Title: Medical evidence evaluation using a multi-stage Bayesian approach

Authors: Paul S. Koku, Anique A. Qureshi

Addresses: Florida Atlantic University, College/Graduate School of Business, University Tower, 220 S.E. 2nd Ave., Fort Lauderdale, FL 33301, USA. Queens College, City University of New York, USA

Abstract: Analyses of errors in medical diagnoses have generally been confined to the application of single-stage Bayesian models. While this approach is illuminating, it limits the scope of analyses to those inherent in the equipment and/or the test. However, the ability of a physician to correctly interpret the results produced by equipment, or a test, could also have a profound effect on the accuracy of diagnosis. Using a single-stage Bayesian approach underestimates the likelihood of error. In this paper, we show that by using a multi-stage Bayesian model we can incorporate the ability of a physician to interpret test results accurately. By combining the physician|s ability with the accuracy of the equipment or test, it is possible to obtain a better estimate of the probability of making mistakes with medical diagnoses.

Keywords: Bayesian; diagnoses; evaluation; evidence; medical; model.

DOI: 10.1504/IJHTM.1999.001059

International Journal of Healthcare Technology and Management, 1999 Vol.1 No.1/2, pp.125-130

Published online: 30 Jun 2003 *

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