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BACKGROUND: Bipolar disorder (BD) is a chronic illness and is one of the worldwide leading causes of disability. It is often a lifelong illness and incurs a substantial economic burden on the health care system, the patients, and society as a whole. However, there are few studies evaluating the economic impact of alternative strategies in the management of BD. OBJECTIVES: We reviewed and critically appraised the available published economic evidence on BD management. In addition, we explored advantages and disadvantages of different methods used in the economic evaluation of the management of BD. METHODS: A systematic literature search was undertaken using seven electronic databases to identify all English language articles published between January 1980 and March 2012 that provided data on complete economic evaluations for any treatment strategy for BD. The quality of included studies was appraised according to recommendations from the Cochrane Collaboration. RESULTS: A total of 7,284 citations were obtained. After initial screening, 20 eligible studies were identified, five of which were trial-based, and 15 of which were model-based economic evaluations. Given the variability in methods and the quality of the identified studies, no conclusive recommendation for the most cost-effective therapy for BD could be provided. CONCLUSIONS: The cost-effectiveness of different treatment strategies varied between settings, and transferability of these results across settings remains questionable. Although additional research using a longer time horizon is required to validate the findings for trial-based economic evaluations, discrete event simulation appears to be the most natural and plausible technique for modeling the cost-effectiveness of alternative BD treatment strategies.

Original publication





Bipolar Disord

Publication Date





557 - 582


bipolar disorder, collaborative care, cost-effectiveness, economic evaluation, pharmacoeconomics, systematic review, Bipolar Disorder, Cost-Benefit Analysis, Disease Management, Electronic Health Records, Humans