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2379. A Markov chain for the evaluation of inpatient flow in hospitals
Contributed abstract in session MD-15: Healthcare services, stream OR in Health Services (ORAHS).
Monday, 14:30-16:00Room: 18 (building: 116)
Authors (first author is the speaker)
| 1. | Anders Reenberg Andersen
|
| Department of Applied Mathematics and Computer Science, Technical University of Denmark |
Abstract
Many hospitals face the challenge of an increasing demand for admissions to their inpatient nursing wards. The possible solutions to this problem include relocating patients, merging nursing wards, and optimizing the balance of bed capacity between them. In any case, hospital planners need a model that describes the influence of the admission rate, length of stay, allocated capacity, and relocation policies on the occupancy of beds. This study proposes a model based on a continuous-time Markov chain. We reduce the model's computational requirements by evaluating each ward separately and approximating the process governing patients arriving from the other wards. We base our approximation on interrupted Poisson processes, where the interruption times follow hyper-exponential distributions. By employing this approach, we are able to evaluate the occupancy of all inpatient nursing wards in a Danish hospital. Our numerical experiments indicate that this approach is insensitive to the length of stay distribution type and accurately reflects the occupancy of many wards in the hospital.
Keywords
- Health Care
- Stochastic Models
- Queuing Systems
Status: accepted
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