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Improving clinician-patient communication of health risks when diagnostic test information is imprecise
1Department of Economics, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. john.fountain@canterbury.ac.nz
Abstract:
Both clinicians and patients experience difficulty with the statistical reasoning required to make inferences about health states on the basis of information derived from diagnostic tests. This problem will grow in importance as we move into the era of personalised medicine where an increasing supply of imprecise diagnostic tests meets an increasing demand to use such tests on the part of intelligent but statistically innumerate clinicians and patients. We describe a user-friendly, interactive, graphical interface for calculating, visualising, and communicating accurate inferences about uncertain health states when diagnostic information (test sensitivity and specificity, and health state prevalence) is imprecise and ambiguous in its application to a specific patient. The software is free, open-source, and runs on all popular PC operating systems (Windows, Mac, Linux).
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