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Knowing for the Sake of Knowing

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  • David A. Asch
  • James P. Patton
  • John C. Hershey

Abstract

In evaluating diagnostic tests, traditional methods in decision analysis often emphasize how the results of the test will or will not affect patient management. Clinicians are advised to avoid testing if the results will not alter treatment strategy or other management plans. But patients may be interested in the prognostic information that testing provides even if it is not used to guide treatment. The authors present a model that defines this prognostic information as the expected deviation from the prior probability of disease. The model generates utility functions that are curvilinear over prior probabilities. Whereas the traditional threshold ap proach to medical decision making produces at most three zones of management strategy (withhold, test, and treat), the incorporation of prognostic information into threshold analysis produces two additional zones (test but withhold anyway, and test but treat anyway). Con ditions under which one or both of these additional zones will appear are described. The model justifies the practice of performing tests that cannot alter management plans; it explains the unwillingness of some patients to undergo diagnostic testing when they fear unwanted results; and it provides a method for quantifying the sensitive nature of confidential tests. The model is illustrated using the antibody test for the Smith antigen. This test has a high specificity but a low sensitivity for lupus erythematosus. Clinicians may use the test because a positive result will support their prior suspicion of disease even though they may not change their management strategy if the test result is negative. The advantage of testing in this setting lies in the test's potential for establishing with virtual certainty that the disease is present. Thus, the test is valued for the prognostic information it provides apart from its effect on patient management. Key words : confidentiality; decision making; diagnostic tests; in formation theory; privacy; probability; prognosis; utility analysis. (Med Decis Making 1990;10:47-57)

Suggested Citation

  • David A. Asch & James P. Patton & John C. Hershey, 1990. "Knowing for the Sake of Knowing," Medical Decision Making, , vol. 10(1), pages 47-57, February.
    • Handle: RePEc:sae:medema:v:10:y:1990:i:1:p:47-57
    DOI: 10.1177/0272989X9001000108
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    References listed on IDEAS

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    1. David E. Bell, 1985. "Disappointment in Decision Making Under Uncertainty," Operations Research, INFORMS, vol. 33(1), pages 1-27, February.
    2. David E. Bell, 1982. "Regret in Decision Making under Uncertainty," Operations Research, INFORMS, vol. 30(5), pages 961-981, October.
    3. Brian E. Forst, 1974. "Decision Analysis and Medical Malpractice," Operations Research, INFORMS, vol. 22(1), pages 1-12, February.
    4. Harold Bursztajn & Robert M. Hamm & Thomas G. Gutheil & Archie Brodsky, 1984. "The Decision-Analytic Approach to Medical Malpractice Law," Medical Decision Making, , vol. 4(4), pages 401-414, December.
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    Cited by:

    1. Camerer, Colin & Weber, Martin, 1992. "Recent Developments in Modeling Preferences: Uncertainty and Ambiguity," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 325-370, October.
    2. Russell Golman & George Loewenstein & Andras Molnar & Silvia Saccardo, 2022. "The Demand for, and Avoidance of, Information," Management Science, INFORMS, vol. 68(9), pages 6454-6476, September.
    3. Steven J. Kachelmeier, 1996. "Discussion of “Tax Advice and Reporting Under Uncertainty: Theory and Experimental Evidence†," Contemporary Accounting Research, John Wiley & Sons, vol. 13(1), pages 81-89, March.
    4. Bernd Lütkenhöner & Türker Basel, 2013. "Predictive Modeling for Diagnostic Tests with High Specificity, but Low Sensitivity: A Study of the Glycerol Test in Patients with Suspected Menière’s Disease," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-12, November.
    5. Peter J. Neumann & Joshua T. Cohen & James K. Hammitt & Thomas W. Concannon & Hannah R. Auerbach & ChiHui Fang & David M. Kent, 2012. "Willingness‐to‐pay for predictive tests with no immediate treatment implications: a survey of US residents," Health Economics, John Wiley & Sons, Ltd., vol. 21(3), pages 238-251, March.

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