Advocating for evolution, not disruption, in healthcare

https://medcitynews.com/2019/04/advocating-for-evolution-not-disruption-in-healthcare/?utm_campaign=MCN%20Daily%20Top%20Stories&utm_source=hs_email&utm_medium=email&utm_content=71446469&_hsenc=p2ANqtz–34bi05gJtda54hwonqyCB9rxFgJoCujD6XqJVlAXN-4zFSD8Z-UjONzK_dzDDHx1pG_jCZPZSiwrDtx_-6cOwrzj3_Q&_hsmi=71446469

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Healthcare doesn’t shatter and reanimate as the terms “disruption” and “disruptive innovation” suggest. It evolves. Even groundbreaking technologies in history show the transformation happening over time and with continuous building upon prior advances.

Late last year, the Christensen Institute’s Rebecca Fogg wrote about disruption accelerating in healthcare, priming of the pump for new capitated health plans and new delivery models. It is certain that leading consultancies have expressed a surging desire to disrupt in their business intelligence work and their analysis holds some insight for business leaders. But the truth about what our healthcare system will look like over the next 20 years is far from determined — and “disruption” will certainly not be the optimal path.

Disruption is, well, disruptive. It leaves in its wake complicating debris that trend towards more disorder. Consider that disruption’s synonyms include breakdown, collapse, disarrangement, disturbance, havoc, upset,… Is this what we actually want or need? Healthcare doesn’t shatter and reanimate, it evolves. Over 200 years ago, for example, the invention of the stethoscope ushered in a series of generational discoveries that transformed public health, general health, and overall life expectancy through the enhancement of insight into pathophysiology underlying human symptoms.  The new technology was groundbreaking, but the transformation happened over time and with continuous building upon prior advances. This evolutionary system works remarkably well. To disrupt it, to disarrange it, does not make sense.

At the center of Fogg’s argument is interest in different models that seem to be on the increase. The data does not fully support this view or serve as evidence of a pending wave of disruption. What we see instead are repeated ripples.

Take the “wave” of HMOs initiated in the 1970s. The ramp was supposed to be significant — combining financing and care delivery would be genuinely transformative. And yet the model’s penetration over 20 years only reached about 15 percent nationwide, and even now (data as of 2016) has only increased to 31.6 percent.

Further, in 2014 and again in 2018, Rand Corporation explored health payment constructs. Its most recent report on this work is a great representation of both our progress and stagnation: Findings suggest that in the window between initial engagement around alternative payment models (such as value-based care in 2014) and follow up (in 2018) little in the way of significant change has occurred. While we have seen plenty of perceived “disruptive models” emerge, we’ve also witnessed models championed as “disruptive” fall away.

The rise, plateau, and sometimes decline of various broad modernization initiatives is common and should be expected. The whole effort is hard.  We do not have any magical ability to foretell the future.  And we do a poor job of grasping the evolutionary nature of healthcare and the timelines of its change. Sure, we see pockets of capitated plan models that work, locations where the ACO makes sense, incidences where bundles show promise. But we are not primed for disruption that will change everything, or even most things, tomorrow. Rather, we are primed for a series of experiments, discoveries, and adaptive evolution. This is OK.

Three points stand out significantly in charting the realistic course of healthcare change moving forward:.

  1. The road is long.
    Understanding that healthcare evolution is a journey and not a rapid-shift prospect is important. There are a variety of considerations, one of which is contemplating the measures of success in the future state. Part of the failure of using payment models as a measurement for transformation is rooted to how blunt a tool payment structures are in producing desired outcomes. Consider recent disruption in payment models on the music industry. Whether you pay per song or via subscription has little bearing on the quality or appeal of the music itself. And with music, we can at least gauge direct feedback from users of the delivery systems to determine perceived value, effectiveness, and overall adoption. The feedback loops for what is working in healthcare are more complicated and difficult to master, and a great challenge to the value-based care revolution has been a lack of good measures. This is due, in part, to the framing of systematic structural levers as the core issue. That we cannot measure what holds value has little to do with whether a service is paid for through a capitated structure or through FFS. That’s not to say that payment structures do not alter incentives and change care behaviors, but whether one option is better than another is not the right question. This shouldn’t be discouraging. Evolution requires contemplation and development and new measures addressing different disease needs, delivery models, and technological capabilities. But all this takes time. It’s no use oversimplifying the nature of the beast.
  2. The substrate matters.
    It is essential to consider what is working and where. Solution sets for physicians and individuals, as well as the healthcare system as a whole, must be a mix of scaled capabilities and regional deployments. The recent study by Jha, et. al. in JAMA showed how breaking down traditional arguments about our health system is important to ensure we are understanding its problems and potential precisely. Among other things, the study shed light on the point that we have 50 different systems within our system from which to learn. The sheer variety state to state — not only in demographic and disease needs, but also in how treatment and services are paid for — enables enormous opportunity for innovation and testing. A relatively untapped resource lies in exploring what is working and why within these individual substrates. Breaking down the national system to a function of its parts would be a productive exercise for creating an adaptive mechanism for a “learning” healthcare system that evolves and advances more productively.
  3. The status quo is a threat to be managed.
    If healthcare innovators want to be “disruptive,” they need to take on the entirety of a complex, multi-faceted, multi-trillion-dollar industry. Clay Christenson writes of the velocity of history in his Innovators Dilemma. Being caught unawares is a great risk, akin to missing the new train when it leaves the station and you stuck on your old platform. That’s a powerful motivator. But in healthcare, the profits (and there are significant profits) create a ruthless resistance to any alteration of the status quo. So new trains don’t get to run on the current system’s tracks, rendering them irrelevant. Or they seem impactful, but run on the same schedule and under the same power, making them more or less lipstick on the proverbial pig. The introduction of change to the system must aim to be holistic, and include the critical voices of all stakeholders — predominant businesses, physicians, patients, investors, government and upstarts alike.

Amid the flurry of articles and analysis expounding the grandiosity of ever-imminent healthcare disruption (just around the corner), a nod to Darwin and the observable nature of our actual healthcare system and a scientifically based understanding of evolution seems appropriate.