'Ten Commandments' for Conducting Comparative Effectiveness Research Using 'Real-World Data'

摘要

The use of "real-world data" (RWD), defined as "data used for decision-making that are not collected in conventional RCTs" (randomized controlled trials) to inform comparative effectiveness research (CER) questions holds tremendous promise, which can be realized only if such research is conducted by strictly-religiously, one might say-following good research practices. The well-recognized potential for biases associated with analysis of nonrandomized data, as well as the increasing accessibility of these data and their potential for being data-mined, might lead some to view them as "forbidden fruit" for informing medical decisions.5-6 In fact, some may argue that RWD CER results based on nonrandomized data a priori compromises their credibility. Others may argue that clinical trials that target only regulators rather than post-regulatory decision makers, including patients, consumers, payers, prescribers, and policy makers are similarly, albeit differently, flawed because they are less informative for medical decision making than pragmatic clinical trials that address patient, prescriber, and payer concerns. In both randomized trials and studies using data with nonrandom assignment, the virtues of RWD CER results are more likely to be valued by appropriately skeptical audiences if decision makers are confident that the work has been conducted and reported with a dedication to high standards.