Effective Optimisation of the Patient Circuits of an Oncology Day Hospital: Mathematical Programming Models and Case Study

Adrián González-Maestro, Elena Brozos-Vázquez, Balbina Casas-Méndez, Rafael López-López, Rosa López-Rodríguez and Francisco Reyes-Santias
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Adrián González-Maestro: Health Research Institute of Santiago de Compostela (IDIS), Complexo Hospitalario Universitario of Santiago de Compostela (SERGAS), 15706 Santiago de Compostela, Spain
Elena Brozos-Vázquez: Department of Medical Oncology, Hospital Clínico Universitario of Santiago de Compostela, 15706 Santiago de Compostela, Spain
Balbina Casas-Méndez: Department of Statistics, Mathematical Analysis and Optimization, Universidade of Santiago de Compostela, 15782 Santiago de Compostela, Spain
Rafael López-López: Health Research Institute of Santiago de Compostela (IDIS), Complexo Hospitalario Universitario of Santiago de Compostela (SERGAS), 15706 Santiago de Compostela, Spain
Rosa López-Rodríguez: Department of Medical Oncology, Hospital Clínico Universitario of Santiago de Compostela, 15706 Santiago de Compostela, Spain
Francisco Reyes-Santias: Health Research Institute of Santiago de Compostela (IDIS), Complexo Hospitalario Universitario of Santiago de Compostela (SERGAS), 15706 Santiago de Compostela, Spain

Mathematics, 2021, vol. 10, issue 1, 1-31

Abstract: In this paper, we first use the information we have on the patients of an oncology day hospital to distribute the treatment schedules they have in each of the visits to this centre. To do this, we propose a deterministic mathematical programming model in such a way that we minimise the duration of the waiting room stays of the total set of patients and taking into account the restrictions of the circuit. Secondly, we will look for a solution to the same problem under a stochastic approach. This model will explicitly consider the existing uncertainty in terms of the different times involved in the circuit, and this model also allows the reorganisation of the schedules of medical appointments with oncologists. The models are complemented by a tool that solves the problem of assigning nurses to patients. The work is motivated by the particular characteristics of a real hospital and the models are used and compared with data from this case.

Keywords: treatment schedules; medical appointment scheduling; integer linear programming; stochastic programming; nurse assignment; case study (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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