Scheduling inpatient admission under high demand of emergency patients
- Resource Type
- Conference
- Authors
- Mazier, Alexandre; Xie, Xiaolan; Sarazin, Marianne
- Source
- 2010 IEEE International Conference on Automation Science and Engineering Automation Science and Engineering (CASE), 2010 IEEE Conference on. :792-797 Aug, 2010
- Subject
- Robotics and Control Systems
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Aerospace
Bioengineering
Engineered Materials, Dielectrics and Plasmas
Nuclear Engineering
Power, Energy and Industry Applications
Hospitals
Schedules
Monte Carlo methods
Optimization
Stochastic processes
Programming
- Language
- ISSN
- 2161-8070
2161-8089
This paper addresses the problem of scheduling inpatient admission in a hospital with highly uncertain length of stay and with a significant part of patients from emergency department. The main difficulty is to keep enough beds for unknown emergency patients and unknown future inpatients, also called elective patients, when planning admission of elective patients. For this purpose, we model inpatient admission scheduling as a stochastic programming problem. We propose an average sampling technique to estimate the number of beds needed for emergency patients and unknown inpatients. Three strategies are proposed to solve the stochastic programming problem. Experiments with data sets derived from data collected from a French medium-sized hospital are conducted to assess the performance of the three strategies.