Over the last year or so I have written several articles about health systems running pragmatic clinical trials. These are designed to reflect “real-world” medical care by recruiting broad populations of patients, embedding the trial into the usual healthcare setting, and leveraging data from health systems to produce results that can be readily used to improve patient care.
For instance, I wrote about a presentation by Russell Rothman, M.D., the vice president for population health research at Vanderbilt University Medical Center, in which he described some of the informatics infrastructure of one PCORI-funded study, ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness).
ADAPTABLE is a $14 million, three-year pragmatic clinical trial that is comparing the effectiveness of two different daily doses of aspirin widely used to prevent heart attacks and strokes in individuals living with heart disease. Its goal is to enroll 20,000 patients. For that project, the Mid-South Clinical Data Research Network (CDRN) takes EHR data from health systems and transforms it into a common data model to run queries against.
The U.S. Food and Drug Administration (FDA) has been at the center of much of this work. In its Sentinel project, queries go from one organization to the distributed network and curated results are returned, using the same agreed-upon data model. Its National Evaluation System for health Technology (NEST) is designed to generate evidence across the total product lifecycle of medical devices by leveraging real-world evidence and applying advanced analytics.
Now the FDA is signaling its intent to expand its work to get real-world data from EHRs and other data sources to assess product efficacy and safety. I think this is a valuable role for the FDA to play in building a nationwide learning health system.
In a recent blog post, FDA Commission Scott Gottlieb, M.D., stated that real-world evidence can help the FDA gain a deeper understanding of a medical product’s safety and benefits, its additional treatment implications, and its potential limitations. “By better leveraging this information, we can also enable more efficient medical product development by integrating greater complements of safety and benefit information gleaned from clinical care. This is especially true when it comes to our important obligation to continue to evaluate products in the post-market setting.”
Gottlieb mentions that as part of the President’s Fiscal Year 2019 Budget, the FDA has put forward a $100 million medical data enterprise proposal to build a modern system that would rely on the electronic health records from about 10 million lives. This system would expand the data enterprise the FDA already maintains by incorporating new information from EHRs and other sources that would allow it to more fully evaluate medical products in the post-market setting.
Gottlieb noted that previous investments in post-market data have mostly focused on systems to consolidate and analyze information derived from payer claims, but the capacity to use clinical data derived from EHRs allows for faster reporting on the performance of medical products in real-world medical settings.
He pointed to a few limitations with claims data, including an inherent lag between when a medical event occurs and when it’ll show up in payer claims. Plus, he wrote, it is not always clear, by looking at claims data alone, what actually happened to the patient and whether the medical product was a factor. So the fiscal 2019 budget request seeks to address some of these limitations by giving the agency the ability to access the clinical medical information contained in de-identified electronic health records.
Interestingly, Gottlieb envisions the system created as a “national utility” for improving medical care, and allowing the FDA to optimize its regulatory decisions. “It would give patients and providers the access to near-real-time, post-market information that can better inform their decisions,” he wrote. “Such an enterprise can not only support our evaluation of safety and benefit using data derived from real-world settings, but it can also make the development of new innovations more efficient. If we have more dependable, near-real-time tools for evaluating products in real-world settings, we can allow key questions to be further evaluated in the post-market setting. This can allow some of the cost of development to be shifted into the post-market, where we can sometimes access better information about how products perform in real-world settings.
Real-world data can come from other sources such as product and disease registries, patient-related activities in outpatient or in-home use settings, and mobile health devices. So Gottlieb stressed that it is key that the sources of these data elements, such as different health care systems, be able to communicate electronically. “This requires full interoperability and the elimination of any silos. The FY 2019 Budget request seeks to establish these building blocks, and assemble the data into an interoperable platform. There are several foundational steps that we’re already undertaking to build a strong programmatic basis for using real world data and evidence.”
Some health IT leaders on Twitter responded to the blog post with enthusiasm. HL7 CTO Wayne Kubick called it a “vision which can be rapidly achieved by leveraging APIs powered by the HL7 FHIR standards, which are becoming widely available under 21st Century Cures.”
