Author Interviews, Health Care Systems / 01.09.2015
Data-Driven Model Can Help Predict Hospital Discharges
MedicalResearch.com Interview with:
Dr. Sean Barnes Ph.D.
Department of Decision, Operations & Information Technologies
Robert H. Smith School of Business
University of Maryland, College Park, MD
Medical Research: What is the background for this study? What are the main findings?
Dr. Barnes: Hospitals are continually being challenged to provide timely and efficient care in the face of increasingly constrained resources. One recent approach to help improve patient flow in hospitals is Real-Time Demand and Capacity Management, by which clinicians huddle each morning to predict the number of patients they expect to discharge on a given day (and hence the number of beds that will become available to potentially utilize for newly admitted patients). We proposed a data-driven method for predicting discharges--either on an individual or aggregate basis--and demonstrated that we could match or exceed the predictive accuracy of clinicians. In addition, we showed (with moderate success) that we could use this model to rank patients in order of their expected discharge times, which could be used to prioritize the remaining care tasks for specific subsets of patients.
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