Observational studyJournal of the American Medical Informatics Association : JAMIA2022
Will Apple devices' passive atrial fibrillation detection prevent strokes? Estimating the proportion of high-risk actionable patients with real-world user data.
Observational study in Journal of the American Medical Informatics Association : JAMIA, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Digital Health Solutions for Cardiovascular Disease Prevention: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Patient engagement with consumer wearable devices in the electronic health record.Frontiers in digital health · 2026Article
- Predicting Engagement Patterns With Connected Wearable Devices in a Health System: Survival Analysis.Journal of medical Internet research · 2025Article
- The Honest Enterprise Research Broker: Facilitating Ethical, Efficient, and Secure Access to Health Data for Research.Applied clinical informatics · 2025Article
- Individualized prediction of atrial fibrillation onset risk based on lifelogs.American journal of preventive cardiology · 2025Article
- Detection of Arrhythmias Using Smartwatches-A Systematic Literature Review.Healthcare (Basel, Switzerland) · 2024Review
- Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study.JMIR medical informatics · 2024Article
- Article
- Review
- Review
- Centering the patient in informatics applications.Journal of the American Medical Informatics Association : JAMIA · 2022Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveUtilizing integrated electronic health record (EHR) and consumer-grade wearable device data, we sought to provide real-world estimates for the proportion of wearers that would likely benefit from anticoagulation if an atrial fibrillation (AFib) diagnosis was made based on wearable device data. MATERIALS AND
methodsThis study utilized EHR and Apple Watch data from an observational cohort of 1802 patients at Cedars-Sinai Medical Center who linked devices to the EHR between April 25, 2015 and November 16, 2018. Using these data, we estimated the number of high-risk patients who would be actionable for anticoagulation based on (1) medical history, (2) Apple Watch wear patterns, and (3) AFib risk, as determined by an existing validated model.
resultsBased on the characteristics of this cohort, a mean of 0.25% (n = 4.58, 95% CI, 2.0-8.0) of patients would be candidates for new anticoagulation based on AFib identified by their Apple Watch. Using EHR data alone, we find that only approximately 36% of the 1802 patients (n = 665.93, 95% CI, 626.0-706.0) would have anticoagulation recommended even after a new AFib diagnosis. DISCUSSION AND
conclusionThese data suggest that there is limited benefit to detect and treat AFib with anticoagulation among this cohort, but that accessing clinical and demographic data from the EHR could help target devices to the patients with the highest potential for benefit. Future research may analyze this relationship at other sites and among other wearable users, including among those who have not linked devices to their EHR.
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Registered trials
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