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.
D001499:Bayes Theorem; D003657:Decision Making; D003937:Diagnosis, Differential; D006801:Humans; D008954:Models, Biological; D011336:Probability