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“Saving lives or harming the healthy?” Overuse and fluctuations in routine medical screening

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  • Özge Karanfil
  • John Sterman

Abstract

Tests to screen for certain diseases—for example, thyroid cancer screening, screening mammography, and screening of high blood pressure for hypertension—are increasingly common in medical practice. However, guidelines for routine screening are contentious for many disorders and often fluctuate over time. Some tests are over‐ or underused compared to available evidence that justifies their use, with clinical practice persistently deviating from evidence‐based guidelines. Here we develop an integrated, broad boundary feedback theory and formal model to explain the dynamics of routine population screening including fluctuations in policy‐decision thresholds and the expansion of selection criteria which may lead to inappropriate use. We present a behaviorally realistic, boundedly rational model of detection and selection for medical screening that explains the potential of endogenous oscillations in practice guidelines as decision‐makers—including epidemiologists, clinicians, and patients, or policymakers from guideline issuing organizations, perceive harms and benefits from potential outcomes and make trade‐offs between sensitivity and specificity by altering the existing guidelines and actual practice. The model endogenously generates fluctuations in screening indications, test thresholds, test efficiency, and the target screening population, leading to long periods during which practice guidelines are suboptimal even if the underlying evidence base is constant. We use cancer screening as a motivating example, but the model is generic with a wide range of potential applications for important managerial problems in medical contexts, such as screening for hypertension, hypercholesterolemia, autism spectrum disorder, Alzheimer's disease, and related dementia. It also applies to other managerial problems in nonmedical contexts, such as airport screening, background checks, tax audits, automotive emission tests, contentious jurisdiction, or to consumers of other kinds of information who need to make a decision—on behalf of an individual, or for the whole population. © 2020 System Dynamics Society

Suggested Citation

  • Özge Karanfil & John Sterman, 2020. "“Saving lives or harming the healthy?” Overuse and fluctuations in routine medical screening," System Dynamics Review, System Dynamics Society, vol. 36(3), pages 294-329, July.
  • Handle: RePEc:bla:sysdyn:v:36:y:2020:i:3:p:294-329
    DOI: 10.1002/sdr.1661
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    References listed on IDEAS

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    1. Elise A. Weaver & George Richardson, 2006. "Threshold setting and the cycling of a decision threshold," System Dynamics Review, System Dynamics Society, vol. 22(1), pages 1-26, March.
    2. Barbara E. Kahn & Mary Frances Luce, 2003. "Understanding High-Stakes Consumer Decisions: Mammography Adherence Following False-Alarm Test Results," Marketing Science, INFORMS, vol. 22(3), pages 393-410, April.
    3. David F. Ransohoff & Michael Pignone & Louise B. Russell, 2011. "Using Models to Make Policy," Medical Decision Making, , vol. 31(4), pages 527-529, July.
    4. Cutler, David M. & Lleras-Muney, Adriana, 2010. "Understanding differences in health behaviors by education," Journal of Health Economics, Elsevier, vol. 29(1), pages 1-28, January.
    5. Thomas R. Stewart & Jeryl L. Mumpower, 2004. "Detection and selection decisions in the practice of screening mammography," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 23(4), pages 908-920.
    6. John D. Sterman, 1989. "Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment," Management Science, INFORMS, vol. 35(3), pages 321-339, March.
    7. Negar Darabi & Niyousha Hosseinichimeh, 2020. "System dynamics modeling in health and medicine: a systematic literature review," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 29-73, January.
    8. Sterman, J.D., 2006. "Learning from evidence in a complex world," American Journal of Public Health, American Public Health Association, vol. 96(3), pages 505-514.
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    Cited by:

    1. Özge Karanfil & Niyousha Hosseinichimeh & Jim Duggan, 2020. "System dynamics and bio‐medical modeling," System Dynamics Review, System Dynamics Society, vol. 36(4), pages 389-396, October.

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