Abstract

Bed management, an important function of any hospital, has a major impact on patient care, patient flow, patient and staff satisfaction, and ultimately on the hospital’s operating margin. A key challenge in bed management is optimizing the bed-assignment process in a complex and dynamic operating environment. Efficient bed assignment requires the merging of clinical information, hospital operations information, interdependencies between units, and real-time information on patients, resources, and workflows. We have developed analytical decision support tools with embedded mathematical models to periodically recommend bed-patient assignments. Using an innovative mixed-integer goal-programming modeling approach, we are able to accommodate the multiple goals and complex operating rules of different hospitals. We implemented and hosted our prototype bed-assignment solution as a cloud-based application for Mount Sinai Medical Center in New York.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call