Clinical trials evaluating medicines, medical devices, and procedures now commonly assess the economic value of these interventions. The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. As decision makers increasingly demand evidence of economic value for health care interventions, conducting high-quality economic analyses alongside clinical studies is desirable because they broaden the scope of information available on a particular intervention, and can efficiently provide timely information with high internal and, when designed and analyzed properly, reasonable external validity. In 2005, ISPOR published the Good Research Practices for Cost-Effectiveness Analysis Alongside Clinical Trials: The ISPOR RCT-CEA Task Force report. ISPOR initiated an update of the report in 2014 to include the methodological developments over the last 9 years. This report provides updated recommendations reflecting advances in several areas related to trial design, selecting data elements, database design and management, analysis, and reporting of results. Task force members note that trials should be designed to evaluate effectiveness (rather than efficacy) when possible, should include clinical outcome measures, and should obtain health resource use and health state utilities directly from study subjects. Collection of economic data should be fully integrated into the study. An incremental analysis should be conducted with an intention-to-treat approach, complemented by relevant subgroup analyses. Uncertainty should be characterized. Articles should adhere to established standards for reporting results of cost-effectiveness analyses. Economic studies alongside trials are complementary to other evaluations (e.g., modeling studies) as information for decision makers who consider evidence of economic value along with clinical efficacy when making resource allocation decisions.

Trial-based cost-effectiveness studies have appeal because of their high internal validity and timeliness. Improving the quality and uniformity of these studies will increase their value to decision makers who consider evidence of economic value along with clinical efficacy when making resource allocation decisions.

PurposeReal‐world evidence (RWE) includes data from retrospective or prospective observational studies and observational registries and provides insights beyond those addressed by randomized controlled trials. RWE studies aim to improve health care decision making.MethodsThe International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the International Society for Pharmacoepidemiology (ISPE) created a task force to make recommendations regarding good procedural practices that would enhance decision makers' confidence in evidence derived from RWD studies. Peer review by ISPOR/ISPE members and task force participants provided a consensus‐building iterative process for the topics and framing of recommendations.ResultsThe ISPOR/ISPE Task Force recommendations cover seven topics such as study registration, replicability, and stakeholder involvement in RWE studies. These recommendations, in concert with earlier recommendations about study methodology, provide a trustworthy foundation for the expanded use of RWE in health care decision making.ConclusionThe focus of these recommendations is good procedural practices for studies that test a specific hypothesis in a specific population. We recognize that some of the recommendations in this report may not be widely adopted without appropriate incentives from decision makers, journal editors, and other key stakeholders.

Purpose: Real-world evidence (RWE) includes data from retrospective or prospective observational studies and observational registries and provides insights beyond those addressed by randomized controlled trials. RWE studies aim to improve health care decision making. Methods: The International Society for Pharmacoeconomics and Outcomes Research (ISPOR)and the International Society for Pharmacoepidemiology (ISPE) created a task force to make recommendations regarding good procedural practices that would enhance decision makers' confidence in evidence derived from RWD studies. Peer review by ISPOR/ISPE members and task force participants provided a consensus-building iterative process for the topics and framing of recommendations.Results: The ISPOR/ISPE Task Force recommendations cover seven topics such as study registration, replicability, and stakeholder involvement in RWE studies. These recommendations, in concert with earlier recommendations about study methodology, provide a trustworthy foundation for the expanded use of RWE in health care decision making. Conclusion:The focus of these recommendations is good procedural practices for studies that test a specific hypothesis in a specific population. We recognize that some of the recommendations in this report may not be widely adopted without appropriate incentives from decision makers, journal editors, and other key stakeholders. KEYWORDScomparative effectiveness, decision making, guidelines, pharmacoepidemiology, real-world data, treatment effectivenessThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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We evaluated four methods for computing confidence intervals for cost-effectiveness ratios developed from randomized controlled trials: the box method, the Taylor series method, the nonparametric bootstrap method and the Fieller theorem method. We performed a Monte Carlo experiment to compare these methods. We investigated the relative performance of each method and assessed whether or not it was affected by differing distributions of costs (normal and log normal) and effects (10% absolute difference in mortality resulting from mortality rates of 25% versus 15% in the two groups as well as from mortality rates of 55% versus 45%) or by differing levels of correlation between the costs and effects (correlations of -0.50, -0.25, 0.0, 0.25 and 0.50). The principal criterion used to evaluate the performance of the methods was the probability of miscoverage. Symmetrical miscoverage of the intervals was used as a secondary criterion for evaluating the four methods. Overall probabilities of miscoverage for the nonparametric bootstrap method and the Fieller theorem method were more accurate than those for the other the methods. The Taylor series method had confidence intervals that asymmetrically underestimated the upper limit of the interval. Confidence intervals for cost-effectiveness ratios resulting from the nonparametric bootstrap method and the Fieller theorem method were more dependably accurate than those estimated using the Taylor series or box methods. Routine reporting of these intervals will allow individuals using cost-effectiveness ratios to make clinical and policy judgments to better identify when an intervention is a good value for its cost.

The LCM and TPM with a log-transformed dependent variable are superior to other approaches in handling data with ceiling effects.

The second section of our Special Task Force builds on the discussion of value and perspective in the previous article of the report by 1) defining a health economics approach to the concept of value in health care systems; 2) discussing the relationship of value to perspective and decision context, that is, how recently proposed value frameworks vary by the types of decisions being made and by the stakeholders involved; 3) describing the patient perspective on value because the patient is a key stakeholder, but one also wearing the hat of a health insurance purchaser; and 4) discussing how value is relevant in the market-based US system of mixed private and public insurance, and differs from its use in single-payer systems. The five recent value frameworks that motivated this report vary in the types of decisions they intend to inform, ranging from coverage, access, and pricing decisions to those defining appropriate clinical pathways and to supporting provider-clinician shared decision making. Each of these value frameworks must be evaluated in its own decision context for its own objectives. Existing guidelines for cost-effectiveness analysis emphasize the importance of clearly specifying the perspective from which the analysis is undertaken. Relevant perspectives may include, among others, 1) the health plan enrollee, 2) the patient, 3) the health plan manager, 4) the provider, 5) the technology manufacturer, 6) the specialty society, 7) government regulators, or 8) society as a whole. A valid and informative cost-effectiveness analysis could be conducted from the perspective of any of these stakeholders, depending on the decision context.