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Guidelines exist for the conduct and review of ecomic evaluations. In the United States, the systematic review of ecomic outcomes and the inclusion of ecomic data in systematic reviews have t been standardized as much as is the case for clinical outcomes. The lack of standardization leads to large variation in the quality of ecomic evaluations and in the use of ecomic data in systematic reviews. This suggests a need to establish some standards in the United States. Systematic reviews play a critical role in determining the comparative effectiveness of medical interventions and are critical for developing clinical practice guidelines, efficacy-based coverage decisions, and general health policy. As such, the processes of searching for and summarizing studies illustrating clinical efficacy and effectiveness have been streamlined in the United States and elsewhere. While much work is being done to evaluate the comparative effectiveness of medical interventions, the United States has fallen behind international best practices in using ecomic data in the comparison of medical interventions for the purposes of policymaking. With increased awareness of the importance of evaluating value for money in health care, the number of published ecomic evaluations has increased in recent years. As more ecomic analyses are produced, researchers and policymakers need to have methods to synthesize and interpret the results of multiple analyses that address a single issue; systematic review offers a framework for doing this. However, systematic reviews of ecomic analyses pose special challenges for those who perform reviews and those who use them. Traditional techniques of meta-analysis are t appropriate for many ecomic analyses, which are often syntheses, as in the case of ecomic modeling studies, and hence should t be combined as one might combine the results of different randomized controlled trials. Instead, systematic reviews of ecomic modeling studies are most useful for comparing and contrasting how different investigators have chosen to structure their models and estimate key variables. They can also clarify how results differ between studies based on these different assumptions. Identifying sources of variation across studies can help individual decisionmakers determine which studies best apply to their particular settings and can guide future research by identifying areas of uncertainty. A little over a decade ago, health ecomists had t yet developed a formal methodology for reviewing and summing up evidence from individual ecomic evaluations...or indeed for assessing whether systematic reviews are possible in this context. Today, there are as yet widely validated methodological criteria to be applied to screening ecomic studies for inclusion in systematic reviews. The difficulty with developing systems to evaluate best practices for conducting ecomic evaluations is that each ecomic evaluation faces a potentially unique set of constraints relative to gold standard sets of recommendations. Systems proposed to date have listed criteria for the assessment of ecomic evaluations, yet have hardly tested comparative rating and weighting of technical criteria. This comparative weighting and the need to determine whether strength in one area can offset a deficiency in ather will be critical to the success of the system that is developed. However, it is t clear that systems that will result in a relative ranking of studies that are t perfect can provide anything other than an approximate estimate of the comparative validity of differing results. Nevertheless, there is unquestionably an urgent need for improving the design, analysis and reporting of ecomic evaluations in health care. The aim of this paper is to review the strengths and weaknesses of checklists that have been used to evaluate best practices for conducting ecomic evaluations in health care.