Randomized clinical trials (RCTs) help provide information on safety and outcomes of drugs and devices, but there are problems to using RCTs that can be solved with the help of data stored in electronic health records.
The "richness and immediacy [of data] could allow tailored treatment decisions in real-time," according to a viewpoint published this week in the Journal of the American Medical Association by Derek Angus, M.D., chairman of the Department of Critical Care Medicine at the University of Pittsburgh.
However, the "singular beauty of the RCT is the strength of casual inference that arises from random assignment," he writes.
Neither of these is a perfect solution when standing alone, but if they can be fused, therein lies great promise, Angus says.
Some of the problems that fusing data and RCTs can solve, according to Angus, include:
- Cost and ease of use: A good amount of infrastructure is needed for RCTs, but integrating them with the EHR could reduce costs, he writes. In addition, the EHR could help enroll patients in trials and generate treatment assignments. However, Angus adds that there are barriers to this, including data system integration, oversight of the system and patient privacy protections.
- Patient, clinician comfort with randomization: RCTs can use a similar approach to a tailored big data decision support to assign patients to trials, Angus writes. Currently the randomization ratio is 50:50, but by using an adaptive trial technique, "response-adaptive randomization," the odds a patient is assigned to a poorly faring treatment group will lessen over time.
- Slow knowledge translation: One of the best ways to improve RCTs through addition of data would be to fuse all elements into a new RCT called "a randomized, embedded, multifactorial, adaptive platform (REMAP) trial," he writes. This new trial would incorporate adaptive designs and big data to function not just as a research study, but also as a "continuous quality improvement program," according to Angus.
While randomized controlled trials have been the gold standard, "it will be critical to identify where the evidence generated by big data is adequate enough to change practice. In other cases, big data may generate new paradigms for increasing the efficiency of randomized clinical trials," according to Mayo Clinic researchers Nilay D. Shahan and Jyotishman Pathak.
The U.S. Food and Drug Administration announced in June an interest in considering the use of electronic health records with electronic data capture in order to improve clinical trials for new and investigational drugs.
To learn more:
- get the viewpoint (subscription required)