BIO panel: Fast, robust data will clear reimbursement path for digital therapeutics

2016-06-13

Digital health and digital therapeutics will produce a tremendous amount of data, which could be the key to getting them reimbursed by payers, according to panelists at BIO 2016 last week. UCSF Professor of Health Economics and Health Services Research Kathryn Phillips led a panel that included Rowan Chapman, managing director of new business ventures at GE Ventures; Evidation Health CEO Deborah Kilpatrick; and Nicole Littman, vice president client services at Quorum Consulting. The panelists talked about Proteus Digital Health's sensor-embedded pharmaceuticals as one example of a digital medicine or digital therapeutic. Littman said few payers have elected to cover Proteus so far. "What payers are saying in their non-coverage statement is there are no clinical utility studies," she said. "The translation to that is 'If you use this, can you demonstrate that the patients are actually experiencing better outcomes?' From the manufacturer’s perspective, we demonstrated that the product is doing what it’s supposed to do. But payers are looking for a little bit more." But Evidation Health CEO Kilpatrick said that digital health interventions inherently produce a lot of data quickly and easily, which means that even if payers set a high bar for reimbursing them, they're well equipped to step up to that bar. "For payers who don’t want to pay, one of the easiest objections is 'Well that wasn’t in my population.' And while that is a harder objection to overcome with traditional therapeutics and diagnostics, with digital it’s 'Fine, I’ll go do it in your population.' And I can do that very rapidly because I can contact your members and I can [collect data] really fast. I don’t think expectations should or will be different [for digital therapeutics], because I think the speed and efficiency with which they can be met is going to be a game changer. And I think it’s going to be better for patients, for innovation, and for companies ultimately." The data from sensors and phones that facilitates quick, efficient clinical utility studies also constitutes one of the key use cases for digital health, according to Kilpatrick. In the same way that knowing a patient's genomic information facilitates personalized medicine, passively collecting behavioral data via the phone can help target interventions to the most receptive populations. "We’re throwing off digital signals all the time," she said. "If you use those signals to phenotype people, you can relate that to whether or not they’re likely to be adherent to medication, to whether or not they’re likely to show up to their primary care provider on their next visit, you can relate that in case of heart failure to readmissions, you can do all kinds of powerful things that allow us to quantify outcomes in ways that simply weren’t available to us before. So this notion of being able to identify super responders based on behavior, not just biology, that’s real and that’s here."

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