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Optimizing Colonoscopy Screening for Colorectal Cancer Prevention and Surveillance

Author

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  • Fatih Safa Erenay

    (Department of Management Sciences, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada)

  • Oguzhan Alagoz

    (Department of Industrial and Systems Engineering, University of Wisconsin–Madison, Madison, Wisconsin 53706)

  • Adnan Said

    (Department of Medicine, University of Wisconsin–Madison, Madison, Wisconsin 53792)

Abstract

Millions of Americans undergo colonoscopy screening for colorectal cancer (CRC) prevention and surveillance every year. The efficiency of colonoscopy operations depends on how often patients are screened, which is a complex and controversial decision, as reflected by the discrepancy between clinical practice and guidelines. We develop a partially observable Markov decision process to optimize colonoscopy screening policies for the objective of maximizing total quality-adjusted life years. Our model incorporates age, gender, and risk of having CRC into the screening decisions and therefore provides a novel framework for personalized CRC screening. In addition to deriving the maximum attainable benefit from colonoscopy screening, which reflects the opportunity cost of following current guidelines, our results have several policy implications. Using clinical data, we show that the optimal colonoscopy screening policies may be more aggressive than the guidelines under some conditions. Optimal screening policies recommend that females with CRC history undergo colonoscopy more frequently than males. In contrast, females without CRC history should be screened less frequently than males. This result, which was not recognized before, signifies the role of gender in optimal CRC screening decisions.

Suggested Citation

  • Fatih Safa Erenay & Oguzhan Alagoz & Adnan Said, 2014. "Optimizing Colonoscopy Screening for Colorectal Cancer Prevention and Surveillance," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 381-400, July.
  • Handle: RePEc:inm:ormsom:v:16:y:2014:i:3:p:381-400
    DOI: 10.1287/msom.2014.0484
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    References listed on IDEAS

    as
    1. Fatih Safa Erenay & Oguzhan Alagoz & Ritesh Banerjee & Robert R. Cima, 2011. "Estimating the Unknown Parameters of the Natural History of Metachronous Colorectal Cancer Using Discrete-Event Simulation," Medical Decision Making, , vol. 31(4), pages 611-624, July.
    2. Turgay Ayer & Oguzhan Alagoz & Natasha K. Stout, 2012. "OR Forum---A POMDP Approach to Personalize Mammography Screening Decisions," Operations Research, INFORMS, vol. 60(5), pages 1019-1034, October.
    3. Lisa M. Maillart & Julie Simmons Ivy & Scott Ransom & Kathleen Diehl, 2008. "Assessing Dynamic Breast Cancer Screening Policies," Operations Research, INFORMS, vol. 56(6), pages 1411-1427, December.
    4. Richard D. Smallwood & Edward J. Sondik, 1973. "The Optimal Control of Partially Observable Markov Processes over a Finite Horizon," Operations Research, INFORMS, vol. 21(5), pages 1071-1088, October.
    5. Giovanni Parmigiani & Steven Skates & Marvin Zelen, 2002. "Modeling and Optimization in Early Detection Programs with a Single Exam," Biometrics, The International Biometric Society, vol. 58(1), pages 30-36, March.
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    12. Boloori, Alireza & Saghafian, Soroush & Chakkera, Harini A. A. & Cook, Curtiss B., 2017. "Data-Driven Management of Post-transplant Medications: An APOMDP Approach," Working Paper Series rwp17-036, Harvard University, John F. Kennedy School of Government.
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