Operations Research 2025
Abstract Submission

2359. Optimizing Patient Flow: Predicting and Managing Aftercare Demand to Tackle Hospital Bed-Blocking

Invited abstract in session WC-8: Patient Flow Optimization, stream Health Care Management.

Wednesday, 13:30-15:00
Room: H8

Authors (first author is the speaker)

1. Anne Zander
Applied Mathematics, University of Twente
2. Anouk Beursgens
University of Twente
3. Richard Boucherie
Stochastich Operations Research, University of Twente
4. Aleida Braaksma
University of Twente

Abstract

As the demand for elderly care increases and healthcare resources become more strained, ensuring an efficient transition from hospital to aftercare becomes vital. Elderly patients often require care provided by aftercare organizations, such as nursing and care homes, and home care after hospital discharge. However, limited aftercare capacity often leads to bed-blocking: patients occupying hospital beds longer than medically necessary. This research addresses the issue by taking a system-wide perspective, combining aftercare demand prediction with capacity planning in aftercare, assuming collaboration between hospitals and aftercare organizations. Using hospital data, we predict aftercare demand on different time scales (short-term, mid-term, and long-term), which provides input for capacity planning in aftercare. In this talk, we focus on long-term, strategic bed capacity planning in aftercare. We model the hospital aftercare system as a modified call-packing system, taking into account that the time spent in the hospital may contribute to the patient’s recovery process to a certain extent. We propose a modified offered load approximation on the basis of which we can optimize aftercare capacity. Our first numerical results show a significant reduction in costs, which include costs for blocked beds in the hospital and costs for empty beds in aftercare, as well as bed-blocking. In conclusion, by aligning hospital and aftercare operations, we seek to reduce bed-blocking, improve patient flow, optimize resource use, and enhance care quality.

Keywords

Status: accepted

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