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Dynamically Planning Operating Room Schedules Using Model Predictive Control

[+] Author Affiliations
Zhigang Zeng, Theodor Freiheit

University of Calgary, Calgary, AB, Canada

Paper No. DSCC2017-5359, pp. V003T27A016; 10 pages
  • ASME 2017 Dynamic Systems and Control Conference
  • Volume 3: Vibration in Mechanical Systems; Modeling and Validation; Dynamic Systems and Control Education; Vibrations and Control of Systems; Modeling and Estimation for Vehicle Safety and Integrity; Modeling and Control of IC Engines and Aftertreatment Systems; Unmanned Aerial Vehicles (UAVs) and Their Applications; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Control of Smart Buildings and Microgrids; Energy Systems
  • Tysons, Virginia, USA, October 11–13, 2017
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5829-5
  • Copyright © 2017 by ASME


Efficient management of operating room (OR) schedules is of particular interest as this service is the largest cost and revenue center in a hospital and can substantially impact its staffing and finances. A major problem associated with developing OR schedules for elective surgeries is the uncertainty inherent in the duration of surgical services which can disrupt a daily plan. Another problem is the impact of facilities and resources upstream and downstream to the operating room, which affect the performance of the overall system. Using a manufacturing system analytical approach, the peri-operative process is modeled as a transfer line with three machines and two buffers using a discrete time Markov chain. Model predictive control is then applied to control the pace of patient release into the OR rooms. With this model and empirical studies of OR and recovery duration, guidance can be given to OR managers on how to dynamically schedule and reschedule patients throughout an operating room’s day that minimizes cost for a given workload.

Copyright © 2017 by ASME



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