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dc.contributor.advisorSir, Mustafa Yasareng
dc.contributor.authorLin, Rung-Chuaneng
dc.contributor.otherUniversity of Missouri-Columbia. Graduate School. Theses and Dissertations. Dissertations. 2013 Dissertationseng
dc.coverage.spatialUnited Stateseng
dc.date.issued2013eng
dc.date.submitted2013 Summereng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Surgical services constitute a major portion of overall expenses in a hospital including staff salaries, operating rooms, beds, etc. Surgery is also a major source of revenue for a hospital. Therefore, an efficient management of surgical services is essential for hospitals. However, surgical services form a large system that involves complex interactions of multiple resources and complex trade-offs among multiple performance measures making it difficult to manage. We categorize activities in surgical services planning as long-term strategic decisions, mid-term tactical decisions, and short-term operational decisions and focus on three main planning problems in surgical services, one from each category and each having multiple objectives with difficult trade-offs. These include 1) strategic optimization of resource levels in surgical services considering labor cost, patient waiting time, and system completion time; 2) tactical staff scheduling to minimize average employee fatigue and shift preference scores; and 3) operational surgical case scheduling to determine the starting time of cases and assigning operating room to each case considering multiple objectives including minimizing the patient waiting time and completion time of the last case (i.e., makespan), and maximizing surgeon satisfaction with regard to their case sequence preferences. In addition, two data analysis studies are performed for supporting these three main problems. These include 1) developing forecasts to predict patient volumes for short-term corrective allocation decisions to make real-time changes to staff schedules determined by the tactical staff scheduling problem; and 2) developing a predictive model for estimating operation durations to schedule surgical cases efficiently. Our models can help hospital managers and schedulers to make better long-term, mid-term, and short-term decisions without compromising on efficiency while improving the safety and satisfaction in surgical services.eng
dc.description.bibrefIncludes bibliographical references (pages 121-141).eng
dc.format.extent1 online resource (xii, 142 pages) : illustrations (some color)eng
dc.identifier.oclc892852760eng
dc.identifier.urihttps://doi.org/10.32469/10355/40173eng
dc.identifier.urihttps://hdl.handle.net/10355/40173
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the campus of the University of Missouri--Columbia.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.sourceSubmitted by the University of Missouri--Columbia Graduate School.eng
dc.subject.lcshSurgeryeng
dc.subject.lcshHospitals -- Planningeng
dc.subject.lcshHospitals -- Managementeng
dc.subject.lcshHealth services administrationeng
dc.titleMulti-objective optimization models for surgical services planningeng
dc.typeThesiseng
thesis.degree.disciplineIndustrial and manufacturing systems engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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