Realising the full potential of data-enabled trials in the UK: a call for action.

RATIONALE: Clinical trials are the gold standard for testing interventions. COVID-19 has further raised their public profile and emphasised the need to deliver better, faster, more efficient trials for patient benefit. Considerable overlap exists between data required for trials and data already collected routinely in electronic healthcare records (EHRs). Opportunities exist to use these in innovative ways to decrease duplication of effort and speed trial recruitment, conduct and follow-up. APPROACH: The National Institute of Health Research (NIHR), Health Data Research UK and Clinical Practice Research Datalink co-organised a national workshop to accelerate the agenda for 'data-enabled clinical trials'. Showcasing successful examples and imagining future possibilities, the plenary talks, panel discussions, group discussions and case studies covered: design/feasibility; recruitment; conduct/follow-up; collecting benefits/harms; and analysis/interpretation. REFLECTION: Some notable studies have successfully accessed and used EHR to identify potential recruits, support randomised trials, deliver interventions and supplement/replace trial-specific follow-up. Some outcome measures are already reliably collected; others, like safety, need detailed work to meet regulatory reporting requirements. There is a clear need for system interoperability and a 'route map' to identify and access the necessary datasets. Researchers running regulatory-facing trials must carefully consider how data quality and integrity would be assessed. An experience-sharing forum could stimulate wider adoption of EHR-based methods in trial design and execution. DISCUSSION: EHR offer opportunities to better plan clinical trials, assess patients and capture data more efficiently, reducing research waste and increasing focus on each trial's specific challenges. The short-term emphasis should be on facilitating patient recruitment and for postmarketing authorisation trials where research-relevant outcome measures are readily collectable. Sharing of case studies is encouraged. The workshop directly informed NIHR's funding call for ambitious data-enabled trials at scale. There is the opportunity for the UK to build upon existing data science capabilities to identify, recruit and monitor patients in trials at scale.

Use of prescribing safety quality improvement reports in UK general practices: a qualitative assessment.

BACKGROUND: Quality improvement (QI) initiatives are increasingly used to improve the quality of care and reduce prescribing errors. The Royal College of General Practitioners (RCGP) and Clinical Practice Research Datalink (CPRD) QI initiative uses routinely collected electronic primary care data to provide bespoke practice-level reports on prescribing safety. The aim of this study was to explore how the QI reports were used, barriers and facilitators to use, long-term culture change and perceived impact on patient care and practices systems as a result of receiving the reports. METHODS: A qualitative study using purposive sampling of practices contributing to the CPRD, semi-structured interviews and inductive thematic analysis. We interviewed general practitioners, pharmacists, practice managers and research nurses. RESULTS: We conducted 18 interviews, and organised themes summarising the use of QI reports in practice: receiving the report, facilitators and barriers to acting upon the reports, acting upon the report, and how the reports contribute to a quality culture. Effective dissemination of reports, and a positive attitude to audit and the perceived relevance of the clinical topic facilitated use. Lack of time and failure to see or act upon the reports meant they were not used. Factors influencing use of the reports included the structure of the report, ease of identifying cases, and perceptions about coding accuracy. GPs and pharmacists used the reports to conduct case reviews and directly contact patients to discuss unsafe prescribing and patient medication preferences. Finally, the reports contributed to the development of a quality culture within practices through promoting audit activity and acting as a reminder of good prescribing behaviours, promoting future patient safety initiatives, contributing to continuing professional development and improving local networks. CONCLUSIONS: This study found the reports facilitated individual case review leading to an enhanced sense of quality culture in practices where they were utilised. Our findings demonstrate that the reports were generally considered useful and have been used to support patient safety and clinical practice in specific cases.

Quality improvement of prescribing safety: a pilot study in primary care using UK electronic health records.

BACKGROUND: Quality improvement (QI) is a priority for general practice, and GPs are expected to participate in and provide evidence of QI activity. There is growing interest in harnessing the potential of electronic health records (EHR) to improve patient care by supporting practices to find cases that could benefit from a medicines review. AIM: To develop scalable and reproducible prescribing safety reports using patient-level EHR data. DESIGN AND SETTING: UK general practices that contribute de-identified patient data to the Clinical Practice Research Datalink (CPRD). METHOD: A scoping phase used stakeholder consultations to identify primary care QI needs and potential indicators. QI reports containing real data were sent to 12 pilot practices that used Vision GP software and had expressed interest. The scale-up phase involved automating production and distribution of reports to all contributing practices that used both Vision and EMIS software systems. Benchmarking reports with patient-level case review lists for two prescribing safety indicators were sent to 457 practices in December 2017 following the initial scale-up (Figure 2). RESULTS: Two indicators were selected from the Royal College of General Practitioners Patient Safety Toolkit following stakeholder consultations for the pilot phase involving 12 GP practices. Pilot phase interviews showed that reports were used to review individual patient care, implement wider QI actions in the practice, and for appraisal and revalidation. CONCLUSION: Electronic health record data can be used to provide standardised, reproducible reports that can be delivered at scale with minimal resource requirements. These can be used in a national QI initiative that impacts directly on patient care.

Limitations for health research with restricted data collection from UK primary care.

PURPOSE: UK primary care provides a rich data source for research. The impact of proposed data collection restrictions is unknown. This study aimed to assess the impact of restricting the scope of electronic health record (EHR) data collection on the ability to conduct research. The study estimated the consequences of restricted data collection on published Clinical Practice Research Datalink studies from high impact journals or referenced in clinical guidelines. METHODS: A structured form was used to systematically analyse the extent to which individual studies would have been possible using a database with data collection restrictions in place: (1) retrospective collection of specified diseases only; (2) retrospective collection restricted to a 6- or 12-year period; (3) prospective and retrospective collection restricted to non-sensitive data. Outcomes were categorised as unfeasible (not reproducible without major bias); compromised (feasible with design modification); or unaffected. RESULTS: Overall, 91% studies were compromised with all restrictions in place; 56% studies were unfeasible even with design modification. With restrictions on diseases alone, 74% studies were compromised; 51% were unfeasible. Restricting collection to 6/12 years had a major impact, with 67 and 22% of studies compromised, respectively. Restricting collection of sensitive data had a lesser but marked impact with 10% studies compromised. CONCLUSION: EHR data collection restrictions can profoundly reduce the capacity for public health research that underpins evidence-based medicine and clinical guidance. National initiatives seeking to collect EHRs should consider the implications of restricting data collection on the ability to address vital public health questions.