N Engl J Med 2017; 377:957-964 September 7, 2017DOI: 10.1056/NEJMra1510058
Niteesh K. Choudhry, M.D., Ph.D.
|Randomized Contolled Trials|| highest cost, |
Cannot adapt treatment to the patient
|Pragmatic Trials||lower cost, more real-world than RCT|
|Health Insurance||very low cost, the most real-world|
a lot of data
The well-recognized limitations of traditional randomized, controlled trials (RCTs), including their cost, the nature of the patients and providers included in them, and even the types of interventions that they can evaluate, have led to the search for alternative methods and settings for conducting these types of studies. Pragmatic trials,1 also referred to as “practical” or “effectiveness” trials, have been widely advocated as means of addressing these limitations. These designs rely on simplified data-collection processes, strategies such as broad eligibility criteria for both patients and providers, and an acceptance of protocol “violations” such as crossover, nonadherence, and loss to follow-up that make the trial conditions similar to the way in which care is delivered in routine practice.2-5
Many of the pragmatic trials that have appeared in the peer-reviewed literature have recruited patients individually from traditional care settings such as physician offices or hospitals and have prospectively collected baseline and outcome data.6-8 As a result, although aspects of their design provide tremendous efficiencies and greatly enhance generalizability, many pragmatic trials share the fundamental features of traditional RCTs that make them cumbersome to conduct. To address this problem, “registry randomized trials” that leverage the existing participant-identification and data-collection efforts of disease registries have been proposed,9 but registries themselves usually require an expensive infrastructure and trials embedded in them cannot, by definition, be conducted when no relevant registry exists.
Another alternative is to embed trials within health insurance systems and to use the massive amounts of data that insurers generate and collect in the process of administering health benefits (Figure 1)
Typical Features of Different Types of Randomized, Controlled Trials (RCTs).). Information from “claims” submitted to insurers by health care institutions, providers, or diagnostic facilities is commonly used in observational comparative-effectiveness studies and health services research studies but can also provide efficiencies (e.g., the evaluation of study outcomes without the need for prospective data collection) for RCTs. In addition, because the way in which patients interact with insurers is very different from the way in which patients interact with providers in traditional clinical environments, trials that are based in health insurance systems may provide new ways of administering the interventions to be tested and may in fact be the most rigorous way to determine how health insurance itself should be structured. Of course, the potential advantages of trials that are conducted with the use of health insurance data and that are based in health insurance systems create new methodologic challenges. This article outlines some of the considerations, with an emphasis on studies that leverage the data and infrastructure of health insurance systems to identify and evaluate a broad range of clinically relevant and policy-relevant questions.
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