Introduction to Clinical Decision Making
In the last few years there has been a remarkable increase in the amount of clinical data in the average hospital chart, and more and more problem-solving algorithms have been developed. We need better “thinking tools” to help us handle the flow of information. The term “clinical decision making” is used to describe a systematic way to handle data and algorithms to decide on a best course of action. This introductory article discusses some of the problems in establishing a decision criterion, both for a population and for an individual patient. Comparing the probabilities and utilities of various diagnostic outcomes (true positive, false positive, etc.) leads to a diagnostic strategy. The article also discusses conditional probability. Bayes' theorem, and likelihood ratios.
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Reprinted from Seminars in Nuclear Medicine, Vol 8, No 4, October 1978, pages 273-282.
PII: S0001-2998(10)00046-2
doi:10.1053/j.semnuclmed.2010.05.001
© 2010 Elsevier Inc. All rights reserved.
