Impact of an Intervention on Inequalities in Overprescribing - the 3i-o study

The University of Leeds requires access to NHS England data for the purpose of the following research project:

Impact of an Intervention on Inequalities in Overprescribing -the 3i-o study

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

This study will look at individual patients from GP practices in areas subject to an Audit and Feedback intervention to reduce rates of prescription of antibiotic, addictive painkillers and gabapentinoid medications, and control areas not subject to such interventions.

The aim of the study is to evaluate the impact, implementation and sustainability of audit and feedback on health inequalities in prescribing in general practice. The objectives are to measure the impact of feedback on overprescribing inequalities and evaluate the balance between equity and efficiency of feedback interventions in reducing over-prescription of these medications. The information will allow the University of Leeds to assess the impact on health service resource use and costs. The University of Leeds will use the NHS England data being requested and data collected in the project on the costs of the feedback intervention and preferences of members of the general public for overall effectiveness versus reducing health inequalities, to conduct a distributional cost effectiveness analysis of the intervention.

The following NHS England Data will be accessed:

> Hospital Episode Statistics Admitted Patient Care (HES APC), HES Outpatients (OP) and Emergency Care Data Set (ECDS) – necessary to derive estimates of costs associated with hospital care and of hospitalisations and number and duration of hospital admissions and inform the distributional cost-effectiveness evaluation.

> Medicines dispensed in Primary Care (NHSBSA data) – necessary to give a more complete measure of the effectiveness of the intervention on antibiotic and addictive painkillers and gabapentinoids prescribing. These Data will be used to conduct additional cost-effectiveness analysis using dispensed, as opposed to prescribed, antibiotic medications, as dispensed medications may be more relevant measure of NHS resource use.

The level of the Data will be:

> Identifiable

Although only pseudonymised data fields have been requested from NHS England, North of England Care Support System (NECS) hold the identifiers for the cohort, and therefore, though no attempt will be made, NECS have the technical means to reidentify participants.

The Data will be minimised as follows:

> Limited to a study cohort identified by the University of Leeds – a cohort of participants from GP practices taking part in the 3i-o study (estimated cohort size: 150 practices with approximately 10,000 patients each, that is, 1.5 million patients in total). Patients can opt out of the 3i-o study through their GP, meaning the GPs won't flow their identifiers to NECS for participation in the study. Section 251 support is in place for the flow of cohort identifiers from NECS to NHS England.

> Limited to data between Jan 2017 to latest available. For each individual patient, data will only be provided from the date of when intervention started for each individual study participant registered in GP practices in intervention areas and an 'index date' for each individual participant registered in GP practices in control areas. Data will be compared from pre-intervention and over a 12-month period of intervention delivery (addictive painkillers) or 48-month period of intervention delivery (antibiotics in Bradford and Craven). For NHSBSA data, data will not be limited to these periods described.

> Limited to the following geographic areas have received feedback interventions to reduce overprescribing in the past six years:

(1) Bradford and Craven – Covers Bradford City, Districts, Craven and Airedale, relatively young population, high levels of ethnic diversity and deprivation, urban and rural. Feedback interventions: opioids, gabapentinoids and antibiotics.

(2) Hull and East Riding – Predominantly white British ethnicity, Hull has a relatively younger, deprived and urban population, whereas East Riding is relatively older, more affluent and rural population. Feedback interventions: opioids and antibiotics.

(3) Tees Valley - Covers Darlington, Hartlepool, Middlesbrough, Redcar and Cleveland and Stockton on Tees, normal age distribution, mixed rural, urban and coastal, high deprivation, ethnic diversity and asylum seekers. Feedback interventions: opioids and gabapentinoids.

These study areas have been selected to ensure diversity in factors that evidence suggests increase risks of overprescribing.

The University of Leeds is the research sponsor and 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.

This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care. It also aims to improve public health by providing evidence to help NHS decision-makers identify effective and cost-effective means of reducing unnecessary use of antibiotic, addictive painkillers and gabapentinoid medications.

The funding is provided by the National Institute for Health and Care Research (NIHR). The funding is specifically for the 3i-o study described.

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

NECS is a processor acting under the instructions of the University of Leeds. NECS’ role is limited to linking their primary care data for the patients registered in the study GP practices to the NHS E data being requested in this DARS, creating a working space for the linked data on their Axiom platform where work with the linked data by University of Leeds will occur.

Microsoft Azure provides IT back up services to NECS and will store copies of the Data as contracted by NECS.

The independent Trial Steering Committee (TSC) and independent Data Monitoring and Ethics Committee (DMEC) are involved in an advisory capacity. The TSC provides advice, through its chair, to the chief investigator, the trial sponsor, the trial funder, on all appropriate aspects of the trial. The DMEC provides advice to the TSC.

NECS will also act on an advisory capacity, to facilitate data linkage between primary care data they will provide access to and link to the NHS E data being requested in this DARS, as well as use of their Axiom platform where work with the linked data will occur.

Data will be accessed by:

- Substantive employees of the University of Leeds and NECS

- A visiting academic, currently employed by the University of Exeter, who has an honorary contract with the University of Leeds and will be under the supervision of a substantive employee of the University of Leeds for the purposes described in this DSA only.

A Public and Patient Involvement and Engagement (PPIE) group was convened to help refine the purpose of the research. The group supported the design of the study for the purposes described above. This included working with six PPIE contributors from early design and will continue through to dissemination, implementation, and NHS adoption.

The PPIE involvement has provided a unique perspective on the problems of over-prescription of commonly used antibiotic and painkiller medications and the potential unintended effects of attempts to reduce their excessive use. It has been helping the University of Leeds to define the research question to ensure it is relevant to the patient population and is helping the University of Leeds to design their research methods. Specific examples of the PPIE group’s ongoing involvement include providing a PPIE perspective on topic guides for qualitative interviews that will seek to elicit patient experiences of the effects of audit and feedback interventions in the study and review patient facing materials before submission for ethics approval. The group also have ensured that the inclusion criteria is broad and included patient groups that are disadvantaged according to ethnicity or education.

North of England Care Support System (NECS) will transfer data to NHS England. The data will consist of identifying details (specifically NHS number, Date of Birth, postcode and a unique person ID) for the cohort to be linked with NHS England data. A date of enrolment into the study will also be provided for each participant.

NHS England will provide the relevant records from the HES, ECDS and Medicines Dispensed datasets to NECS. The Data will contain no direct identifying data items but will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient.

The data will be stored (and processed from) the North East and North Cumbria (NENC) Secure Data Environment (SDE) infrastructure.

NHS North East and North Cumbria Integrated Care Board (ICB) is the host organisation for the North East and North Cumbria Secure Data Environment (SDE).

NECS stores Data on the Cloud provided by Microsoft Limited, NECS provides support to NENC.

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. The data will not leave England at any time.

Access is restricted to employees or agents of the University of Leeds and NHS North of England Commissioning Support Unit who have authorisation from the Lead Investigator.

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

The Data will be linked at person record level with primary care data obtained from protection and confidentiality.

The Data will be linked at person record level with primary care data obtained from NECS for the patients registered in the 150 GP practice taking part in the 3i-o study.

The Data will not be linked with any other data.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset.

The NHS England Data will be kept separate from other unrelated data NECS hold in the Axymn platform for exclusive access by authorised University of Leeds researchers for the purposes of conducting the 3i-o study.

Analysts from the University of Leeds and NECS will analyse the Data for the purposes described above.

The expected outputs of the processing will be:

- A final report of findings to NIHR is expected to be published in the NIHR Journal Library before the end of 2026.

- Submissions to peer reviewed journals, including separate publications for the main health impact of the intervention, target journal, British Medical Journal, a second will report the cost-effectiveness analysis of Audit & Feedback intervention, target journal is Value in Health. Both are expected to be published before the end of 2026.

- Presentations at the National Health Economics Study Group meeting and International European conferences in Public Health and Health Economics, over the years 2026 and 2027.

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.

The outputs will be communicated to relevant recipients through the following dissemination channels:

- Journals

- Dissemination event for patients/ the public, key stakeholders, Trial Steering Committee and Data Monitoring

- Committee and participating sites to include wider NHS implementation/adoption guidance.

- Study Summary Reports prepared for an in collaboration with health professional and provider organisations.

- Fact sheets summarising study findings to inform NHS primary care services for dissemination among NHS primary care networks.

- Final dissemination event to report research finding to key stakeholders (e.g.-patients/national patient advocates, clinicians, NHS England-commissioners).

- Plain English summaries for dissemination to wider lay audiences working in collaboration with our PPIE Group.

The outputs will be communicated to relevant recipients within 12 months after the study end, and beyond this timepoint with professional and guideline setting organisations.

The findings of this study are expected to contribute to more selective use of antibiotics and addictive painkillers throughout the NHS, thereby limiting opportunities for unnecessary use of these treatments and for resistance to antibiotics to develop, thus limiting harm and safeguarding the effectiveness of what is a limited resource.

The 3i-o project proposes to use the data to measure the effects of an Audit & Feedback intervention providing GP practices 6 bimonthly comparative feedback prompting clinicians to “think twice” before initiating opioids for chronic, non-cancer pain and antibiotics for common infections, and actively review repeat prescribing. The 3i-o study will therefore determine whether this intervention may be ready to be rolled-out nationally or, if it exacerbates inequalities in excessive use of these medications, the need for additional measures to support a reduction in overprescribing in practices serving disadvantaged populations. The timescale to onset of these benefits is Year 1-3 post-programme end of 2026.

The use of the data could:

- help the system to better understand the health and care needs of populations.

- lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.

- advance understanding of regional and national trends in health and social care needs.

- inform planning health services and programmes, for example to improve equity of access, experience and outcomes.

- 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.

Primary care was responsible for £9.4 billion (55%) of NHS prescribing costs in 2020-21 and therefore represents a major target for efforts to reduce overprescribing. However, it is not known whether interventions to reduce overprescribing in primary care exacerbate or reduce health inequalities. There is concern that well-intentioned interventions may actually increase health inequalities, with more affluent groups benefitting more so or sooner than more deprived groups. This study is expected to benefit the more disadvantaged members of society by determining whether the intervention being studied had any effect on health inequalities and, if found to exacerbate them, whether extra health care and research resources are needed to reduce inequalities.

These benefits will be achieved by first, demonstrating how A&F interventions can be done to reduce excessive use of antibiotics and addictive opioids in primary care and what measures may be needed to avoid that the intervention increases health inequalities.

The findings will be advertised in professional organisations, including Royal College of GPs, commissioners from Integrated Care Boards and patient groups.

Yielded Benefits is not a requirement for new applications.