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Change will be needed to harness the knowledge of real-world evidence

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By Mari Serebrov
Regulatory Editor

The FDA may be under a congressional mandate to advance the use of real-world evidence in its regulatory decisions, but many of the obstacles in getting the patient data needed to generate that evidence are beyond the agency's reach.

"Medicine is largely in the reimbursement business," Laura Esserman, a professor and surgeon at the University of California-San Francisco School of Medicine, said at a workshop Wednesday on the regulatory use of real-world evidence. Thus, electronic health records (EHRs), which contain much of the real-world data available, are based on the paper records of old and are geared more toward payment than patient experience.

For instance, patients may be suffering from fatigue, but that fact could be absent from their EHRs because that wasn't the billable purpose of the appointment. And while prescriptions are captured in the record, the reason for the prescription isn't, said Sally Okun, vice president for advocacy, policy and patient safety at Patientslikeme.

The goal of generating evidence from real-world data is to create a "learning health care system" that basically writes living textbooks for medical products and practices and that can expedite approval and safety decisions while maximizing benefit and minimizing the risk for individual patients.

"This is a process. We have some new building blocks and tools," the FDA's Rich Moscicki said in his introductory remarks at the workshop hosted by the Duke-Margolis Center for Health Policy. He noted that by 2015, nearly 100 percent of U.S. hospitals and 90 percent of doctors were using some form of EHR. In addition, numerous mobile technologies are now available to produce real-world data.

The adoption of such technologies has created a diversity of data and systems to collect that data; the diversity makes it challenging to transform patient data into rigorous real-world evidence. EHRs were not designed for research, Moscicki said, noting the need for standardization of the data, regardless of its source. Other challenges are verifying the data, minimizing bias and finding ways to bridge from randomized controlled trials to real-world evidence and vice versa.

Not there yet

"The EHRs of today are an enormous step forward," said Marc Berger, of the International Society for Pharmacoeconomics and Outcomes Research. But they're not where they need to be. He noted a fatigue among doctors with having to enter multiple datapoints in an EHR while trying to communicate with their patients.

Esserman agreed, saying there should be a limit on how much data each person has to enter. And throughout the workshop, one speaker after another emphasized that the data captured should matter to patients and inform their care.

With much of the data currently intended for payers, the information may be closely held – even though it's broadly recognized as belonging to the patient. For example, one of the biggest difficulties in a platform trial centered on breast cancer is getting breast density information when the scans are done elsewhere, Esserman said.

The technology companies creating the EHR systems and payers also can be barriers, said Joe Selby, executive director of the Patient-Centered Outcomes Research Institute. To realize the full promise of real-world evidence, every holder of the data must be involved. Selby suggested having patients bring pressure to ensure their data are being shared appropriately.

In the meantime, the FDA is using real-world evidence, mostly for postmarket pharmacovigilance and to some extent in support of approvals for products treating rare diseases. But there's so much more that could be done with it. The next step would be the use of real-world evidence for label expansions, several experts said.

To get to the future from here, mindsets and skill sets will have to change – at the FDA, in medical schools and in practice, Esserman said. The purpose of health care at every step should be to improve the care for patients, and that means using real-world evidence to inform that care rather than practicing medicine the same way it's been done for the past 75 years, she added.

The data may have to change, too, along with how they're shared and analyzed. In addition to better linkages, Selby called for data standardization that includes new meaningful measures rather than just claims info. He also made a case for building a trial infrastructure for future observational studies and for more demonstration projects that can blaze new trails in this area of research.

Greg Daniel, who co-authored the new Duke-Margolis white paper "A Framework for Regulatory Use of Real-World Evidence," cited the need to coordinate the demonstration projects already being done so everyone knows who's doing what. Other steps he recommended include:

• improving standards and data collection methods;

• improving the credibility of observational studies and randomizing clinical experience;

• developing evidence-based approaches in research design;

• engaging patients in research design;

• establishing governance of the data;

• developing novel analytic techniques to take advantage of today's computing power.

Industry representatives at the meeting had their own thoughts on next steps, namely regulatory clarity. There is a collaborative spirit among industry when it comes to using real-world data for biomarkers, Symantha Melemed, of Eli Lilly and Co. Inc., said, adding that regulatory clarity would help industry better aim that collaboration.

Industry is excited about the possibilities of real-world evidence, as it could be used for dosing, historical controls, biomarkers, in control arms with rare diseases, label extensions and rapid learning in single-arm trials, Melemed said. But everyone involved will have to evolve to this new way of thinking at the same time.

"This is an innovation. . . . We're excited to get started," Melemed said.