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A Modeling Framework for Control of Preventive Services

Author

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  • E. Lerzan Örmeci

    (Department of Industrial Engineering, Koç University, 34450 Istanbul, Turkey)

  • Evrim Didem Güneş

    (College of Administrative Sciences and Economics, Koç University, 34450 Istanbul, Turkey)

  • Derya Kunduzcu

    (Credit Analytics, Akbank, 34774 Istanbul, Turkey)

Abstract

We present a modeling framework for facilities that provide both screening (preventive) and diagnostic (repair) services. The facility operates in a random environment that represents the condition of the population that needs screening and diagnostic services, such as the disease prevalence level. We model the environment as a partially endogenous process: the population’s health can be improved by providing screening services, which reduces future demand for diagnostic services. We use event-based dynamic programming to build a framework for modeling different kinds of these facilities. This framework contains a number of service priority policies that are concerned with prioritizing screening versus diagnostic services. The main trade-off is between serving urgent diagnostic needs and providing screening services that may decrease future diagnostic needs. Under certain conditions, this trade-off reverses the famous cμ rule; i.e., the patients with lower waiting cost are given priority over the others. We define appropriate event operators and specify the properties preserved by these operators. These characterize the structure of optimal policies for all models that can be built within this framework. A numerical study on colonoscopy services illustrates how the framework can be used to gain insights on developing good screening policies.

Suggested Citation

  • E. Lerzan Örmeci & Evrim Didem Güneş & Derya Kunduzcu, 2016. "A Modeling Framework for Control of Preventive Services," Manufacturing & Service Operations Management, INFORMS, vol. 18(2), pages 227-244, May.
    • Handle: RePEc:inm:ormsom:v:18:y:2016:i:2:p:227-244
    DOI: 10.1287/msom.2015.0556
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    References listed on IDEAS

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    Cited by:

    1. Yuqian Xu & Lingjiong Zhu & Michael Pinedo, 2020. "Operational Risk Management: A Stochastic Control Framework with Preventive and Corrective Controls," Operations Research, INFORMS, vol. 68(6), pages 1804-1825, November.
    2. Ozgur M. Araz & Mayteé Cruz-Aponte & Fernando A. Wilson & Brock W. Hanisch & Ruth S. Margalit, 2022. "An Analytic Framework for Effective Public Health Program Design Using Correctional Facilities," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 113-128, January.
    3. Chen, Yi & Ding, Shuai & Zheng, Handong & Zhang, Youtao & Yang, Shanlin, 2018. "Exploring diffusion strategies for mHealth promotion using evolutionary game model," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 148-161.
    4. Tunçalp, Feray & Güneş, Evrim D. & Örmeci, E. Lerzan, 2024. "Modeling strategic walk-in patients in appointment systems: Equilibrium behavior and capacity allocation," European Journal of Operational Research, Elsevier, vol. 313(2), pages 587-601.
    5. Wenqi Hu & Carri W. Chan & José R. Zubizarreta & Gabriel J. Escobar, 2018. "An Examination of Early Transfers to the ICU Based on a Physiologic Risk Score," Manufacturing & Service Operations Management, INFORMS, vol. 20(3), pages 531-549, July.

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