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

Macnair, Archie; Love, Sharon; Murray, Macey L; Gilbert, Duncan C.; Parmar, Mahesh; Denwood, Tom; Carpenter, James; Sydes, Matthew R.; Langley, Ruth E.; Cafferty, Fay

doi:10.1186/s13063-021-05295-5

Cited by 20 publications

(16 citation statements)

References 16 publications

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“…Compared to traditional RCTs, those using routine data have been shown to generate additional insights [54]. However, getting access to data from administrative databases, electronic health records, and registries is often not straightforward [55]. If such data is accessible and considered in a RCT, characteristics should be reported not only for trial participants, but also for nonparticipants, as explicitly stated in CONSORT-ROUTINE item 15 [13].…”

Section: Discussionmentioning

confidence: 99%

Generalizability and reach of a randomized controlled trial to improve oral health among home care recipients: comparing participants and nonparticipants at baseline and during follow-up

Czwikla

Herzberg

Kapp

et al. 2022

Trials

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Background The generalizability of randomized controlled trials (RCTs) with a low response can be limited by systematic differences between participants and nonparticipants. This participation bias, however, is rarely investigated because data on nonparticipants is usually not available. The purpose of this article is to compare all participants and nonparticipants of a RCT to improve oral health among home care recipients at baseline and during follow-up using claims data. Methods Seven German statutory health and long-term care insurance funds invited 9656 home care recipients to participate in the RCT MundPflege. Claims data for all participants (n = 527, 5.5% response) and nonparticipants (n = 9129) were analyzed. Associations between trial participation and sex, age, care dependency, number of Elixhauser diseases, and dementia, as well as nursing, medical, and dental care utilization at baseline, were investigated using multivariable logistic regression. Associations between trial participation and the probability of (a) moving into a nursing home, (b) being hospitalized, and (c) death during 1 year of follow-up were examined via Cox proportional hazards regressions, controlling for baseline variables. Results At baseline, trial participation was positively associated with male sex (odds ratio 1.29 [95% confidence interval 1.08–1.54]), high (vs. low 1.46 [1.15–1.86]) care dependency, receiving occasional in-kind benefits to relieve caring relatives (1.45 [1.15–1.84]), having a referral by a general practitioner to a medical specialist (1.62 [1.21–2.18]), and dental care utilization (2.02 [1.67–2.45]). It was negatively associated with being 75–84 (vs. < 60 0.67 [0.50–0.90]) and 85 + (0.50 [0.37–0.69]) years old. For morbidity, hospitalizations, and formal, respite, short-term, and day or night care, no associations were found. During follow-up, participants were less likely to move into a nursing home than nonparticipants (hazard ratio 0.50 [0.32–0.79]). For hospitalizations and mortality, no associations were found. Conclusions For half of the comparisons, differences between participants and nonparticipants were observed. The RCT’s generalizability is limited, but to a smaller extent than one would expect because of the low response. Routine data provide a valuable source for investigating potential differences between trial participants and nonparticipants, which might be used by future RCTs to evaluate the generalizability of their findings. Trial registration German Clinical Trials Register DRKS00013517. Retrospectively registered on June 11, 2018.

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Section: Discussionmentioning

confidence: 99%

Generalizability and reach of a randomized controlled trial to improve oral health among home care recipients: comparing participants and nonparticipants at baseline and during follow-up

Czwikla

Herzberg

Kapp

et al. 2022

Trials

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“…Achieving this transfer can be challenging. A recent UK study in two trials, Add-Aspirin and PATCH, found that it took 13 months for Add-Aspirin to receive data from the National Cancer Registration and Analysis Service and 15 months for PATCH to receive data from NHS Digital 20 . In another example, changing interpretation of information governance regulations by data meant that the team behind the EPOCH trial were unable to gain access to post-discharge hospital data in Wales and had to change their primary analysis because of it 21 .…”

Section: Discussionmentioning

confidence: 99%

A good use of time? Providing evidence for how effort is invested in primary and secondary outcome data collection in trials

Gardner

Feky

Pickles

et al. 2022

Preprint

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BackgroundData collection is a substantial part of trial workload for participants and staff alike. How these hours of work are spent is important because stakeholders are more interested in some outcomes than others. The ORINOCO study compared the time spent collecting primary outcome data to the time spent collecting secondary outcome data in a cohort of trials.MethodsWe searched PubMed for phase III trials indexed between 2015 and 2019. From these, we randomly selected 120 trials evaluating a therapeutic intervention plus an additional random selection of 20 trials evaluating a public health intervention. We also added eligible trials from a cohort of 189 trials in rheumatology that had used the same core outcome set.We then obtained the time taken to collect primary and secondary outcomes in each trial. We used a hierarchy of methods that included data in trial reports, contacting the trial team, and approaching individuals with experience of using the identified outcome measures. We calculated the primary:secondary data collection time ratio and notional data collection cost for each included trial.ResultsWe included 161 trials (120 Phase III; 21 Core outcome set; 20 Public health), which together collected 230 primary and 688 secondary outcomes. Full primary and secondary timing data were obtained for 134 trials. The median time spent on primaries was 56 hours (range 0.0 – 10,747) and the median time spent on secondaries was 191 hours (range 0.0 – 1,356,833). The median primary:secondary data collection time ratio was 1:3.0 (i.e. for every minute spent on primary outcomes, 3.0 were spent on secondaries. The ratio varied by trial type: Phase III trials were 1: 3.1, Core outcome set 1:3.4 and Public health trials 1:2.2. The median notional overall data collection cost was £8,016 (range £53 – £31,899,141).ConclusionsDepending on trial type, between two and three times as much time is spent collecting secondary outcome data than collecting primary outcome data. Trial teams should explicitly consider how long it will take to collect the data for an outcome and decide whether that time is worth it given importance of the outcome to the trial.

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“…Many challenges highlighted here have been anecdotally reported in relation to specific projects or data providers [9,11,25]. Through this work, we have identified the broader current issues relating to working with administrative data, as well as developing a more detailed understanding and context around known issues by working with both researchers and data providers.…”

Section: Other Ongoing Workmentioning

confidence: 96%

“…Despite the increased availability of data and interest from funding bodies, there remain challenges for data access, storage and sharing, and difficulties in conducting crossnational research [2,[8][9][10][11]. In addition, accessing data from multiple data providers remains a challenge with different applications, requirements and governance across providers [9].…”

Section: Introductionmentioning

confidence: 99%

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

Lugg-Widger

Munnery

Townson

et al. 2022

IJPDS

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BackgroundThe 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. MethodsA 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. Results107 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. ConclusionThe 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.

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

Cited by 20 publications

References 16 publications

Generalizability and reach of a randomized controlled trial to improve oral health among home care recipients: comparing participants and nonparticipants at baseline and during follow-up

Generalizability and reach of a randomized controlled trial to improve oral health among home care recipients: comparing participants and nonparticipants at baseline and during follow-up

A good use of time? Providing evidence for how effort is invested in primary and secondary outcome data collection in trials

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

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