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Integrating Proactive and Reactive Decision-making in Surgery Scheduling

Zenarosa, Gabriel Lopez (2016) Integrating Proactive and Reactive Decision-making in Surgery Scheduling. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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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
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Zenarosa, Gabriel Lopezgzen@cs.cmu.eduGLZ50000-0003-1096-3559
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairProkopyev, Oleg A.prokopyev@engr.pitt.eduDROLEG
Committee CoChairSchaefer, Andrew J.andrew.schaefer@rice.eduSCHAEFER
Committee MemberRajgopal, Jayantrajgopal@pitt.eduRAJGOPAL
Committee MemberPiasio, Mark A.mark.piasio@highmark.com
Committee MemberShylo, Oleg V.oshylo@utk.edu
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: 15 Nov 2016 14:34
URI: http://d-scholarship.pitt.edu/id/eprint/28900

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