A decomposition approach for the combined master surgical schedule and surgical case assignment problems

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 seve...

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Bibliographic Details
Published in:Health care management science 2014-03, Vol.17 (1), p.49-59
Main Authors: Agnetis, Alessandro, Coppi, Alberto, Corsini, Matteo, Dellino, Gabriella, Meloni, Carlo, Pranzo, Marco
Format: Article
Language:English
Subjects:
Algorithms
Appointments and Schedules
Business and Management
Computer Simulation
Cost control
Decomposition
Econometrics
Efficiency, Organizational
Elective surgery
Health Administration
Health care management
Health Care Rationing - organization & administration
Health Informatics
Hospital Administration
Hospitals
Integrated approach
Management
Operating Rooms - organization & administration
Operations Research/Decision Theory
Planning
Schedules
Scheduling
Studies
Surgery
Systems Analysis
Time Factors
Waiting Lists
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Summary: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.
ISSN:1386-9620
1572-9389
DOI:10.1007/s10729-013-9244-0