Broadening the reach of the FDA Sentinel system: A roadmap for integrating electronic health record data in a causal analysis framework.


Journal

NPJ digital medicine
ISSN: 2398-6352
Titre abrégé: NPJ Digit Med
Pays: England
ID NLM: 101731738

Informations de publication

Date de publication:
20 Dec 2021
Historique:
received: 23 09 2021
accepted: 28 11 2021
entrez: 21 12 2021
pubmed: 22 12 2021
medline: 22 12 2021
Statut: epublish

Résumé

The 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.

Identifiants

pubmed: 34931012
doi: 10.1038/s41746-021-00542-0
pii: 10.1038/s41746-021-00542-0
pmc: PMC8688411
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

170

Subventions

Organisme : U.S. Department of Health & Human Services | U.S. Food and Drug Administration (U.S. Food & Drug Administration)
ID : 75F40119D10037

Informations de copyright

© 2021. The Author(s).

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Auteurs

Rishi J Desai (RJ)

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. rdesai@bwh.harvard.edu.

Michael E Matheny (ME)

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.

Kevin Johnson (K)

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.

Keith Marsolo (K)

Department of Population Health Sciences, Duke University, Durham, NC, USA.

Lesley H Curtis (LH)

Department of Population Health Sciences, Duke University, Durham, NC, USA.

Jennifer C Nelson (JC)

Biostatistics Unit, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.

Patrick J Heagerty (PJ)

Department of Biostatistics, University of Washington, Seattle, WA, USA.

Judith Maro (J)

Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA, USA.

Jeffery Brown (J)

Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA, USA.

Sengwee Toh (S)

Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA, USA.

Michael Nguyen (M)

Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, FDA, Silver Spring, MD, USA.

Robert Ball (R)

Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, FDA, Silver Spring, MD, USA.

Gerald Dal Pan (G)

Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, FDA, Silver Spring, MD, USA.

Shirley V Wang (SV)

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Joshua J Gagne (JJ)

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Johnson & Johnson, New Brunswick, NJ, USA.

Sebastian Schneeweiss (S)

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Classifications MeSH