Literature DB >> 16247290

Economic analyses of human genetics services: a systematic review.

Josh J Carlson1, Nora Beidler Henrikson, David L Veenstra, Scott D Ramsey.   

Abstract

PURPOSE: The study's purpose was to conduct a structured review of economic analyses of genetic services. These will be increasingly valuable tools for assessing the clinical and economic outcomes of new medical technologies.
METHODS: We searched for economic studies published between January 1990 and August 2004 from a variety of publicly available databases. Articles were first reviewed to determine whether they were original studies, and second to determine whether they were formal cost-effectiveness analyses by established criteria. Articles meeting these criteria were graded using a validated rating scale.
RESULTS: Of 149 articles, 63 met established criteria for cost-effectiveness analyses. The majority (87%) were published since 1996. The majority of studies considered adult (31) or prenatal (25) conditions with the remainder considering preconception or pediatric conditions. More than half used life years gained or an ad hoc measure of outcome (e.g., cases detected). Twenty-five percent measured outcome as quality-adjusted life years. The disease areas most considered were cancer (21%) and aneuploidies (18%). The average quality ranking was 87 of 100 possible (range 48-100). Common shortcomings included lack of statement of perspective, lack of discussion of potential bias, and lack of disclosure of funding sources.
CONCLUSIONS: Relatively few economic evaluations are available for genetic services, and most are clustered in specific disease areas. Overall quality was high, but varied widely. Most shortcomings that would improve study quality are easy to address. To improve the relevance of these studies, researchers need to incorporate measures of outcome that are familiar to decision makers, including quality-adjusted life years.

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Mesh:

Year:  2005        PMID: 16247290     DOI: 10.1097/01.gim.0000182467.79495.e2

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


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