and ambulance callouts between areas that do/do not use multi-disciplinary case management.


DATA MINIMISATION

The study cohort is people added to the frequent callers list by the East of England Ambulance Service, the London Ambulance Service, the West Midlands Ambulance Service, and the Welsh ambulance Service during 2018. Approximately 316 frequent callers will be identified by each ambulance service, giving a total cohort size of 1264. Approx 948 of these participants will be the subject of the cohort for the NHS Digital linkage.

Data are only required for subjects that form part of this cohort from the East of England Ambulance Service, the London Ambulance Service, and the West Midlands Ambulance Service. However, all data items are required for these cohort members to conduct the planned analysis. All possible filtering will be applied during cohort identification. Therefore, the data requested cannot be further narrowed down by geography, demographics, or any other factors. Data for cohort members identified by the Welsh Ambulance Service will instead be obtained from the SAIL Databank.

Data are required for 6 months before the patient is added to the frequent callers list to establish baseline trends, and for 6 months afterwards to identify any change in resource use. Thus, the full dataset spans the period July 2017 to June 2019. Data outside this period are not required.

All patient episodes in the requested datasets during the requested period are needed. The number of NHS contacts within six months of classification as a frequent caller is a key study outcome. Details of each contact are required in order to check for signs of harm resulting from the intervention, or unintended effects on other NHS services.

Frequent callers are a group with complex and sensitive needs. There are no study-specific visits or activities and following up patients directly could cause unintended distress. Therefore, use of routine data is the least intrusive and most reliable method for follow up. This methodology was approved by Wales Research Ethics Committee 4 on 14 August 2019. Section 251 approval was granted by the Confidentiality Advisory Group on 27th May 2020.


DATA PROCESSING

Data will only be processed by substantive employees of Swansea University (the sole data controller) who have appropriate training in data protection and confidentiality. Data will only processed via the SAIL Databank, a secure data haven hosted at Swansea University.

Access to the SAIL Databank is via a two-factor authentication procedure (a personal username and password, and individually issued Yubikey device). The remote desktop environment has built-in measures to protect data including logging all user activity; restricting internet access; and preventing data exports without prior approval.

Data will not be matched to other publicly available data, and there will be no attempt to re-identify individuals. All findings of the statistical analysis, and all study outputs, will present as anonymous, aggregate data only.

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GPs-in-EDs (Phase 2) NIHR HS&DR 15/145/04 — DARS-NIC-267223-D4Q3F

Type of data: information not disclosed for TRE projects

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(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

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

When:DSA runs 2020-05-01 — 2022-04-30 2020.09 — 2021.02.

Access method: One-Off

Data-controller type: CARDIFF UNIVERSITY, SWANSEA UNIVERSITY

Sublicensing allowed: No

Datasets:

1. Hospital Episode Statistics Admitted Patient Care
2. Hospital Episode Statistics Accident and Emergency
3. Hospital Episode Statistics Accident and Emergency (HES A and E)
4. Hospital Episode Statistics Admitted Patient Care (HES APC)

Objectives:

The research described in this Agreement is an integral part of a wider study funded by the National Institute for Health Research (NIHR). The overall study is divided into separate work packages and Cardiff University, as the contact organisation with the NIHR for this study, is leading on Work Packages relating to the existing academic and practitioner literature, the intervention taxonomy, and the qualitative research.

Swansea University is the lead organisation for study Work Packages involving quantitative research, including the work described in this Agreement. Cardiff University has been included as a joint data controller because of its involvement in the earlier phases in this study. Cardiff University jointly scoped the need for this project and determined why this project is required. Cardiff University will not receive or process any data under this Agreement but may provide advice as part of the study management team. Only Swansea University will process the data under this Agreement.

The NIHR is funding this project. There is a steering committee which provides advice to each delegated work package responsible teams. As such the NIHR is not a data controller as it only provides advice as requested by the joint data controllers Cardiff University and Swansea University.

Lawful basis under GDPR
GDPR Article 6 (1) (e) states that processing is lawful if it is necessary for the performance of a task carried out in the public interest.

Swansea University has determined that the use of data under this Agreement to undertake an assessment of the various methods of deploying General Practitioners (GPs) working within Emergency Departments (EDs) is in the public interest from both clinical and economic perspectives. Furthermore, the processing proposed is necessary to provide the data required to make this assessment.

GDPR Article 9 (2) (j) states that processing of personal data is lawful if it is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes and proportionate to the aim pursued, respect the essence of the right to data protection.

Swansea University has determined that the processing outlined in this Agreement will enable assessment of various GPs-in-EDs models currently in use at Emergency Departments. This assessment is both in the public interest (as explained above) and, by defining clear objectives for the statistical analysis of the data requested, the processing is proportionate to the study’s research aims.

Swansea University is requesting HES Accident & Emergency and HES Admitted Patient Care data at record level in order to strengthen the evidence base on different service models of GPs-in-EDs. This study seeks to understand the impact of such services on patient health outcomes; their experience and safety, and the health services resource use and related cost of delivering these models.

The overall aim of the study is to determine the clinical and cost effectiveness of GPs-in-EDs models and to understand the ways in which service design and setting (context) generate variations in outcomes.

The study is intended to evaluate the ability of different GPs-in-EDs models to achieve the key outcomes described in an effective practice framework (addressing greatest health needs first; only doing what is needed; reducing inappropriate variation) and the resources needed to deliver these outcomes.

Swansea University is requesting pseudonymised patient level data only for specified study sites which include twelve Emergency Departments in England. The data subjects are all individuals who have created HES episodes at A&E, possibly followed by admission, during the period of time requested and minimised to the providers listed below.

Swansea University is requesting pseudonymised patient level data providing information on admission date and time, gender, age, health event date and time, visit status (first attendance or re-attendance), attendance category, primary diagnosis, investigations, treatment and disposition codes, and mainly non-sensitive information relating to subsequent admission, episodes and discharge. Swansea University is requesting one data item which is categorised as sensitive; this field will facilitate, through analysis of HES A&E and HES APC fields, a more complete understanding of patient assessment and treatment following presentation at study site EDs. All other data requested is pseudonymised, personal, record level, special category data.

Swansea University will use this record level data to calculate various ED-specific estimates to be used as outcome measures to compare different GPs-in-EDs models. These measures, in the form of appropriate summary statistics, include the average patient age and gender split; the total number of ED attendances; admissions; proportion of re-attendances; average waiting times, and the proportion admitted as an inpatient to the same hospital.

The study team has only requested HES A&E and HES APC data fields required to execute the study's Statistical and Health Economics Analysis Plan (SHEAP) as approved by the independent Study Scrutiny Committee.

The study team have also limited the request to the work package window between 2010/11 and 2018/19. This window has been chosen to provide a time frame before the first intervention of GPs-in-EDs and after the last intervention. The time before and after is to be able to analyse the effect of using the GPs-in-EDs model, from prior and post intervention data.

At the data extraction stage, the study team will only request data relating to presentations to and attendances at Emergency Departments (EDs) at twelve English study sites. The sites are listed below, along with the Site Provider codes which, to the best of the study team’s knowledge, were in use over the study period.

The twelve sites are as listed below; this is the final list of study Emergency Departments in England.

The twelve sites and codes are:
1. Musgrove Park Hospital (Taunton and Somerset NHS Foundation Trust); code RBA11
2. Friarage Hospital (South Tees Hospitals NHS Foundation Trust); code RTR45
3. Chichester Hospital (Western Sussex Hospitals NHS Foundation Trust); codes RYR16 & RYR51
4. Airedale General Hospital (Airedale NHS Foundation Trust); code RCF22
5. Queen Elizabeth Hospital (Gateshead Health NHS Foundation Trust); codes RR7EN & RR729
6. Royal United Hospitals (Royal United Hospitals Bath NHS Foundation Trust); codes RD1C3 & RD130
7. St. George's (St. George's University Hospitals NHS Foundation Trust); code RJ701
8. North Tees (North Tees and Hartlepool NHS Foundation Trust); codes RVWAE & RVWNA
9. Manchester Royal Infirmary (Manchester University NHS Foundation Trust); codes RM326 & R0A1F
10. Countess Of Chester Hospital (Countess of Chester Hospital NHS Foundation Trust); codes RJR05 & RJR45
11. Warwick Hospital (South Warwickshire NHS Foundation Trust); codes RJC02 & RJC05
12. Southport & Formby Hospital (Southport & Ormskirk Hospital NHS Foundation Trust); codes RBN51, RET26, RVY25, RTV1G, RVY01 & RVY1Y.

Swansea University has determined that there is no alternative, less intrusive method of obtaining the various site-level characteristics required to achieve the study’s objectives.

Expected Benefits:

Increasing demand on the United Kingdom (UK) National Health Service, urgent and emergency services is testing the capacity of the system and there are concerns about the consequent ability to deliver good quality care. One of the recommendations in a joint report by the Royal Colleges of Emergency Medicine, Paediatrics and Child Health, Physicians and Surgeons to address these pressures is that every Emergency Department (ED) should have a co-located primary care facility.

However, the evidence base to support different service models of General Practitioners (GPs) working within EDs (GPs-in-EDs models) is weak. Understanding the impact of such a service on patient health outcomes, experience and safety and the health services resource use and related cost of delivering these outcomes is important. This research is intended to evaluate the ability of GPs in the ED setting and different GP models to achieve key outcomes in an effective practice framework: namely, addressing greatest health needs first; only doing what is needed; reducing inappropriate variation; and co-production and the resources needed to deliver these outcomes.

It is anticipated that the research findings (due February 2021) will be of immediate interest to policy makers, service commissioners and providers.

The study’s findings have the potential to shape the provision of GP services in EDs at all Emergency Departments in the UK. The potential impact is, therefore, considerable, effectively extending to the entire general population. It is difficult, in advance of undertaking the cost-effectiveness analyses proposed in this study, to quantify with any precision potential costs and savings but, should the study’s findings lead to savings in the NHS-wide delivery of such services, then these are likely to be considerable.

Any benefits arising from the study will be to the NHS. The NHS includes the NIHR (the study funder), NHS Digital, as well as the study sites. The study team will only benefit from cost or efficiency savings as members of the public, i.e. in the same way as other members of the public using the NHS.

Benefits will be measured directly by specific study outcomes. These include the appropriate treatment of patients on arrival at EDs; appropriate referrals to further services, either in the ED or elsewhere; and in the proportion of patients returning to the ED within specified time intervals.

Outputs:

To meet a condition of the research funding, Swansea University will produce a comprehensive study report containing appropriate summaries of the study data (including HES data), and analysis of that data. The deadline for this report is February 2021. The report will also form the basis of academic articles to be submitted to high-quality peer-reviewed journals, conference presentations, and other outputs, as specified in the study's dissemination strategy.

In addition to fulfilling the requirements to submit a definitive study report to its funder (NIHR, the National Institute for Health Research), the study team will seek simultaneously to publish the main study findings in appropriate high-impact academic journals. Given that these findings concern the provision of GP services, and hence will be of widespread interest, it is envisaged that target journals will include The Lancet, the British Medical Journal, the British Journal of General Practice, and the Annals of Emergency Medicine - all with an international readership. It is also the intention of the study team to present study findings at appropriate National and International conferences, such as those annually hosted by the Health Technology Assessment international (HTAi).

The study team will summarise findings for dissemination to NHS organisations. The Universities anticipate the study will provide the evidence base for unscheduled care delivery in Emergency Departments in England and Wales, evaluating different models of GPs in or alongside EDs for their effectiveness and safety, good use of resources and sustainability, suitable for local contexts. The Universities will explore strategies for dissemination with the Stakeholder group and other senior advisors, consisting of senior policy and operational representatives of both nations and from Royal Colleges (Emergency Medicine, General Practitioners). It is likely that this will involve presentations at leading national conferences, as well as securing invitations to smaller seminars and local meetings to a variety of professional and lay audiences.

Timing of these communications will be in agreement with the funder, the NIHR. The study team is obliged by the terms of its funding to liaise with the NIHR in order to maximise impact by synchronising the publication of major outputs. The current target date for submission of the funder’s report is February 2021 but the report’s publication timetable is dependent on the NIHR’s reviewing processes. Similarly, conference presentations on study results are also embargoed by the funder until publication of its report. The study team will further liaise with the funder on this matter, again with the view of maximising impact.

Processing:

Record level, pseudonymised HES A&E and HES APC data - minimised as described above - will be extracted from the HES A&E and HES APC datasets and securely disseminated to Swansea University.

The data from NHS Digital will be combined with the corresponding equivalent SAIL (record level pseudonymised data for the sole Welsh A&E site - a study control). There will be no linkage of this combined data and this combination will allow for analysis using a study ‘control’ site. Further manipulation of the combined data will be required to generate summary characteristics for the extended control group. These summary characteristics will then be reported.

Swansea University will, in accordance with the study's Statistical and Health Economics Analysis Plan (SHEAP), then calculate various Emergency Department specific estimates to be used as outcome measures to compare different GPs-in-EDs models. These measures, in the form of appropriate summary statistics, include the average patient age and gender split, the total number of ED attendances, admissions, proportion of re-attendances, average waiting times, and the proportion admitted as an inpatient to the same hospital.

For continuous outcomes, appropriate summary statistics will be analysed.

There is no requirement to re-identify individuals, and no re-identification will be attempted. Data processing will only be performed by substantive employees of Swansea University, the sole data controller and sole data processor. These employees will possess appropriate, certified and SAIL-specified training in data protection and confidentiality, such as that provided by the Medical Research Council.

All NHS Digital data will be stored, processed and accessed at Swansea University, with secure access to study researchers solely via the SAIL Gateway. Study researchers will be accredited Sail Gateway users, will have completed appropriate and certificated training on Research Data and Confidentiality, and will only be able to access the data through SAIL’s secure two-factor authentication processes. These processes involve the use of a personalised ‘Yubikey’ device, issued only to accredited SAIL Gateway users.

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