Article ID: | iaor20171633 |
Volume: | 65 |
Issue: | 3 |
Start Page Number: | 635 |
End Page Number: | 656 |
Publication Date: | Jun 2017 |
Journal: | Operations Research |
Authors: | Verter Vedat, Zhang Dan, Kucukyazici Beste, Samiedaluie Saied |
Keywords: | scheduling, combinatorial optimization, allocation: resources, simulation, medicine, queues: applications, programming: dynamic |
We study patient admission policies in a neurology ward where there are multiple types of patients with different medical characteristics. Patients receive specialized care inside the neurology ward and delays in admission to the ward will have negative impact on their health status. The level of this impact varies among patient types and depends on the severity of patients. Patients are also different in terms of arrival rate and length of stay at the ward. The patients normally wait in the emergency department until a ward bed is assigned to them. We formulate this problem as an infinite‐horizon average cost dynamic program and propose an efficient approximation scheme to solve large‐scale problem instances. The computational results from applying our model to a neurology ward show that dynamic policies generated by our approach can reduce the overall deterioration in patients’ health status compared to several alternative policies. The online appendix is available at https://doi.org/10.1287/opre.2016.1574.