This paper addresses the design problem of outpatient chemotherapy oncology departments. The objective is to identify the most effective resource configuration (e.g. number of chairs, number of oncologists) to reduce the patient waiting time and increase the average number of daily treatments. A stochastic simulation model was developed to emulate the patient flow in different oncology unit configurations. Then, it was used to generate the expected results of an extended design of experiments. To evaluate the impact of the different resources on the performance of the oncology departments the ANOVA analysis was employed. Besides, a Pareto multi-objective analysis was carried out to further support any decision-maker in the selection of the most suitable resource configuration. Particularly, to make easier the decision-making process, a comprehensive table chart was elaborated. Finally, a multiple non-linear regression model was generated in order to empower the health managers in easily assessing the performance of any real ward configuration. The analysis of results pointed out that the two mentioned objectives are rather conflicting. Furthermore, it proved that a higher number of resources not necessarily implies a significant improvement in the performance measures.

System design of outpatient chemotherapy oncology departments through simulation and design of experiments

Corsini R. R.
Primo
Methodology
;
Costa A.;Fichera S.;Pluchino A.;Parrinello V.
2022-01-01

Abstract

This paper addresses the design problem of outpatient chemotherapy oncology departments. The objective is to identify the most effective resource configuration (e.g. number of chairs, number of oncologists) to reduce the patient waiting time and increase the average number of daily treatments. A stochastic simulation model was developed to emulate the patient flow in different oncology unit configurations. Then, it was used to generate the expected results of an extended design of experiments. To evaluate the impact of the different resources on the performance of the oncology departments the ANOVA analysis was employed. Besides, a Pareto multi-objective analysis was carried out to further support any decision-maker in the selection of the most suitable resource configuration. Particularly, to make easier the decision-making process, a comprehensive table chart was elaborated. Finally, a multiple non-linear regression model was generated in order to empower the health managers in easily assessing the performance of any real ward configuration. The analysis of results pointed out that the two mentioned objectives are rather conflicting. Furthermore, it proved that a higher number of resources not necessarily implies a significant improvement in the performance measures.
design of experiments
healthcare
length-of-stay
Oncology unit
simulation
stochastic design
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/541389
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