Abstract
OBJECTIVE: Providing patient-centered care requires consideration of numerous factors when making decisions that will influence a patient's health status. BACKGROUND: Clinical decisions should be informed by relevant research evidence, but the literature often lacks pertinent information for problems encountered in routine clinical practice. Although a randomized clinical trial provides the best research design to ensure the internal validity of study findings, ethical considerations and the competitive culture of sport often preclude random assignment of patients or participants to a control condition. CLINICAL ADVANTAGES: A cohort study design and Bayesian approach to data analysis can provide valuable evidence to support clinical decisions. Dichotomous classification of both an outcome and 1 or more predictive factors permits quantification of the likelihood of occurrence of a specified outcome. CONCLUSIONS: Multifactorial prediction models can reduce uncertainty in clinical decision making and facilitate the individualization of treatment, thereby supporting delivery of clinical services that are both evidence based and patient centered.