Professionals such as doctors and psychiatrists who work in clinical settings are often faced with difficult decisions that do not have an immediately evident "correct solution." A doctor, for instance, may need to decide how best to treat a patient when each available treatment is associated with some form of risk or danger. In such situations, a clinical professional may be able to use clinical decision analysis, a formal, mathematics-based technique for the analysis of a variety of possible choices. Clinical decision analysis is usually based on a "decision tree," a plot of possible decisions that shows possibilities at each junction of a process and the probabilities associated with each. Use of clinical decision analysis involves compiling and comparing the probabilities of certain outcomes on a decision tree to determine which "branches" of the tree are most likely to have a positive outcome.
Clinical decision analysis can be used to benefit clinical practice at many different levels. A doctor could use such formal analysis to choose the best specific treatment for an individual patient, for instance. Likewise, health professionals involved in setting health policy, such as hospital directors and many government health workers, can formally analyze the possible outcomes of various policy decisions. Even patients, given that they possess the required knowledge, can use clinical decision analysis to make the best decisions concerning their own health and treatment options.
The decision tree is the most common tool used in clinical decision analysis. Such a tree indicates the possible outcomes of each decision and the estimated probability that each outcome will actually occur. A given treatment option, for instance, may result in outcomes such as "condition cured," "condition cured with some side effects," and "condition not cured." Each outcome could lead to new decisions, each with their own outcomes and probabilities. The decision makers can multiply the probabilities along a given branch to determine the overall probability of a given final outcome.
While clinical decision analysis can provide some insight into the best way to approach a difficult decision, it is not a flawless way to consistently make perfect decisions. In many cases, formal decision analysis is used when the possible outcomes of a series of decisions have similar probabilities, so even choosing the "best" option may provide only a minimally improved chance of a positive outcome. Additionally, it can be difficult to account for the many variables that affect decision outcomes, and sometimes clinical decision analysis fails because of completely unforeseen consequences of a decision. This method of decision analysis relies on the decision maker's ability to predict consequences.
