Evidence map›Paper›PMID 29325575›Full record

ReviewTrials2018

Routinely collected data for randomized trials: promises, barriers, and implications.

Kimberly A Mc Cord, Rustam Al-Shahi Salman, Shaun Treweek, Heidi Gardner, Daniel Strech, William Whiteley, John P A Ioannidis, Lars G Hemkens

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Trials, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

78 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Use of pragmatic randomized trials in multiple sclerosis: A systematic overview.Multiple sclerosis (Houndmills, Basingstoke, England) · 2024
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18 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Kimberly A Mc CordBasel Institute for Clinical Epidemiology and Biostatistics (CEB), Department of Clinical Research, University Hospital Basel, University of Basel, Spitalstrasse 12, 4031, Basel, Switzerland.
Rustam Al-Shahi SalmanCentre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK.
Shaun TreweekHealth Services Research Unit, University of Aberdeen, Aberdeen, AB25 2ZD, UK.
Heidi GardnerHealth Services Research Unit, University of Aberdeen, Aberdeen, AB25 2ZD, UK.
Daniel StrechInstitute for History, Ethics and Philosophy of Medicine, Hannover Medical School, 30625, Hannover, Germany.
William WhiteleyCentre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK.
John P A IoannidisStanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Lars G HemkensBasel Institute for Clinical Epidemiology and Biostatistics (CEB), Department of Clinical Research, University Hospital Basel, University of Basel, Spitalstrasse 12, 4031, Basel, Switzerland. lars.hemkens@usb.ch.

Funding

British Heart Foundation CS/18/2/33719Chief Scientist Office HSRU1Chief Scientist Office SCAF/17/01Medical Research Council G1002605The Dunhill Medical Trust R380R/1114
6 · The paper itself

Abstract

backgroundRoutinely collected health data (RCD) are increasingly used for randomized controlled trials (RCTs). This can provide three major benefits: increasing value through better feasibility (reducing costs, time, and resources), expanding the research agenda (performing trials for research questions otherwise not amenable to trials), and offering novel design and data collection options (e.g., point-of-care trials and other designs directly embedded in routine care). However, numerous hurdles and barriers must be considered pertaining to regulatory, ethical, and data aspects, as well as the costs of setting up the RCD infrastructure. Methodological considerations may be different from those in traditional RCTs: RCD are often collected by individuals not involved in the study and who are therefore blinded to the allocation of trial participants. Another consideration is that RCD trials may lead to greater misclassification biases or dilution effects, although these may be offset by randomization and larger sample sizes. Finally, valuable insights into external validity may be provided when using RCD because it allows pragmatic trials to be performed.

methodsWe provide an overview of the promises, challenges, and potential barriers, methodological implications, and research needs regarding RCD for RCTs.

resultsRCD have substantial potential for improving the conduct and reducing the costs of RCTs, but a multidisciplinary approach is essential to address emerging practical barriers and methodological implications.

conclusionsFuture research should be directed toward such issues and specifically focus on data quality validation, alternative research designs and how they affect outcome assessment, and aspects of reporting and transparency.

Indexed as

Data CollectionRandomized Controlled Trials as TopicEthics, ResearchHumansResearch DesignClinical epidemiologyElectronic health recordsEvidence-based medicineRegistriesRoutinely collected health dataTrials

Identifiers

PMID29325575
PMCPMC5765645

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.