relation: http://eprints.imtlucca.it/1624/
title: A decomposition approach for the combined master surgical schedule and surgical case assignment problems
creator: Agnetis, Alessandro
creator: Coppi, Alberto
creator: Corsini, Matteo
creator: Dellino, Gabriella
creator: Meloni, Carlo
creator: Pranzo, Marco
subject: H Social Sciences (General)
subject: QA Mathematics
description: This research aims at supporting hospital management in making prompt Operating Room (OR) planning decisions, when either unpredicted events occur or alternative scenarios or configurations need to be rapidly evaluated. We design and test a planning tool enabling managers to efficiently analyse several alternatives to the current OR planning and scheduling. To this aim, we propose a decomposition approach. More specifically, we first focus on determining the Master Surgical Schedule (MSS) on a weekly basis, by assigning the different surgical disciplines to the available sessions. Next, we allocate surgeries to each session, focusing on elective patients only. Patients are selected from the waiting lists according to several parameters, including surgery duration, waiting time and priority class of the operations. We performed computational experiments to compare the performance of our decomposition approach with an (exact) integrated approach. The case study selected for our simulations is based on the characteristics of the operating theatre (OT) of a medium-size public Italian hospital. Scalability of the method is tested for different OT sizes. A pilot example is also proposed to highlight the usefulness of our approach for decision support. The proposed decomposition approach finds satisfactory solutions with significant savings in computation time.
publisher: Springer
date: 2013-06
type: Article
type: PeerReviewed
identifier:   Agnetis, Alessandro and Coppi, Alberto and Corsini, Matteo and Dellino, Gabriella and Meloni, Carlo and Pranzo, Marco  A decomposition approach for the combined master surgical schedule and surgical case assignment problems.  Health Care Management Science.  pp. 1-11.  ISSN 1386-9620      (2013)  
relation: http://dx.doi.org/10.1007/s10729-013-9244-0
relation: 10.1007/s10729-013-9244-0