{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T03:04:46Z","timestamp":1774407886697,"version":"3.50.1"},"reference-count":41,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2020,4,11]],"date-time":"2020-04-11T00:00:00Z","timestamp":1586563200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"US Food and Drug Administration","award":["# HHSF223201400030I"],"award-info":[{"award-number":["# HHSF223201400030I"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The US Food and Drug Administration (FDA) Sentinel System uses a distributed data network, a common data model, curated real-world data, and distributed analytic tools to generate evidence for FDA decision-making. Sentinel system needs include analytic flexibility, transparency, and reproducibility while protecting patient privacy. Based on over a decade of experience, a critical system limitation is the inability to identify enough medical conditions of interest in observational data to a satisfactory level of accuracy. Improving the system\u2019s ability to use computable phenotypes will require an \u201call of the above\u201d approach that improves use of electronic health data while incorporating the growing array of complementary electronic health record data sources. FDA recently funded a Sentinel System Innovation Center and a Community Building and Outreach Center that will provide a platform for collaboration across disciplines to promote better use of real-world data for decision-making.<\/jats:p>","DOI":"10.1093\/jamia\/ocaa028","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T12:24:20Z","timestamp":1583497460000},"page":"793-797","source":"Crossref","is-referenced-by-count":41,"title":["Using and improving distributed data networks to generate actionable evidence: the case of real-world outcomes in the Food and Drug Administration\u2019s Sentinel system"],"prefix":"10.1093","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9340-7189","authenticated-orcid":false,"given":"Jeffrey S","family":"Brown","sequence":"first","affiliation":[{"name":"Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, Massachusetts, 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