Incorporando dinámicas de no aparición en la programación de sesiones de quimioterapia
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Date
2024
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Abstract
Cancer is one of the leading causes of death worldwide and the demand for chemotherapy treatments is growing faster than the capacity health centers have to provide them. Consequently, it is imperative to identify efficient resource management practices for the inter-day scheduling of chemotherapy sessions. We approach the inter-day chemotherapy scheduling problem through a three-step solution approach. First, we reclaim future resources tied to treatments disrupted by patient no-shows. Second, we identify patients for whom current wait times can be reduced. Third, we employ a proactive scheduling policy obtained through the resolution of a Markov decision process via approximate dynamic programming techniques. Using data from the UC CHRISTUS Health Network, we present a case study that demonstrates the impact of no-shows on health systems and the potential benefits that can be obtained from the use the proposed solution approach. From the results, we can conclude that our approach leads to substantial improvements in multiple aspects of outpatient chemotherapy operations. Specifically, the proposed approach achieves a discounted operational cost reduction of 22.3% and a 32.6% reduction in average waiting times when compared with existing algorithms. The results allow us to conclude that there are multiple benefits associated with incorporating no-shows into the problem’s resolution and that the proposed solution approach not only reduces discounted operational costs, but also improves the level of service offered to patients.
Description
Tesis (Magíster en Ciencias de la Ingeniería)--Pontificia Universidad Católica de Chile, 2024
Keywords
Chemotherapy, No Shows, Interday Scheduling, Markov Decision Process, OR in health services