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Clinical Decision Analysis

Since its introduction in the mid-1970s, the clinical usefulness of medical decision analysis has been debated. Advocates have argued that the use of clinical decision analysis will improve the quality of health care by enabling clinicians and patients to consistently make informed decisions that incorporate both current biomedical knowledge and individual patient values and preferences. Critics, on the other hand, have questioned the validity of clinical recommendations based on decision analysis models and assumptions. The article by Aoki and colleagues in this issue of Medical Decision Making speaks directly to this issue. In this article, the authors update the results of a decision analysis originally published in the fall of 1998 addressing the clinical management of patients with known, unruptured cerebral aneurysms. This reanalysis was prompted by the publication of a report from the International Study of Unruptured Intracranial Aneurysms that provided new information about the natural history of unruptured aneurysms and the outcomes of preventive surgery that was unavailable and “wished for” at the time the original analysis was performed. The original analysis concluded that for the base case, a healthy 40-year-old man with an unruptured anterior aneurysm less than 10 mm in diameter, preventive surgery was preferable to watchful waiting. In contrast, the results of the revised analysis lead to the opposite clinical recommendation: watchful waiting without surgery. The slow diffusion of valid new medical information into practice is widely recognized as a potentially reversible factor that negatively affects the quality of care. The 2 articles by Aoki and colleagues illustrate how decision analysis can facilitate the process of translating clinical research into practice by providing a way to explore the effects of new information on practice that takes the clinical context, patient-specific factors, and other pertinent medical evidence into account. The results of such analyses should help practitioners and health care policy makers make quicker, more insightful decisions regarding the clinical implications of new research by addressing 2 major barriers to making full use of clinical research in practice: proper integration of new findings with existing information and mismatches between research data and clinical circumstances. Although these 2 analyses illustrate how decision analysis can be used to improve the quality of patient care, they also raise some concerning questions that need to be addressed before the potential benefits of clinical decision analysis can be fully realized. The 1st is why wasn’t the uncertainty about the true values of several important input variables more clearly reflected in the original study’s conclusions? The rise of evidence-based medicine in recent years has focused attention on assessing the validity of medical information and using the highest quality, most valid information available in formulating clinical practice recommendations. A major result has been the publication of evidence-based practice guidelines that include both recommendations for practice and a summary of the strength of the evidence supporting them, a combination that enables clinicians and other users of the guidelines to make more informed decisions about their appropriate use in practice. (A good example is the 2nd report of the U.S. Preventive Services Task Force.) These rules of evidence were well established and commonly used at the time the original analysis was published in 1998 but, following standard decision analysis practice, were not mentioned in the published report and presumably not used during the analysis. The results of the 2nd analysis demonstrate that the usual decision analysis approach to uncertainty about important input data, sensitivity analysis, failed to guarantee the validity of the original conclusions. These findings clearly indicate that it