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ONLINE CAPACITY PLANNING FOR REHABILITATION TREATMENTS: AN APPROXIMATE DYNAMIC PROGRAMMING APPROACH

Published online by Cambridge University Press:  11 December 2018

Ingeborg A. Bikker Open the ORCID record for Ingeborg A. Bikker [Opens in a new window] ,
Martijn R.K. Mes ,
Antoine Sauré  and
Richard J. Boucherie
Ingeborg A. Bikker
Affiliation:
Center for Healthcare Operations Improvement and Research (CHOIR), University of Twente Drienerlolaan 5, 7500 AE Enschede, The Netherlands and Department of Healthcare Logistics, Sint Maartenskliniek, Hengstdal 3, 6574 NA Ubbergen (Nijmegen), The Netherlands and Stochastic Operations Research, Department of Applied Mathematics, University of Twente, Drienerlolaan 5, 7500 AE Enschede, The Netherlands E-mail: i.a.bikker@utwente.nl
Martijn R.K. Mes
Affiliation:
Department Industrial Engineering and Business Information Systems (IEBIS) University of Twente Drienerlolaan 5, 7500 AE Enschede, The Netherlands
Antoine Sauré
Affiliation:
Telfer School of Management, University of Ottawa, 55 Laurier Avenue East, Ottawa, ON, Canada K1N 6N5
Richard J. Boucherie
Affiliation:
Center for Healthcare Operations Improvement and Research (CHOIR), University of Twente Drienerlolaan 5, 7500 AE Enschede, The Netherlands and Stochastic Operations Research, Department of Applied Mathematics, University of Twente, Drienerlolaan 5, 7500 AE Enschede, The Netherlands
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Abstract

We study an online capacity planning problem in which arriving patients require a series of appointments at several departments, within a certain access time target.

This research is motivated by a study of rehabilitation planning practices at the Sint Maartenskliniek hospital (the Netherlands). In practice, the prescribed treatments and activities are typically booked starting in the first available week, leaving no space for urgent patients who require a series of appointments at a short notice. This leads to the rescheduling of appointments or long access times for urgent patients, which has a negative effect on the quality of care and on patient satisfaction.

We propose an approach for allocating capacity to patients at the moment of their arrival, in such a way that the total number of requests booked within their corresponding access time targets is maximized. The model considers online decision making regarding multi-priority, multi-appointment, and multi-resource capacity allocation. We formulate this problem as a Markov decision process (MDP) that takes into account the current patient schedule, and future arrivals. We develop an approximate dynamic programming (ADP) algorithm to obtain approximate optimal capacity allocation policies. We provide insights into the characteristics of the optimal policies and evaluate the performance of the resulting policies using simulation.

Keywords

approximate dynamic programminghealthcare logisticsonline capacity planningoperations researchMarkov decision processrehabilitation treatment planningsimulation
Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 34 , Special Issue 3: Analytic Methods in Health Care and in Clinical Trials In Honor and Memory of Lycourgos (Lee) Papayanopoulos , July 2020 , pp. 381 - 405
Copyright
Copyright © Cambridge University Press 2018

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