Reviewing the evidence used in cost effectiveness models in health technology assessment: a qualitative investigation of current concerns
posterposted on 25.02.2020 by Eva Kaltenthaler, Paul Tappenden, Suzanne Paisley
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INTRODUCTION Health technology assessment (HTA) reports involve the development of a cost-effectiveness model in addition to a systematic review of the clinical effectiveness evidence. The purpose of modelling is to draw together all relevant evidence and bring this to bear on the decision problem. By its very nature, the development of the economic model requires additional information beyond clinical efficacy to inform its parameters. The way in which this is done has a fundamental impact on the results of the model and ultimately the decision outcome. Whilst there are accepted methods for reviewing efficacy within the framework of a systematic review the same is not true for the scope of evidence required for models. A systematic approach is required but it is unclear exactly what that means. Several issues need to be considered when reviewing evidence to use in populating cost-effectiveness models. Where timelines are stringent, rapid methods are needed. At the same time the approach needs to be transparent, reproducible, and systematic with precautions for minimising bias. Multiple sources of evidence will be required including: randomised controlled trials and other clinical studies, registry databases, elicitation of expert clinical judgement, industry submissions, routine costing datasets, health valuation studies, grey literature and other sources. Some of the issues around reviewing for model parameters have been highlighted in detail,1,2,3,4 yet there remains very little guidance in the literature with regard to best practice in this area. This study used qualitative methods to explore these issues more fully.
EthicsThere is no personal data or any that requires ethical approval
PolicyThe data complies with the institution and funders' policies on access and sharing
Sharing and access restrictionsThe data can be shared openly
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Methodology, headings and units
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