Improving Patient Access to Chemotherapy Treatment at Duke Cancer Institute

Jonathan C. Woodall (), Tracy Gosselin (), Amy Boswell (), Michael Murr () and Brian T. Denton ()
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Jonathan C. Woodall: Duke Medicine, Durham, North Carolina 27710
Tracy Gosselin: Duke Cancer Institute, Durham, North Carolina 27710
Amy Boswell: Duke Cancer Institute, Durham, North Carolina 27710
Michael Murr: Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina 27695
Brian T. Denton: Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109

Interfaces, 2013, vol. 43, issue 5, 449-461

Abstract: This paper describes how we applied simulation and optimization in combination to improve patient flow within the Duke Cancer Institute, a large cancer center. We first developed a discrete-event simulation model to predict patient waiting time and resource utilization throughout various parts of the center, including the outpatient clinic, radiology, the pharmacy, laboratory services, and the oncology treatment facility. Simulation model studies showed that nurse unavailability during oncology treatment causes a serious bottleneck in patient flow. Next, we developed a mixed-integer programming model to relieve the bottleneck by optimizing weekly and monthly scheduling of different types of nurses. Finally, we developed a novel simulation-optimization model to further relieve the bottleneck by optimizing the starting times of nurse shifts. Our paper summarizes our main findings and the resulting recommendations that Duke Cancer Institute implemented.

Keywords: simulation; optimization; integer programming; healthcare; nurse scheduling (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:43:y:2013:i:5:p:449-461

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