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

Kimberly A. Mc Cord, Rustam Al-Shahi Salman, Shaun P Treweek, Heidi Rebecca Gardner, Daniel Strech, William Whiteley, John P. A. Ioannidis, Lars Hemkens (Corresponding Author)

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Abstract

Routinely 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.
Original languageEnglish
Article number29
JournalTrials
Volume19
DOIs
Publication statusPublished - 11 Jan 2018

Bibliographical note

This work was supported by Stiftung Institut für klinische Epidemiologie. The Meta-Research Innovation Center at Stanford University is funded by a grant from the Laura and John Arnold Foundation. The funders had no role in design and conduct of the study; the collection, management, analysis, or interpretation of the data; or the preparation, review, or approval of the manuscript or its submission for publication.

Keywords

  • routinely collected health data
  • electronic health records
  • registries
  • evidence-based medicine
  • trials
  • clinical epidemiology

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