Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
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Budget impact analyses (BIAs) are an essential part of a comprehensive economic assessment of a health care intervention and are increasingly required by reimbursement authorities as part of a listing or reimbursement submission. ⋯ We recommend a framework for the BIA, provide guidance on the acquisition and use of data, and offer a common reporting format that will promote standardization and transparency. Adherence to these good research practice principles would not necessarily supersede jurisdiction-specific BIA guidelines but may support and enhance local recommendations or serve as a starting point for payers wishing to promulgate methodology guidelines.
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This article proposes an integrated approach to the development, validation, and evaluation of new risk prediction models illustrated with the Fungal Infection Risk Evaluation study, which developed risk models to identify non-neutropenic, critically ill adult patients at high risk of invasive fungal disease (IFD). ⋯ It is cost-effective to formally assess the risk of IFD for non-neutropenic, critically ill adult patients. This integrated approach to developing and evaluating risk models is useful for informing clinical practice and future research investment.
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The US Food and Drug Administration (FDA) provides formal guidance for the use of patient-reported outcomes (PROs) in support of labeling claims, whereas the European Medicines Agency (EMA) offers insight in a reflection paper relating to health-related quality of life in lieu of formal guidance. ⋯ The EMA is more likely than the FDA to grant PRO claims and for higher order constructs. On a macro level, there appears to be poor concordance between claims granted by both agencies. On close examination, however, there appears to be greater concordance than previously recognized, which may be instructive in formulating future PRO strategies. Further research to create strategic alignment across agencies may be beneficial.
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There is a need for methodological scrutiny in the economic assessment of personalized medicine. In this article, we present a list of 10 specific issues that we argue pose specific methodological challenges that require careful consideration when designing and conducting robust model-based economic evaluations in the context of personalized medicine. Key issues are related to the correct framing of the research question, interpretation of test results, data collection of medical management options after obtaining test results, and expressing the value of tests. ⋯ Finally, it is important to understand that a test strategy does not necessarily lead to more quality-adjusted life-years (QALYs). It is possible that the test will lead to not only fewer QALYs but also fewer costs, which can be defined as "decremental" cost per QALYs. Different decision criteria are needed to interpret such results.