Open AccessValidation of an Electronic Health Record–Based Suicide Risk Prediction Modeling Approach Across Multiple Health Care Systems
Author(s) -
Yuval BarakCorren,
Víctor M. Castro,
Matthew K. Nock,
Kenneth D. Mandl,
Emily Madsen,
Ashley N. Seiger,
William G. Adams,
Reuben Applegate,
Elmer V. Bernstam,
Jeffrey G. Klann,
Ellen P. McCarthy,
Shawn N. Murphy,
Marc D. Natter,
Brian Ostasiewski,
Nandan Patibandla,
Gary E. Rosenthal,
George S. Silva,
Kun Wei,
Griffin M. Weber,
Sarah R. Weiler,
Ben Y. Reis,
Jordan W. Smoller
Publication year - 2020
Publication title -
jama network open
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.278
H-Index - 39
ISSN - 2574-3805
DOI - 10.1001/jamanetworkopen.2020.1262
Subject(s) - generalizability theory , ninth , health care , medicine , diagnosis code , poison control , medical record , public health , occupational safety and health , medical emergency , data mining , computer science , psychology , environmental health , population , nursing , acoustics , economics , radiology , economic growth , pathology , developmental psychology , physics
Across 5 diverse health care systems, a computationally efficient approach leveraging the full spectrum of structured electronic health record data was able to detect the risk of suicidal behavior in unselected patients. This approach could facilitate the development of clinical decision support tools that inform risk reduction interventions.
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