Clinical prediction rules: what are they and what do they tell us?

Clinical prediction rules are research-based tools that quantify the contributions of relevant patient characteristics to provide numeric indices that assist clinicians in making predictions. Clinical prediction rules have been used to describe the likelihood of the presence or absence of a condition, assist in determining patient prognosis, and help the classification of patients for treatment. The recent rapid rise in the use of clinical prediction rules raises questions about the conditions under which they may be used most appropriately. What is the potential role of clinical prediction rules in physiotherapy practice and what are the strategies by which clinicians can determine their appropriate use for a given clinical setting?

Clinical prediction rules use quantitative methods to build upon the body of literature and expert opinion and can provide quick and inexpensive estimates of probability. Clinical prediction rules can be of great value to assist clinical decision making but should not be used indiscriminately. They are not a replacement for clinical judgment and should complement rather than supplant clinical opinion and intuition. The development of valid clinical prediction rules should be a goal of physiotherapy research. Specific areas in need of attention include deriving and validating clinical prediction rules to screen patients for potentially serious conditions for which current tests lack adequate diagnostic accuracy or have unacceptable cost and risk, and to assist in classification of patients for treatments that are likely to result in substantially different outcomes in heterogeneous groups of patients.