Admission scheduling of inpatients by considering two inter-related resources: beds and operating rooms

ABSTRACT

This paper studies the admission scheduling problem with considering the capacity usage of two inter-related resources (beds and operating rooms) between three consecutive stages of care during surgical patients' admissions to Chinese public hospitals, namely (1) pre-surgical inpatient bed, (2) surgery, (3) post-surgical inpatient bed. Demand comes from two types of patients: (1) emergency patients, who arise randomly and have to be admitted immediately, and (2) elective patients, whose admissions can be scheduled. The authors develop a Markov Decision Process (MDP) model that decides how many elective patients should be admitted each day, with the objective of optimally using both operating room and inpatient bed capacity. The authors demonstrate that the number of elective admissions scheduled each day is monotonically increasing in the state of the system and in the bed capacity, indicating that a higher level of waiting elective patients and available (or total) bed capacity pulls more elective admissions through the system. The total discounted expected cost of the system exhibits decreasing marginal returns as the capacity in each stage increases independently of other stages. Through numerical experiments, there is substantial value in making admission scheduling decisions by jointly considering inpatient beds and operating rooms.

Keywords:

• Operations management in health services
• admission scheduling
• capacity planning
• operating room and inpatient bed
• Markov decision process

2010 Mathematics Subject Classifications:

• 37Hxx Random dynamic systems
• 37NxxApplications
• 90Bxx Operations research and management science

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Department of Science and Technology of Sichuan Province [2019YFS0276] and the National Natural Science Foundation of China [71532007].