Using the Electronic Medical Record to Identify Patients at High Risk for Frequent Emergency Department Visits and High System Costs

American Journal of Medicine

Volumn 130, Issue 5, 2017, Pages 601.e17-601.e22

  Frost, David W ^a,b,e   Vembu, Shankar ^c,e   Wang, Jiayi ^c,e   Tu, Karen ^a,b,e,f   Morris, Quaid ^a,c,d,e   Abrams, Howard B ^a,b,e  

^a UNIVERSITY OF TORONTO   (Canada)

^b UNIVERSITY HEALTH NETWORK   (Canada)

^c Donnelly Centre for Cellular and Biomolecular Research   (Canada)

^d Banting and Best Department of Medical Research   (Canada)

^e UNIVERSITY OF TORONTO   (Canada)

^f INSTITUTE FOR CLINICAL EVALUATIVE SCIENCES   (Canada)

Author keywords

Electronic medical records; Frequent emergency department visits; High users; Machine learning; Predictive modeling

Indexed keywords

ADULT; ARTICLE; ELECTRONIC MEDICAL RECORD; EMERGENCY WARD; HEALTH CARE COST; HEALTH CARE SYSTEM; HEALTH CARE UTILIZATION; HIGH RISK POPULATION; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; PATIENT IDENTIFICATION; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; ALGORITHM; DATA MINING; ECONOMICS; ELECTRONIC HEALTH RECORD; HOSPITAL COST; HOSPITAL EMERGENCY SERVICE; STATISTICAL MODEL; UTILIZATION;

ALGORITHMS; DATA MINING; ELECTRONIC HEALTH RECORDS; EMERGENCY SERVICE, HOSPITAL; HOSPITAL COSTS; HUMANS; LOGISTIC MODELS; ROC CURVE;

EID: 85011954158     PISSN: 00029343     EISSN: 15557162     Source Type: Journal    
DOI: 10.1016/j.amjmed.2016.12.008     Document Type: Article

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