Visual analytics to optimize patient-population evidence delivery for personalized care
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Electronic medical records (EMR) can be used to identify cohorts of patients who are clinically comparable to an individual patient. In this paper, we describe an approach that applies visual analytics to EMR data to describe the clinical course for an individual patient, display outcomes for a comparable cohort stratified by treatment, and generate predictions regarding a patient's clinical course based on treatment options. The visual display of information is designed to help clinicians choose among alternative therapies based on the EMR-derived outcomes of the cohort. Copyright © 2007 by the Association for Computing Machinery.
Published Version (Please cite this version)10.1145/2506583.2506608
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Associate Research Professor in the Social Science Research Institute
Adjunct Associate in the Department of Psychiatry and Behavioral Sciences
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