Zenarosa, Gabriel Lopez
(2016)
Integrating Proactive and Reactive Decision-making in Surgery Scheduling.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Aggregate surgical expenditures in the US amounted to about 5.2% of the Gross Domestic Product in 2010, and are projected to increase. About 42% of hospitals' revenues are generated by their operation rooms (ORs), yet the average OR runs at only 68% capacity. While OR management has many aspects, the most important and challenging issues are centered on surgery scheduling. Advance surgery schedules improve OR efficiency; however, days of surgeries rarely go as planned, and rescheduling is performed in practice as uncertainties unravel. Surgery scheduling involves sequential decision-making; advance scheduling and day-of-surgery rescheduling must account for subsequent rescheduling to achieve better OR efficiencies over myopic decision-making. This dissertation focuses on the integration of proactive and reactive decision-making in surgery scheduling. We present stochastic programs with chance-constrained recourse for surgery scheduling and rescheduling: minimizing the total expected OR underutilization subject to probabilistic overtime constraints, where surgery durations and occurrences are random. We demonstrate how our approach outperforms the surgery scheduling and rescheduling policies used in practice at a hospital, and we provide some insights on further improvements that can be made at the operational, tactical, and strategic decision-making levels.
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Details
| Item Type: |
University of Pittsburgh ETD
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| Status: |
Unpublished |
| Creators/Authors: |
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| ETD Committee: |
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| Date: |
20 September 2016 |
| Date Type: |
Publication |
| Defense Date: |
7 July 2016 |
| Approval Date: |
20 September 2016 |
| Submission Date: |
24 July 2016 |
| Access Restriction: |
5 year -- Restrict access to University of Pittsburgh for a period of 5 years. |
| Number of Pages: |
110 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Industrial Engineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
surgery scheduling, advance scheduling, day-of-surgery rescheduling, stochastic programming, chance-constrained programming, chance-constrained recourse, probabilistic constraints, integer programming, optimization, optimization software, modeling systems, parallel algorithms |
| Date Deposited: |
20 Sep 2016 18:51 |
| Last Modified: |
20 Sep 2021 05:15 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/28900 |
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