Wednesday, April 13, 2016
Quick thought experiment for you: In past 10 years, about how many times have you had a “whoa” moment when you learned about an innovation in medicine?
When did the light bulb go on about the implications of genomics? Were you alarmed as you realized the scope Eric Topol’s vision for a patient – led hostile take-over of diagnosis and treatment? Maybe you had to stifle a sniffle at your desk when you saw how a Brazilian medical team used 3D printing to give a blind expectant mother the experience of a sonogram? Or perhaps you “binged whoa-ed” your way through a couple of hours TEDMED, Cleveland Clinic’s annual Top 10 Medical Innovations, or the ambitious projects at Verily (the Alphabet subsidiary formed when Google[x] Life Sciences “graduated“)? Or was it more arm’s length — observations of the growing consensus on the newsstands that we will soon live well into our hundreds, happily sipping genomic-ally perfect healthcare from devices, apps, driverless cars, robotic health assistants, and implanted chips?
And if you will permit me a follow up question: In the past 10 years, how many times have you had a “whoa” moment when you learned about an innovative approach to how we will pay for this medical innovation?
When I ask myself the two questions above, the answers are “I couldn’t possibly count” and “zero”. For that and many other reasons, I have the sense that there a real problem emerging here.
For so many futuristic visions of healthcare delivery, I am easily persuaded that there is a path for the technology to become a reality. Actually, in many cases very little R and D is needed –we just need to bring what technology has accomplished in pilots and laboratories to mainstream scale. But what remains entirely unclear to me (and I don’t mean to be a drag) is exactly what economic forces are going to create the collaboration, interoperability, regulatory environment, and consumer empowerment that these visions require.
It’s not just about how much it costs — basically everyone knows there’s a big problem with healthcare costs, so all medical innovations include some clause about how they will ultimately save money (and for our purposes here, I will leave those claims alone, though I’ll confess it is a tempting target). But what about the mechanisms of payment? If it is becoming ever more clear that healthcare outcomes are determined outside of healthcare delivery, can we continue to draw a sharp line between medical and non-medical interventions that lead to health? How can our tired system of writing medical policy (determining what treatments health insurers cover and don’t cover) possibly keep up with the innovations happening in healthcare delivery? And even if the process could, what human being can sort through the evidence that pours out of research in journals, society standards of care, and all manner of new sources of “real world evidence”? Can we really do no better than “auto auth” to make the broken system of prior authorization which infuriates physicians, and generally puts well meaning people at odds with their humanity, their ethics, and occasionally patient safety? And as much as I support the shift of “pay for volume” to “pay for value”, do we really think that marginal shared risk by itself can bridge the gap we are facing here? And I could go on – provider network management, insurance product development, care management, analytics… good work being done by smart, dedicated people in all of these areas, but ultimately I question whether we can meet the huge opportunities and challenges of medical innovation without fundamentally rethinking the way we pay for healthcare.
So, in my view, we need some futuristic visions for paying for healthcare. I’m no futurist, but I have some ideas and I plan to blog about them here. Happily, Gartner has given me some space to do so by accepting my proposal for “A Grassroots, Digital Solution to Financing Global Population Health” into the Maverick Research Program – our incubator for technology-related research outside the normal scope of our research.
In this research I will explore the following three hypotheses:
- All current systems of financing healthcare on not equipped to match the pace of innovation in healthcare delivery, much less the broader demands of population health.
- Emerging capabilities in analytic modeling (what we at Gartner call Smart Machines, but you might know as “machine learning”, “cognitive computing” or “artificial intelligence”) will, in the not-so-distant future, be better suited to making decisions about allocating scarce healthcare resources than all of the humans and institutions currently performing that role. (or to be slightly more to the point: Smart Machines should ration healthcare)
- A solution architecture is possible (working title: The Universal Health Intervention Hub [better ideas welcome]) using the emerging technologies of digital business, distributed ledger (“grassroots”), Internet of Things (IoT), and a common set of protocols between stakeholders.
As a part of this research, I will take contemporary examples out of the news from around the world, to demonstrate how #2 and #3 would work as an alternative to #1 (Hep C drugs, the lead problem in Flint Michigan, and “housing first” approach to managing indigent populations are on the list of problems to analyze). I will post periodic updates on this blog, publish a note available to Gartner clients in the early Fall, and present my findings (positive or not) at Gartner’s IT Symposium in Orlando in October.
I would appreciate your help. Comment here if you have ideas, evidence, or anecdote to add to this conversation. Consider people or organizations from your that might be interested or have ideas to add. And most of all, keep reading – I’ll be back soon.
I look forward to the research ahead.