16
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Increasing the generalizability of economic evaluations: Recommendations for the design, analysis, and reporting of studies

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objectives:Health technology assessment (HTA) is increasingly an international activity, and HTA agencies collaborate to avoid unnecessary duplication of effort. However, the sharing of the results from HTAs raises questions about their generalizability; namely, are the results of an HTA undertaken in one country relevant to another?

          Methods:This study presents recommendations for increasing the generalizability of economic evaluations. They represent an important component of HTAs and are commonly thought to have limited generalizability.

          Results:Recommendations are given for studies using patient-level data (i.e., evaluations conducted alongside clinical trials) and for studies using decision analytic modeling.

          Conclusions:If implemented, the recommendations would increase the value for investments in HTA.

          Related collections

          Most cited references19

          • Record: found
          • Abstract: found
          • Article: not found

          A rational framework for decision making by the National Institute For Clinical Excellence (NICE).

          Regulatory and reimbursement authorities face uncertain choices when considering the adoption of health-care technologies. In this Viewpoint, we present an analytic framework that separates the issue of whether a technology should be adopted on the basis of existing evidence from whether more research should be demanded to support future decisions. We show the application of this framework to the assessment of heath-care technologies using a published analysis of a new drug treatment for Alzheimer's disease. The results of the analysis show that the amount and type of evidence required to support the adoption of a health technology will differ substantially between technologies with different characteristics. Additionally, the analysis can be used to aid the efficient design of research. We discuss the implications of adoption of this new framework for regulatory and reimbursement decisions.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Introducing economic and quality of life measurements into clinical studies.

            Although the collection of cost and quality of life data alongside clinical studies generates detailed patient level data in a timely fashion, it also raises practical and methodological challenges. These include the fact that the settings and patients enrolled in trials may not be typical of those found in regular clinical practice, that costs and quality of life may be influenced by the trial protocol, that the clinical alternatives compared in trials may not be the most relevant for cost-effectiveness assessments, that the length of follow-up may be too short to observe changes in cost and quality of life, and that adding these data will increase the overall measurement burden in the trial. This paper discusses these challenges and the ways in which they might be overcome, focussing particularly on preference-based measures of quality of life. In particular, recommendations are given for choosing the range of quality of life instruments, sample size calculations for quality of life measurement and the measurement of quality of life in multinational studies.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Principles of Good Practice for Decision Analytic Modeling in Health-Care Evaluation: Report of the ISPOR Task Force on Good Research Practices—Modeling Studies

              Mathematical modeling is used widely in economic evaluations of pharmaceuticals and other health-care technologies. Users of models in government and the private sector need to be able to evaluate the quality of models according to scientific criteria of good practice. This report describes the consensus of a task force convened to provide modelers with guidelines for conducting and reporting modeling studies.
                Bookmark

                Author and article information

                Journal
                International Journal of Technology Assessment in Health Care
                Int J Technol Assess Health Care
                Cambridge University Press (CUP)
                0266-4623
                1471-6348
                April 2005
                April 26 2005
                April 2005
                : 21
                : 2
                : 165-171
                Article
                10.1017/S0266462305050221
                15921055
                a7ad9d09-d7c2-4025-84f0-053d0bcf33dc
                © 2005

                https://www.cambridge.org/core/terms

                History

                Comments

                Comment on this article