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A Statistical Evaluation of Recurrent Medical Examinations

Author

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  • Thomas L. Lincoln

    (University of Maryland, College Park, Maryland)

  • George H. Weiss

    (University of Maryland, College Park, Maryland)

Abstract

In this paper we consider the efficiency of different policies for scheduling medical examinations in a search for diseases like cancer, which start without overt symptoms. We treat both periodic and random examinations and allow for imperfect diagnosis depending on how long the disease has been present. The results of our theory are then checked against a rough data fit to the incidence curve of cervical cancer.

Suggested Citation

  • Thomas L. Lincoln & George H. Weiss, 1964. "A Statistical Evaluation of Recurrent Medical Examinations," Operations Research, INFORMS, vol. 12(2), pages 187-205, April.
    • Handle: RePEc:inm:oropre:v:12:y:1964:i:2:p:187-205
    DOI: 10.1287/opre.12.2.187
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    Cited by:

    1. Jonathan E. Helm & Mariel S. Lavieri & Mark P. Van Oyen & Joshua D. Stein & David C. Musch, 2015. "Dynamic Forecasting and Control Algorithms of Glaucoma Progression for Clinician Decision Support," Operations Research, INFORMS, vol. 63(5), pages 979-999, October.
    2. 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.
    3. John D. Rice & Brent A. Johnson & Robert L. Strawderman, 2022. "Screening for chronic diseases: optimizing lead time through balancing prescribed frequency and individual adherence," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(4), pages 605-636, October.

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