Visual Analytics to Optimize Patient-Population Evidence Delivery for Personalized Care

Abstract

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.

DOI: 10.1145/2506583.2506608

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Cite this paper

@inproceedings{Mane2013VisualAT, title={Visual Analytics to Optimize Patient-Population Evidence Delivery for Personalized Care}, author={Ketan K. Mane and Phillips Owen and Charles Schmitt and Kirk C. Wilhelmsen and Kenneth Gersing and Ricardo Pietrobon and Igor Akushevich}, booktitle={BCB}, year={2013} }