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,
Francisco Reyes-Santias
Affiliations
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
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.