Regional Planning Model for Cancer Screening with Imperfect Patient Adherence

Aaron Ratcliffe (), Ann Marucheck () and Sean Xin Xu ()
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Aaron Ratcliffe: Department of Computer Information Systems and Supply Chain Management, Appalachian State University, Boone, North Carolina 28608-2049;
Ann Marucheck: Kenan-Flagler Business School, University of North Carolina, Chapel Hill, North Carolina 27599-3490
Sean Xin Xu: Kenan-Flagler Business School, University of North Carolina, Chapel Hill, North Carolina 27599-3490

Service Science, 2019, vol. 11, issue 2, 113-137

Abstract: The effectiveness of cancer screening and adherence to cancer screening guidelines can be inhibited by long wait times for screening appointments. We develop a queueing network model of screening for a disease within a population of patients with imperfect adherence to screening guidelines to characterize the relationship between the screening request frequency rate and the wait time for screens. We first use our model to derive the capacity needed by a given system or the population size a given system can serve to guarantee a certain service level. We analyze routine screening for average-risk patients as well as the additional capacity required for diagnostic screening and surveillance of high-risk patients. We perform a numerical study using national public health data for colorectal cancer (CRC) screening in the United States and provide insights for public health officials, providers, and policy makers by showing how queueing models can be applied to regional planning decisions for determining CRC screening capacity requirements.

Keywords: healthcare operations; capacity planning; disease screening; colorectal cancer; queueing network (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orserv:v:11:y:2019:i:2:p:113-137

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