Access to routinely collected health data for clinical trials - review of successful data requests to UK registries

Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials

BACKGROUND

Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.

METHODS-AND-RESULTS

Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status.

DISCUSSION

DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.

Navigating the complexities of drug development for inflammatory bowel disease

Inflammatory bowel disease (IBD) - consisting of ulcerative colitis and Crohn's disease - is a complex, heterogeneous, immune-mediated inflammatory condition with a multifactorial aetiopathogenesis. Despite therapeutic advances in this arena, a ceiling effect has been reached with both single-agent monoclonal antibodies and advanced small molecules. Therefore, there is a need to identify novel targets, and the development of companion biomarkers to select responders is vital. In this Perspective, we examine how advances in machine learning and tissue engineering could be used at the preclinical stage where attrition rates are high. For novel agents reaching clinical trials, we explore factors decelerating progression, particularly the decline in IBD trial recruitment, and assess how innovative approaches such as reconfiguring trial designs, harmonizing end points and incorporating digital technologies into clinical trials can address this. Harnessing opportunities at each stage of the drug development process may allow for incremental gains towards more effective therapies.

The use of linked administrative data in Australian randomised controlled trials: A scoping review

BACKGROUND/AIMS

The demand for simplified data collection within trials to increase efficiency and reduce costs has led to broader interest in repurposing routinely collected administrative data for use in clinical trials research. The aim of this scoping review is to describe how and why administrative data have been used in Australian randomised controlled trial conduct and analyses, specifically the advantages and limitations of their use as well as barriers and enablers to accessing administrative data for use alongside randomised controlled trials.

METHODS

Databases were searched to November 2022. Randomised controlled trials were included if they accessed one or more Australian administrative data sets, where some or all trial participants were enrolled in Australia, and where the article was published between January 2000 and November 2022. Titles and abstracts were independently screened by two reviewers, and the full texts of selected studies were assessed against the eligibility criteria by two independent reviewers. Data were extracted from included articles by two reviewers using a data extraction tool.

RESULTS

Forty-one articles from 36 randomised controlled trials were included. Trial characteristics, including the sample size, disease area, population, and intervention, were varied; however, randomised controlled trials most commonly linked to government reimbursed claims data sets, hospital admissions data sets and birth/death registries, and the most common reason for linkage was to ascertain disease outcomes or survival status, and to track health service use. The majority of randomised controlled trials were able to achieve linkage in over 90% of trial participants; however, consent and participant withdrawals were common limitations to participant linkage. Reported advantages were the reliability and accuracy of the data, the ease of long term follow-up, and the use of established data linkage units. Common reported limitations were locating participants who had moved outside the jurisdictional area, missing data where consent was not provided, and unavailability of certain healthcare data.

CONCLUSIONS

As linked administrative data are not intended for research purposes, detailed knowledge of the data sets is required by researchers, and the time delay in receiving the data is viewed as a barrier to its use. The lack of access to primary care data sets is viewed as a barrier to administrative data use; however, work to expand the number of healthcare data sets that can be linked has made it easier for researchers to access and use these data, which may have implications on how randomised controlled trials will be run in future.

The use of healthcare systems data for RCTs

BACKGROUND

Healthcare systems data (HSD) has the potential to optimise the efficiency of randomised controlled trials (RCTs), by decreasing trial-specific data demands. Therefore, the use of HSD in trials is expected to increase. In 2019, it was estimated that 47% of NIHR-funded trials were planning to use HSD. We aim to understand the extent and nature of its current use and its evolution over time.

METHODS

We identified a cohort of RCTs within the NIHR Journals Library that commenced after 2019 and were described as being in progress on 6 June 2022. Details on the source and use of HSD were extracted from eligible RCTs. The use of HSD was categorised according to whether it was used as the sole data source for outcomes and whether the outcomes were primary or secondary. HSD is often insufficient for patient-reported outcomes (PROs). We aimed to determine methods used by trialists for collecting PRO data alongside HSD.

RESULTS

Of the 84 eligible studies, 52 (62%) planned to use HSD and 79 (94%) planned to collect PROs. The number of RCTs planning to use HSD for at least one outcome was 28 (54%) with 24 of these planning to use HSD as the sole data source for at least one outcome. The number of studies planning to use HSD for primary and secondary outcomes was 10 (20%) and 21 (40%) respectively. The sources of HSD were National Health Service (NHS) Digital (n = 37, 79%), patient registries (n = 7, 29%), primary care (n = 5, 21%), The Office for National Statistics (ONS) (n = 3, 13%) and other (n = 2, 8%). PROs were collected for 92% of the trials planning to use HSD. Methods for collection of PROs included in-person (n = 26, 54%), online (n = 22, 46%), postal (n = 18, 38%), phone (n = 14, 29%) and app (n = 2, 4%).

CONCLUSIONS

HSD is being used in around two thirds of the studies but cannot yet be used to support PRO data collection within the cohort we examined. Comparison with an earlier cohort demonstrates an increase in the number of RCTs planning to use HSD.

Using healthcare systems data for outcomes in clinical trials: issues to consider at the design stage

BACKGROUND

Healthcare system data (HSD) are increasingly used in clinical trials, augmenting or replacing traditional methods of collecting outcome data. This study, PRIMORANT, set out to identify, in the UK context, issues to be considered before the decision to use HSD for outcome data in a clinical trial is finalised, a methodological question prioritised by the clinical trials community.

METHODS

The PRIMORANT study had three phases. First, an initial workshop was held to scope the issues faced by trialists when considering whether to use HSDs for trial outcomes. Second, a consultation exercise was undertaken with clinical trials unit (CTU) staff, trialists, methodologists, clinicians, funding panels and data providers. Third, a final discussion workshop was held, at which the results of the consultation were fed back, case studies presented, and issues considered in small breakout groups.

RESULTS

Key topics included in the consultation process were the validity of outcome data, timeliness of data capture, internal pilots, data-sharing, practical issues, and decision-making. A majority of consultation respondents (n = 78, 95%) considered the development of guidance for trialists to be feasible. Guidance was developed following the discussion workshop, for the five broad areas of terminology, feasibility, internal pilots, onward data sharing, and data archiving.

CONCLUSIONS

We provide guidance to inform decisions about whether or not to use HSDs for outcomes, and if so, to assist trialists in working with registries and other HSD providers to improve the design and delivery of trials.

Insights from UKCTOCS for design, conduct and analyses of large randomised controlled trials

Abstract

Randomised controlled trials are challenging to deliver. There is a constant need to review and refine recruitment and implementation strategies if they are to be completed on time and within budget. We present the strategies adopted in the United Kingdom Collaborative Trial of Ovarian Cancer Screening, one of the largest individually randomised controlled trials in the world. The trial recruited over 202,000 women (2001-5) and delivered over 670,000 annual screens (2001-11) and over 3 million women-years of follow-up (2001-20). Key to the successful completion were the involvement of senior investigators in the day-to-day running of the trial, proactive trial management and willingness to innovate and use technology. Our underlying ethos was that trial participants should always be at the centre of all our processes. We ensured that they were able to contact either the site or the coordinating centre teams for clarifications about their results, for follow-up and for rescheduling of appointments. To facilitate this, we shared personal identifiers (with consent) with both teams and had dedicated reception staff at both site and coordinating centre. Key aspects were a comprehensive online trial management system which included an electronic data capture system (resulting in an almost paperless trial), biobanking, monitoring and project management modules. The automation of algorithms (to ascertain eligibility and classify results and ensuing actions) and processes (scheduling of appointments, printing of letters, etc.) ensured the protocol was closely followed and timelines were met. Significant engagement with participants ensured retention and low rates of complaints. Our solutions to the design, conduct and analyses issues we faced are highly relevant, given the renewed focus on trials for early detection of cancer.

Future work

There is a pressing need to increase the evidence base to support decision making about all aspects of trial methodology.

Trial registration

ISRCTN-22488978; ClinicalTrials.gov-NCT00058032.

Funding

This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 16/46/01. The long-term follow-up UKCTOCS (2015 20) was supported by National Institute for Health and Care Research (NIHR HTA grant 16/46/01), Cancer Research UK, and The Eve Appeal. UKCTOCS (2001-14) was funded by the MRC (G9901012 and G0801228), Cancer Research UK (C1479/A2884), and the UK Department of Health, with additional support from The Eve Appeal. Researchers at UCL were supported by the NIHR UCL Hospitals Biomedical Research Centre and by the MRC Clinical Trials Unit at UCL core funding (MC_UU_00004/09, MC_UU_00004/08, MC_UU_00004/07). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the UK Department of Health and Social Care.

Leveraging Virtual Technology to Conduct Clinical Trials in Inflammatory Bowel Disease

Clinical trials have led to major advances in inflammatory bowel disease (IBD) care over the last few decades, yet in that time most clinical trial protocols in IBD have remained markedly the same. Many IBD protocols often still require face-to-face visits and monitoring, hospital-based medication administration, paper-based forms and questionnaires, and short follow-up periods resulting in limited long-term data. These factors have recently been recognized as likely contributors to the low recruitment and lack of diversity of participants across clinical trials in IBD. However, with increasing technological advances, there is now an opportunity for improvement. This article assesses a range of virtual innovations for how they may offer digital solutions to challenges currently encountered in IBD clinical trials. Such solutions include consideration for increasing patient diversity, digital invitation, remote consent and recruitment, virtual visits, remote patient monitoring and data collection, remote medication delivery and administration, remote clinical trial monitoring, and routinely collected health data for long-term follow-up. Adoption of virtual technology may drive the field toward patient centricity and more efficient trial protocols to allow for a new era in IBD clinical trials.

Electronic health records to capture primary outcome measures: two case studies in HIV prevention research

BACKGROUND

There is increasing interest in the use of electronic health records (EHRs) to improve the efficiency and cost-effectiveness of clinical trials, including the capture of outcome measures.

MAIN TEXT

We describe our experience of using EHRs to capture the primary outcome measure - HIV infection or the diagnosis of HIV infection - in two randomised HIV prevention trials conducted in the UK. PROUD was a clinic-based trial evaluating pre-exposure prophylaxis (PrEP), and SELPHI was an internet-based trial evaluating HIV self-testing kits. The EHR was the national database of HIV diagnoses in the UK, curated by the UK Health Security Agency (UKHSA). In PROUD, linkage to the UKHSA database was performed at the end of the trial and identified five primary outcomes in addition to the 30 outcomes diagnosed by the participating clinics. Linkage also produced an additional 345 person-years follow-up, an increase of 27% over clinic-based follow-up. In SELPHI, new HIV diagnoses were primarily identified via UKHSA linkage, complemented by participant self-report through internet surveys. Rates of survey completion were low, and only 14 of the 33 new diagnoses recorded in the UKHSA database were also self-reported. Thus UKHSA linkage was essential for capturing HIV diagnoses and the successful conduct of the trial.

CONCLUSIONS

Our experience of using the UKHSA database of HIV diagnoses as a source of primary outcomes in two randomised trials in the field of HIV prevention was highly favourable and encourages the use of a similar approach in future trials in this disease area.

A DELPHI study priority setting the remaining challenges for the use of routinely collected data in trials: COMORANT-UK

BACKGROUND

Researchers are increasingly seeking to use routinely collected data to support clinical trials. This approach has the potential to transform the way clinical trials are conducted in the future. The availability of routinely collected data for research, whether healthcare or administrative, has increased, and infrastructure funding has enabled much of this. However, challenges remain at all stages of a trial life cycle. This study, COMORANT-UK, aimed to systematically identify, with key stakeholders across the UK, the ongoing challenges related to trials that seek to use routinely collected data.

METHODS

This three-step Delphi method consisted of two rounds of anonymous web-based surveys and a virtual consensus meeting. Stakeholders included trialists, data infrastructures, funders of trials, regulators, data providers and the public. Stakeholders identified research questions or challenges that they considered were of particular importance and then selected their top 10 in the second survey. The ranked questions were taken forward to the consensus meeting for discussion with representatives invited from the stakeholder groups.

RESULTS

In the first survey, 66 respondents yielded over 260 questions or challenges. These were thematically grouped and merged into a list of 40 unique questions. Eighty-eight stakeholders then ranked their top ten from the 40 questions in the second survey. The most common 14 questions were brought to the virtual consensus meeting in which stakeholders agreed a top list of seven questions. We report these seven questions which are within the following domains: trial design, Patient and Public Involvement, trial set-up, trial open and trial data. These questions address both evidence gaps (requiring further methodological research) and implementation gaps (requiring training and/or service re-organisation).

CONCLUSION

This prioritised list of seven questions should inform the direction of future research in this area and should direct efforts to ensure that the benefits in major infrastructure for routinely collected data are achieved and translated. Without this and future work to address these questions, the potential societal benefits of using routinely collected data to help answer important clinical questions will not be realised.

Quantifying the primary and secondary effects of antimicrobial resistance on surgery patients: Methods and data sources for empirical estimation in England

Antimicrobial resistance (AMR) may negatively impact surgery patients through reducing the efficacy of treatment of surgical site infections, also known as the "primary effects" of AMR. Previous estimates of the burden of AMR have largely ignored the potential "secondary effects," such as changes in surgical care pathways due to AMR, such as different infection prevention procedures or reduced access to surgical procedures altogether, with literature providing limited quantifications of this potential burden. Former conceptual models and approaches for quantifying such impacts are available, though they are often high-level and difficult to utilize in practice. We therefore expand on this earlier work to incorporate heterogeneity in antimicrobial usage, AMR, and causative organisms, providing a detailed decision-tree-Markov-hybrid conceptual model to estimate the burden of AMR on surgery patients. We collate available data sources in England and describe how routinely collected data could be used to parameterise such a model, providing a useful repository of data systems for future health economic evaluations. The wealth of national-level data available for England provides a case study in describing how current surveillance and administrative data capture systems could be used in the estimation of transition probability and cost parameters. However, it is recommended that such data are utilized in combination with expert opinion (for scope and scenario definitions) to robustly estimate both the primary and secondary effects of AMR over time. Though we focus on England, this discussion is useful in other settings with established and/or developing infectious diseases surveillance systems that feed into AMR National Action Plans.

Quantifying the primary and secondary effects of antimicrobial resistance on surgery patients: Methods and data sources for empirical estimation in England

Antimicrobial resistance (AMR) may negatively impact surgery patients through reducing the efficacy of treatment of surgical site infections, also known as the “primary effects” of AMR. Previous estimates of the burden of AMR have largely ignored the potential “secondary effects,” such as changes in surgical care pathways due to AMR, such as different infection prevention procedures or reduced access to surgical procedures altogether, with literature providing limited quantifications of this potential burden. Former conceptual models and approaches for quantifying such impacts are available, though they are often high-level and difficult to utilize in practice. We therefore expand on this earlier work to incorporate heterogeneity in antimicrobial usage, AMR, and causative organisms, providing a detailed decision-tree-Markov-hybrid conceptual model to estimate the burden of AMR on surgery patients. We collate available data sources in England and describe how routinely collected data could be used to parameterise such a model, providing a useful repository of data systems for future health economic evaluations. The wealth of national-level data available for England provides a case study in describing how current surveillance and administrative data capture systems could be used in the estimation of transition probability and cost parameters. However, it is recommended that such data are utilized in combination with expert opinion (for scope and scenario definitions) to robustly estimate both the primary and secondary effects of AMR over time. Though we focus on England, this discussion is useful in other settings with established and/or developing infectious diseases surveillance systems that feed into AMR National Action Plans.

Identifying researcher learning needs to develop online training for UK researchers working with administrative data: CENTRIC training

BACKGROUND

The use of administrative data in health and social science research continues to expand, with increased availability of data and interest from funders. Researchers, however, continue to experience delays in access, storage and sharing of administrative data. Training opportunities are limited and typically specific to individual data providers or focussed on the analytical aspects of working with administrative data. The CENTRIC study was funded by the Information Commissioners Office, with the aim of developing a broader training curriculum for researchers working with administrative data in the UK.

METHODS

A mixed-methods design informed curriculum content, including surveys with researchers, focus group discussions with data providers and workshops with members of the public. Researchers were identified from relevant administrative data networks and invited to participate in an online survey identifying training needs. Data providers were approached with a request to input to a face-to-face or online meeting with two members of the research team about their experiences of working with researchers. Data were analysed within the broad framework of the interview schedule, free text responses in the survey were analysed thematically.

RESULTS

107 researchers responded to the online survey and four data providers participated in the focus groups. We identified five main themes, relating to research training needs for UK researchers working with administrative data: communication; timelines; changes & amendments; future-proofing applications; and, the availability of training and support. Data providers either provided additional evidence on these learning needs or ways to address identified challenges. Six modules were developed addressing these training needs. Quotes from the survey and focus groups are used anonymously in the online training modules.

CONCLUSION

The CENTRIC online training curriculum was launched in September 2020 and is available, free of charge for UK researchers. CENTRIC specifically addresses commonly identified training needs of researchers working with administrative data.

Development and evaluation of rapid data-enabled access to routine clinical information to enhance early recruitment to the national clinical platform trial of COVID-19 community treatments

BACKGROUND

The COVID-19 pandemic has presented unique challenges for rapidly designing, initiating, and delivering therapeutic clinical trials. PRINCIPLE (Platform Randomised Trial of Treatments in the Community for Epidemic and Pandemic Illnesses) is the UK national platform investigating repurposed therapies for COVID-19 treatment of older people in the community at high risk of complications. Standard methods of patient recruitment were failing to meet the required pace and scale of enrolment. This paper describes the development and appraisal of a near real-time, data-driven, ethical approach for enhancing recruitment in community care by contacting people with a recent COVID-19 positive test result from the central NHS Test and Trace service within approximately 24-48 h of their test result.

METHODS

A multi-disciplinary team was formed to solve the technical, ethical, public perception, logistical and information governance issues required to provide a near-real time (approximately within 24-48 h of receiving a positive test) feed of potential trial participants from test result data to the research team. PRINCIPLE was also given unique access to the Summary Care Record (SCR) to ensure safe prescribing, and to enable the trial team to quickly and safely bring consented patients into the trial. A survey of the public was used to understand public perceptions of the use of test data for this proposed methodology.

RESULTS

Prior to establishing the data service, PRINCIPLE registered on average 87 participants per week. This increased by up to 87 additional people registered per week from the test data, contributing to an increase from 1013 recruits to PRINCIPLE at the start of October 2020 to 2802 recruits by 20 December 2020. Whilst procedural caveats were identified by the public consultation, out of 2639 people contacted by PRINCIPLE following a positive test result, no one raised a concern about being approached.

CONCLUSIONS

This paper describes a novel approach to using near-real time NHS operational data to recruit community-based patients within a few days of presentation with acute illness. This approach increased recruitment and reduced time between positive test and randomisation, allowing more rapid evaluation of treatments and increased safety for participants. End-to-end public and patient involvement in the design of the approach provided evidence to inform information governance decisions.

TRIAL REGISTRATION

PRINCIPLE is funded by UK Research and Innovation and the Department of Health and Social Care through the National Institute for Health Research. EudraCT number: 2020-001209-22 . 26/03/2020 ISRCTN registry: ISRCTN86534580 . 20/03/2020 REC number: 20/SC/058 IRAS number: 281958.

Conducting Randomized Controlled Trials of Complex Interventions in Prisons: A Sisyphean Task?

Randomized Controlled Trials (RCT) are the "gold standard" for measuring the effectiveness of an intervention. However, they have their limitations and are especially complex in prison settings. Several systematic reviews have highlighted some of the issues, including, institutional constraints e.g., "lock-downs," follow-ups, contamination of allocation conditions and a reliance on self-report measures. In this article, we reflect on our experiences and will describe two RCTs. People in prison are a significantly disadvantaged and vulnerable group, ensuring equitable and effective interventions is key to reducing inequality and promoting positive outcomes. We ask are RCTs of complex interventions in prisons a sisyphean task? We certainly don't think so, but we propose that current accepted practice and research designs may be limiting our understanding and ability to test complex interventions in the real-world context of prisons. RCTs will always have their place, but designs need to be flexible and adaptive, with the development of other rigorous methods for evaluating impact of interventions e.g., non-randomized studies, including pre-post implementation studies. With robust research we can deliver quality evidence-based healthcare in prisons - after all the degree of civilization in a society is revealed by entering its prisons.

Comparison of the Accuracy and Completeness of Records of Serious Vascular Events in Routinely Collected Data vs Clinical Trial-Adjudicated Direct Follow-up Data in the UK: Secondary Analysis of the ASCEND Randomized Clinical Trial

Importance

Routinely collected data could substantially decrease the cost of conducting trials.

Objective

To assess the accuracy and completeness of UK routine data for ascertaining serious vascular events (SVEs) compared with adjudicated follow-up data.

Design, Setting, and Participants

This was a secondary analysis of a randomized clinical trial. From June 24, 2005, to July 28, 2011, the ASCEND (A Study of Cardiovascular Events in Diabetes) primary prevention trial used mail-based methods to randomize people with diabetes without evidence of atherosclerotic vascular disease using a 2 × 2 factorial design to aspirin and/or ω-fatty acids vs matching placebo in the UK. Direct participant mail-based follow-up was the main source of outcome data, with more than 90% of the primary outcome events undergoing adjudication. Follow-up was completed on July 31, 2017. In parallel, more than 99% of participants were linked to routinely collected hospital admission and death registry data (ie, routine data), enabling post hoc randomized comparisons of different sources of outcome data (conducted from September 1, 2018, to October 1, 2021).

Interventions

Random allocation to 100 mg of aspirin once daily vs matching placebo and separately to 1 g of ω-3 fatty acids once daily vs placebo.

Main Outcomes and Measures

The primary outcome consisted of SVEs (a composite of nonfatal myocardial infarction, ischemic stroke, transient ischemic attack [TIA], or vascular death, excluding hemorrhagic stroke).

Results

A total of 15 480 participants were randomized (mean [SD] age, 63 [9] years; 9684 [62.6%] men) and followed up for a mean (SD) of 7.4 (1.8) years. For SVEs, agreement between adjudicated direct follow-up and routine data sources was strong (1401 vs 1127 events; κ = 0.78 [95% CI, 0.76-0.80]; sensitivity, 72.0% [95% CI, 69.7%-74.4%]; specificity, 99.2% [95% CI, 99.0%-99.3%]), and sensitivity improved for SVEs excluding transient ischemic attack (1129 vs 1026 events; sensitivity, 80.6% [95% CI, 78.3%-82.9%]). Rate ratios for the aspirin-randomized comparison for adjudicated direct follow-up vs follow-up solely through routine data alone were 0.88 (95% CI, 0.79-0.97) vs 0.91 (95% CI, 0.81-1.02) for the primary outcome and 0.92 (95% CI, 0.82-1.03) vs 0.91 (95% CI, 0.80-1.02) for SVEs excluding TIA. Results were similar for the ω-3 fatty acid comparison, and adjudication did not seem to markedly change rate ratios.

Conclusions and Relevance

Post hoc analyses of the ASCEND trial suggest that routinely collected hospital admission and death registry data in the UK could be used as the sole method of follow-up for myocardial infarction, ischemic stroke resulting in hospitalization, vascular death, and arterial revascularization in primary prevention cardiovascular trials, without the need for verification by clinical adjudication.

Key Learnings from Running an Extension Study to a Real-World Effectiveness Trial: The Extended Salford Lung Study

Introduction

The Salford Lung Studies (SLS) were real-world randomised controlled trials set within UK primary care that assessed the effectiveness and safety of initiating once-daily fluticasone furoate/vilanterol versus continuing usual care in patients with chronic obstructive pulmonary disease or asthma. Data were collected for a relatively short period, limiting the study of long-term outcomes. To broaden the capture of SLS patients’ data, we undertook the Extended SLS (Ext-SLS), aiming to better understand the patient disease journey and the effects of treatment in a real-world setting, through collection of patient-level data. Here, we present study design information and the challenges and learnings gathered in creating the Ext-SLS.

Methods

The Ext-SLS was intended to augment the SLS by collecting retrospective and prospective (up to 10 years from consent) primary and secondary care electronic health record (EHR) data and patient questionnaires. After ethics approval, general practitioners (GPs) obtained consent from SLS patients remotely (mean 3.2 years post-SLS completion). To facilitate GPs identifying eligible patients, a novel EHR-based approach flagged SLS patients who were alive and registered with their original GP. An automated system sent consent forms/questionnaires to patients. Medical data were collected via EHRs; primary care data were extracted from GPs’ systems whilst secondary care data were sourced from the UK NHS.

Results

Of the 75 GP sites from the SLS, 35 (47%) declined Ext-SLS participation leaving 4158 potentially eligible patients; 1169 (28%) patients were excluded as GPs could not confirm them as SLS participants or due to incapacity. Of 2989 patients invited, 1189 (40%) consented.

Conclusions

Developing an EHR-based trial extension was achieved, with reasonable consent rates amongst invited patients. The resulting Ext-SLS is a unique and valuable research resource. Leveraging EHRs and technology reduced GP burden, facilitating participation. Initiation of extension studies prior to study close-out may help increase GP and patient participation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-021-01827-2.

A study protocol for the development of a SPIRIT extension for trials conducted using cohorts and routinely collected data (SPIRIT-ROUTINE)

Background: Protocols are an essential document for conducting randomised controlled trials (RCTs). However, the completeness of the information provided is often inadequate. To help improve the content of trial protocols, an international group of stakeholders published the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) Initiative in 2013. Presently, there is increasing use of cohorts and routinely collected data (RCD) for RCTs because these data have the potential to improve efficiencies by facilitating recruitment, simplifying, and reducing the cost of data collection. Reporting guidelines have been shown to improve the quality of reporting, but there is currently no specific SPIRIT guidance on protocols for trials conducted using cohorts and RCD. This protocol outlines steps for developing SPIRIT-ROUTINE, which aims to address this gap by extending the SPIRIT guidance to protocols for trials conducted using cohorts and RCD.  Methods: The development of the SPIRIT-ROUTINE extension comprises five stages. Stage 1 consists of a project launch and a meeting to finalise the membership of the steering group and scope of the extension. In Stage 2, a rapid review will be performed to identify possible modifications to the original SPIRIT 2013 checklist. Other key reporting guidelines will be reviewed to identify areas where additional items may be needed, such as the Consolidated Standards of Reporting Trials (CONSORT) extension for trials conducted using cohorts and RCD (CONSORT-ROUTINE). Stage 3 will involve an online Delphi exercise, consisting of two rounds and involving key international stakeholders to gather feedback on the preliminary checklist items. In Stage 4, a consensus meeting of the SPIRIT-ROUTINE steering group will finalise the items to include in the extension. Stage 5 will involve the publication preparation and dissemination of the final checklist.  Conclusion: The SPIRIT-ROUTINE extension will contribute to improving design of trials using cohorts and RCD and transparency of reporting.

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.

Accessing routinely collected health data to improve clinical trials: recent experience of access

BACKGROUND

Routinely collected electronic health records (EHRs) have the potential to enhance randomised controlled trials (RCTs) by facilitating recruitment and follow-up. Despite this, current EHR use is minimal in UK RCTs, in part due to ongoing concerns about the utility (reliability, completeness, accuracy) and accessibility of the data. The aim of this manuscript is to document the process, timelines and challenges of the application process to help improve the service both for the applicants and data holders.

METHODS

This is a qualitative paper providing a descriptive narrative from one UK clinical trials unit (MRC CTU at UCL) on the experience of two trial teams' application process to access data from three large English national datasets: National Cancer Registration and Analysis Service (NCRAS), National Institute for Cardiovascular Outcomes Research (NICOR) and NHS Digital to establish themes for discussion. The underpinning reason for applying for the data was to compare EHRs with data collected through case report forms in two RCTs, Add-Aspirin (ISRCTN 74358648) and PATCH (ISRCTN 70406718).

RESULTS

The Add-Aspirin trial, which had a pre-planned embedded sub-study to assess EHR, received data from NCRAS 13 months after the first application. In the PATCH trial, the decision to request data was made whilst the trial was recruiting. The study received data after 8 months from NICOR and 15 months for NHS Digital following final application submission. This concluded in May 2020. Prior to application submission, significant time and effort was needed particularly in relation to the PATCH trial where negotiations over consent and data linkage took many years.

CONCLUSIONS

Our experience demonstrates that data access can be a prolonged and complex process. This is compounded if multiple data sources are required for the same project. This needs to be factored in when planning to use EHR within RCTs and is best considered prior to conception of the trial. Data holders and researchers are endeavouring to simplify and streamline the application process so that the potential of EHR can be realised for clinical trials.