ORAHS2024
Abstract Submission

93. Optimizing dynamic reserved resource capacity in appointment scheduling with elective and semi-urgent patients

Contributed abstract in session TC-1: Poster session, stream Posters.

Tuesday, 14:00-15:30
Room: Auditorium

Authors (first author is the speaker)

1. Jedidja Lok - Visser
CHOIR, University of Twente
2. Heleen den Hertog
Isala
3. Gina van Vemde
Isala
4. Jan Gerard Maring
Clinical Pharmacy & Connected Care, Isala
5. Gréanne Leeftink
CHOIR, University of Twente

Abstract

In appointment scheduling, it is a common practice to reserve some slots for (semi-)urgent demand arrivals, that require service quickly. The other slots are then given to clients that request an appointment upfront. To determine the number of reserved slots, the (semi-)urgent demand arrivals are often modelled as a distribution with static or seasonal distribution parameters. However, due to recent advances in remote monitoring and telemedicine, updated (semi-)urgent demand arrival information might become available over time. In this study, we use this updated information to dynamically optimise appointment schedules.

We propose near-optimal scheduling policies that reserve slots for (semi-)urgent clients, using updated information on the arrival distribution of (semi-)urgent clients in the near future. We formulate the sequential decision making problem as a Markov Decision Process. We test this model on a Dutch real-life case study in the neurology department of Isala Clinics, Zwolle. This neurology department implemented a brain rehabilitation program in combination with an e-coach for Cerebral Vascular Accident patients. We use the number of active patients in this monitoring application to forecast the number of semi-urgent requests for outpatient appointments. We discuss first results on this practical case study and theoretical instances, and present managerial implications of our near-optimal policies.

Keywords

Status: accepted

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