Abstract
AbstractThe Sentinel System is a major component of the United States Food and Drug Administration’s (FDA) approach to active medical product safety surveillance. While Sentinel has historically relied on large quantities of health insurance claims data, leveraging longitudinal electronic health records (EHRs) that contain more detailed clinical information, as structured and unstructured features, may address some of the current gaps in capabilities. We identify key challenges when using EHR data to investigate medical product safety in a scalable and accelerated way, outline potential solutions, and describe the Sentinel Innovation Center’s initiatives to put solutions into practice by expanding and strengthening the existing system with a query-ready, large-scale data infrastructure of linked EHR and claims data. We describe our initiatives in four strategic priority areas: (1) data infrastructure, (2) feature engineering, (3) causal inference, and (4) detection analytics, with the goal of incorporating emerging data science innovations to maximize the utility of EHR data for medical product safety surveillance.
Funder
U.S. Department of Health & Human Services | U.S. Food and Drug Administration
Publisher
Springer Science and Business Media LLC
Subject
Health Information Management,Health Informatics,Computer Science Applications,Medicine (miscellaneous)
Reference29 articles.
1. Ball, R., Robb, M., Anderson, S. & Dal Pan, G. The FDA’s sentinel initiative—a comprehensive approach to medical product surveillance. Clin. Pharmacol. Therapeutics. 99, 265–268 (2016).
2. Platt, R. et al. The FDA Sentinel Initiative—an evolving national resource. N. Engl. J. Med. 379, 2091–2093 (2018).
3. Sentinel Initiative [Internet]. FDA Advisory Committee Meetings; 2021. https://www.sentinelinitiative.org/communications/fda-advisory-committee-meetings. Accessed March 1, 2021.
4. Sentinel Initiative [Internet]. FDA Safety Communications; 2021. https://www.sentinelinitiative.org/communications/fda-safety-communications. Accessed March 1, 2021
5. Brown, J. S., Maro, J. C., Nguyen, M. & Ball, R. Using and improving distributed data networks to generate actionable evidence: the case of real-world outcomes in the Food and Drug Administration’s Sentinel system. J. Am. Med. Inform. Assoc. 27, 793–797 (2020).
Cited by
33 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献