Rethinking Randomized Clinical Trials for Comparative Effectiveness Research: The Need for Transformational Change

摘要

Join the dialogue on health care reform. Comment on the perspectives published in Annals and offer ideas of your own. All thoughtful voices should be heard. nnWhile advances in medical science have led to continued improvements in medical care and health outcomes, evidence of the comparative effectiveness of alternative management options remains inadequate for informed medical care and health policy decision making. The result is frequently suboptimal and inefficient care as well as unsustainable costs. To enhance or at least maintain quality of care as health reform and cost containment occurs, better evidence of comparative clinical and cost-effectiveness is required (1). nnThe American Recovery and Reinvestment Act of 2009 allocated a $1.1 billion “down payment” to support comparative effectiveness research (CER) (2). Although comparative effectiveness can be informed by synthesis of existing clinical information (systematic reviews, meta-analysis, and decision modeling) and analysis of observational data (administrative claims, electronic medical records, registries and other clinical cohorts, and case–control studies), randomized clinical trials (RCTs) are the most rigorous method of generating comparative effectiveness evidence and will necessarily occupy a central role in an expanded national CER agenda. nnHowever, as currently designed and conducted, many RCTs are ill suited to meet the evidentiary needs implicit in the IOM definition of CER: comparison of effective interventions among patients in typical patient care settings, with decisions tailored to individual patient needs (3). Without major changes in how we conceive, design, conduct, and analyze RCTs, the nation risks spending large sums of money inefficiently to answer the wrong questions—or the right questions too late. nnThis article addresses several fundamental limitations of traditional RCTs for meeting CER objectives and offers 3 potentially transformational approaches to enhance their operational efficiency, analytical efficiency, and generalizability for CER.