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Lessons learned in the Apple Heart Study and implications for the data management of future digital clinical trials

  • Ariadna Garcia
  • , Vidhya Balasubramanian
  • , Justin Lee
  • , Rebecca Gardner
  • , Santosh Gummidipundi
  • , Grace Hung
  • , Todd Ferris
  • , Lauren Cheung
  • , Christopher Granger
  • , Peter Kowey
  • , John Rumsfeld
  • , Andrea Russo
  • , Mellianie Ture Hills
  • , Nisha Talati
  • , Divya Nag
  • , Jeffrey Stein
  • , David Tsay
  • , Sumbul Desai
  • , Kenneth Mahaffey
  • , Mintu Turakhia
  • Marco Perez, Haley Hedlin, Manisha Desai

Research output: Contribution to journalArticlepeer-review

Abstract

The digital clinical trial is fast emerging as a pragmatic trial that can improve a trial’s design including recruitment and retention, data collection and analytics. To that end, digital platforms such as electronic health records or wearable technologies that enable passive data collection can be leveraged, alleviating burden from the participant and study coordinator. However, there are challenges. For example, many of these data sources not originally intended for research may be noisier than traditionally obtained measures. Further, the secure flow of passively collected data and their integration for analysis is non-trivial. The Apple Heart Study was a prospective, single-arm, site-less digital trial designed to evaluate the ability of an app to detect atrial fibrillation. The study was designed with pragmatic features, such as an app for enrollment, a wearable device (the Apple Watch) for data collection, and electronic surveys for participant-reported outcomes that enabled a high volume of patient enrollment and accompanying data. These elements led to challenges including identifying the number of unique participants, maintaining participant-level linkage of multiple complex data streams, and participant adherence and engagement. Novel solutions were derived that inform future designs with an emphasis on data management. We build upon the excellent framework of the Clinical Trials Transformation Initiative to provide a comprehensive set of guidelines for data management of the digital clinical trial that include an increased role of collaborative data scientists in the design and conduct of the modern digital trial.

Original languageEnglish (US)
Pages (from-to)496-510
Number of pages15
JournalJournal of Biopharmaceutical Statistics
Volume32
Issue number3
DOIs
StatePublished - 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)

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