Will Apple devices' passive atrial fibrillation detection prevent strokes? Estimating the proportion of high-risk actionable patients with real-world user data. (22nd February 2022)
- Record Type:
- Journal Article
- Title:
- Will Apple devices' passive atrial fibrillation detection prevent strokes? Estimating the proportion of high-risk actionable patients with real-world user data. (22nd February 2022)
- Main Title:
- Will Apple devices' passive atrial fibrillation detection prevent strokes? Estimating the proportion of high-risk actionable patients with real-world user data
- Authors:
- Feldman, Keith
Duncan, Ray G
Nguyen, An
Cook-Wiens, Galen
Elad, Yaron
Nuckols, Teryl
Pevnick, Joshua M - Abstract:
- Abstract: Objective: Utilizing 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 Methods: This 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. Results: Based 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 Conclusion: These 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 atAbstract: Objective: Utilizing 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 Methods: This 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. Results: Based 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 Conclusion: These 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. … (more)
- Is Part Of:
- Journal of the American Medical Informatics Association. Volume 29:Number 6(2022)
- Journal:
- Journal of the American Medical Informatics Association
- Issue:
- Volume 29:Number 6(2022)
- Issue Display:
- Volume 29, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 29
- Issue:
- 6
- Issue Sort Value:
- 2022-0029-0006-0000
- Page Start:
- 1040
- Page End:
- 1049
- Publication Date:
- 2022-02-22
- Subjects:
- atrial fibrillation -- mobile health (mHealth) -- precision health -- patient-generated data
Medical informatics -- Periodicals
Information Services -- Periodicals
Medical Informatics -- Periodicals
Médecine -- Informatique -- Périodiques
Informatica
Geneeskunde
Informatique médicale
Computer network resources
Electronic journals
610.285 - Journal URLs:
- http://jamia.bmj.com/ ↗
http://www.jamia.org ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=76 ↗
http://www.sciencedirect.com/science/journal/10675027 ↗
http://jamia.oxfordjournals.org/ ↗
http://www.oxfordjournals.org/en/ ↗ - DOI:
- 10.1093/jamia/ocac009 ↗
- Languages:
- English
- ISSNs:
- 1067-5027
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4689.025000
British Library DSC - BLDSS-3PM
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