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Physician, Regulatory, and Payer Perspectives on the Value of Real-World Data

Surabhi Dangi-Garimella, PhD
One of the kickoff sessions on the first day of the 2017 American Society of Clinical Oncology Annual Meeting in Chicago, Illinois, was a lively discussion on ensuring that the data used to inform patient care and create healthcare policies holds value.
Providing the FDA’s perspective on real-world data was Sean Khozin, MD, MPH, senior medical officer at the FDA. Khozin reviewed how the FDA is using real-world evidence in the context of regulatory decision-making.

Khozin provided a timeline of human progress across over the past several decades, which included the development of steam and gas locomotives, the moon landing, and the Internet explosion, among others. However, the clinical trial model remains rudimentary, he said.

“There remains room for improvement in RCTs,” Khozin explained. “We trust these results because they have robust internal validity.” He described the structure of RCTs as a “validity imbalance,” with an overcompensation of internal validity and an external-validity deficit.

RCTs also have poor generalizability—there is no median or average patient “That is just a statistical concept.” So, treatment decisions based on the ‘median’ outcome of a trial will not help us maximize the potential of precision oncology.

Khozin went ahead to outline the characteristics of real-world data, he explained is mostly based on why the data were collected, meaning the intent of data collection: within the controlled settings of a clinical trial or in the real-world of a physician’s office.

“Real-world data helps retrospective analysis,” Khozin explained, which can be achieved using electronic health record (EHR) data that is cleaned up. EHRs have a structured (billing and lab codes, patient history and demographics) and an unstructured component (physician notes and diagnostic reports).

Speaking with The American Journal of Managed Care® in November 2016, Khozin said that one component of the FDA’s Information Exchange and Data Transformation initiative is using real-world evidence, in the form of EHRs, to guide regulatory decisions. He explained that exclusion criteria in clinical trials can be limiting, so the data from clinical trials may not reflect the patients being treated in the real world.

“We can change the intent of data collection from research to real-world data, by providing clinicians incentives to do so,” Khozin said during the ASCO session. This is how pragmatic or prospective trials are defined. Khozin stated that frameworks exist for real-world data collection and that the FDA is not concerned with the original intent of data collection, since there are processes in place to scrutinize the submitted information.

Real-world data can be used for:
  • Pharmacovigilance. Currently a passive process associated with voluntary reporting of adverse events, real-world data can power an active pharmacovigilance program (eg, FDA’s Sentinel program and direct EHR abstraction).
  • Benchmarking. To develop historical control benchmarks to inform future trial designs, and to provide reliable safety and efficacy data.
  • Conduct pragmatic clinical trials. To allow for point-of-care clinical decisions, EHRs are vehicles for prospective clinical research at point of care, can support randomization, are patient-centric, and may bend the cost curve.
The primary challenge with real-world data, Khozin said, is ensuring data quality and the need to provide the right incentives at the point of care to extract clinically relevant data. “This is more an organizational issue.”

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