Analyzing Post-Operative Bed Mix at a Major Hospital
Applied Mathematics and Scientific Computation Program, Department of Mathematics, University of Maryland, College Park, MD 20742
R.H. Smith School of Business, University of Maryland, College Park, MD 20742
University of Maryland Medical Center and School of Medicine, Baltimore, MD 21201
Kogod School of Business, American University, Washington, DC 20016
Efficient bed management and nurse resource allocation are challenges confronting every medical center in the country. Hospitals are bursting at the seams as they attempt to manage increased patient demands in an era of nursing shortages and bed scarcities. Several of the nation’s experts have tied the crisis in emergency room diversions to the downstream bottlenecks seen in intensive care units, step-down units, and medical surgical units. However, building new inpatient ICU capacity is an expensive option. Bed allocation and management decisions are often made without a scientific basis and frequently rely on traditional practice and subjective anecdotes.
We developed a simulation model to analyze the appropriate bed mix for a cardiac surgery ICU and its telemetry unit to maximize throughput of a cardiac surgery service line at a major hospital in Maryland. The model uses historical length of stay data from more than 1,700 cardiac surgery encounters to estimate the maximum throughput of a 30 bed post-operative unit.
The results of the simulation indicate that by altering the current mix of ICU beds and telemetry beds the maximum number of surgeries could be increased by 17%. This increase in surgeries could raise the hospital’s annual profit by more than $2.4 million. The Maryland hospital is currently in the process of implementing the simulation study results.
