RWD for Evaluating Device & Diagnostic Performance & Outcomes

RWD for Evaluating Device & Diagnostic Performance & Outcomes

by Richard Gliklich, MD, CEO of OM1 and Michelle Leavy, MPH, Head of Health Policy at OM1

Interest in real-world data (RWD) and real-world evidence (RWE) has increased rapidly since the passage of the 21st Century Cures Act in late 2016. Use of RWD and RWE for medical device and diagnostic products actually predated the passage of the Cures Act and, in some ways, paved the way for broader use of these data. But the emerging role of RWD and RWE is even broader. It is already playing a critical role in supporting regulatory filings, value and reimbursement decisions, and personalized treatment.

The U.S. Food and Drug Administration (FDA) defines RWD as ‘data relating to patient health status and/or the delivery of health care that are routinely collected from a variety of sources. Examples of RWD include derived from electronic health records (EHRs); patient registries, billing data and from the devices themselves. RWE is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of RWD.”

Because RWD reflect routine clinical care, these data and the resulting RWE can provide insights into medical device and diagnostic product performance and outcomes in broad populations to inform reimbursement policies, clinical guidelines, and regulatory decisions. RWD generated through patient registries have been used to support Medicare coverage decisions for ICDs, while RWD on cervical cancer screening tests have been used to inform clinical guidelines. The FDA has noted that RWE may be used in appropriate circumstances to support the approval of a new device, to support an expansion of indications for use, or to provide a control group for evaluations of safety and/or effectiveness. For example, the FDA used RWD from a patient registry to approve a new indication for a transcatheter aortic valve replacement. Using RWD, for example to extend a label in diagnostics, is particularly appealing because of the ability to gather large numbers of patients and longitudinal histories rapidly. We have also seen the opportunity to leverage RWD in place of traditional registries for post-market surveillance. The FDA has demonstrated interest in developing innovative approaches to generating and using RWD for post-marketing surveillance, including through registries. One example is the creation of coordinated registry networks (CRNs), such as the CRN for Women’s Health Technologies. The FDA developed this CRN in partnership with other agencies to establish RWD sources that use standardized data elements to capture information on technologies unique to women’s health (e.g., medical devices for uterine fibroids). The FDA Center for Devices and Radiologic Health (CDRH) has also helped the effort to use RWD for approval and post-market purposes by publishing its guidance on RWE, emphasizing relevance, reliability, and fitness for the intended purpose.

While use of RWD for regulatory approvals and commitments for device and diagnostic manufacturers has garnered significant attention, a second purpose may be growing even more rapidly. Increasingly, reimbursement authorities, both public and private payers, are interested in seeing evidence of real-world value in considering differentiation in reimbursement. At the same time, providers are entering value-based contracts with both payers and employer groups and being asked to accept some degree of pay for value in these arrangements. These relationships are driving secondary pressure on manufacturers to provide more RWE of clinical and cost-effectiveness.

The third use case for RWD is in personalizing treatment options. RWD is the key substrate for generating accurate predictive models for who is a better or higher risk candidate for a particular device or procedure as well as when in a work-up a particular diagnostic should be utilized. In our experience, from avoiding ‘bundle breakers’ in spine procedures to optimizing diagnostics in women’s health, these models will dramatically improve how specific tests and treatments will be targeted in the future and how patients with specific risk factors can be identified and optimized prior to interventions.

RWD and RWE are rapidly changing the landscape for how medical devices and diagnostics are approved, monitored, reimbursed and used in clinical practice.  Understanding and leveraging RWD is becoming a strategic imperative for manufacturers.