The Innovation Fallacy in Healthcare
Illustration by Belle Mellor
Diffusion Matters More Than Invention
Technical invention is simple. Technical diffusion, not so much.
'Market access innovation' in healthcare is a three-body problem whose solution starts with a different objective: positioning a storyline of value -- a unique narrative -- that aligns the business, growth and innovation agendas of a provider market + a commercial payer market at the same time, as one system of thought.
A drug whose development and marketing budget is based on selling "reducing hospital admissions" is vision and messaging that runs counter to the economics of the $1.5 trillion hospital market, where revenue rotates in an orbit of creating demand and consumption for services delivered in the hospital.
Similarly, a blood test that was “amazing” in its ability to predict Alzheimer's 20+ years ahead of symptoms, per commentary around data presented last week at the American Academy of Neurology annual meeting (the study analyzed biomarkers on 54 participants in an ongoing preventive neurology study called the Biorepository Study for Neurodegenerative Diseases, or BioRAND), is notable for the “breakthrough” its technical potential won’t break through: the Innovation Diffusion Challenge, the same one that the rare disease drug market is flailing with:
No one is paid big enough and long enough to "care" about the ICER of a product whose earn-out doesn't happen for decades. The American Way of Healthcare is an embedded economic system whose feedback loops power short-term wins, which in turn power short-term vision.
Yup, it's "the largest and most lucrative market on Earth" (quoting Andreessen Horowitz), but that market is defined and managed by commercial payers competing in a six-month cycle of member churn. It's also a place where self-funded employers + government budgets can't afford the miracles of medicine. It's a place where the word “science” now sparks savage political conflict and structural stalemate, its ‘positional value’ having collapsed conceptually, its meaning dissolved into the same vapor trail as “patient engagement”.
Healthcare is also a hard knock world for the “profit” minded.
Brand and business managers up and down and throughout the complex system of markets dealing with intense career + financial + personal pressure, generally in the form of quarterly performance reviews by shareholders. But probably its main feature, from a product’s Go-to-Market perspective, is hyper-fragmentation and hyper-commoditization, on an industrial scale.
Richard Isaacson, the lead on the study presented at the AAN, in an interview with CNN:
“There is a dirty little secret in the Alzheimer’s blood testing community where so many testing platforms, biotech companies, and a flurry of new blood tests are released,” Isaacson said, “but it’s unclear which of these tests are most accurate to track progression and evaluate response to therapies to slow progression toward dementia.”
To address this gap, Isaacson’s research team and collaborators at five sites across the United States and Canada set forth to evaluate and eventually cross-compare the clinical use of what the neurologist said he believes will one day become “the cholesterol test for the brain.”
“In the not so far future, people in their 30s, 40s, 50s, 60s and beyond will get a baseline test to evaluate risk and help track progress over time — similar to how traditional cholesterol tests are used today,” said Isaacson, founder of one of the first Alzheimer’s prevention clinics in the United States.
“Our eventual goal is to offer a blood panel at cost to help democratize access and broaden the ability for people to receive care,” he added.
That there's new technical potential to predict disease decades in advance isn't unusual or surprising; if anything, the scientific achievement has almost zero news value. Ditto for curing disease. See all the big forecasts from the market for cell and gene therapies; then take a look at all the commercial withering in the market for cell and gene therapies.
A Big System Problem
Isaacson touches on the economics, the power of the ‘core administrative platforms’ to control the axis of rotation of $5 trillion, the orbital spin, as it were.
“Despite growing scientific evidence behind the benefits of early intervention” to minimize Alzheimer’s risk factors, he says there are currently no billing codes for health insurers to reimburse for dementia prevention:
"Right now, doctors can't even get paid for this type of care. There's no codes. We live in a sick care system. Not a healthcare system. Doctors get money from insurance companies and Medicare when they treat a problem, when someone has memory loss or someone has diabetes or someone has, I don't know, something bad. Not when someone wants to reduce their risk or try to protect themselves from getting a disease. There's no diagnostic code for that. Our medical system is broken, unfortunately."
It’s a familiar refrain framed in familiar terms.
The System is stuck in a loop in time. Its energy for evolution drained from trying to “fix” the horseless carriage with language riding the dead horse of the past. [A sidebar: there is always an infinite supply of “growing scientific evidence” supporting the potential value of an intervention because there is an Endless Ladder of “testing platforms, biotech companies, and a flurry of new blood tests” producing said scientific evidence on a daily, if not hourly, basis.]
A big system problem requires a big system solution.
This means going full bore to develop a different form of economic competition, to approach "market access innovation" through the lens of management innovation, one that solves the Endless Ladder of healthcare innovation: being better than a rival at organizing and ingesting an infinite flow of "value fragments” from the infinite production of infinite technical potential enabled by infinite technologies and data 'use cases' (for more Blue Spoon thinking on this, see LillyDirect vs. NovoCare vs. PfizerForAll: May the Best Ecosystem Win).
Given to Fly
In their obsession to define and then win the future, both Chinese and American leaders risk overlooking a key truth about technology and transformation, says Jeffrey Ding, Assistant Professor of Political Science at George Washington University and the author of Technology and the Rise of Great Powers: How Diffusion Shapes Economic Competition.
People are worried and working on the wrong things.
The focus is on dominating critical technological innovations in new, fast-growing industries, believing that economic power (i.e., control) favors those that pioneer the most important innovations. But technical innovation only gets you so far. He explains:
“Without the humbler undertaking of technical diffusion — how innovations spread and are adopted — even the most extraordinary advances will not matter. A focus on the diffusion of technology points toward an alternative explanation for how technological revolutions change geopolitics: it matters less which country first introduces a major innovation and more which countries adopt and spread those innovations.”
The Information had an exclusive piece of reporting yesterday (“OpenAI’s Latest Breakthrough: AI That Comes Up With New Ideas”) around how new AI aims to resemble inventors like Nikola Tesla, who blended information from multiple fields (think ‘interspecies communication’ — for Blue Spoon perspective on this, see Should Sanofi and Pepsi Collaborate as a New ‘Market Set’?).
OpenAI is preparing to launch new AI models as soon as this week that can connect the dots between concepts from different fields to suggest new types of experiments involving anything from nuclear fusion to pathogen detection, according to three people who have tested the models but are not authorized to speak about it.
If the upcoming models, dubbed o3 and o4-mini, perform the way their early testers say they do, the technology might soon come up with novel ideas for AI customers on how to tackle problems such as designing or discovering new types of materials or drugs. That could attract Fortune 500 customers, such as oil and gas companies and commercial drug developers, in addition to research lab scientists.
OpenAI says there is a big gap remains between ideas AI can generate and the scientists’ ability to verify them. OpenAI believes it can charge $20,000 per month for doctorate-level AI.
Which brings things back to the core premise of this strategy story: the hard nut to crack is the ‘production of health’ as a new economic concept, on par with GDP.
The biggest gap [in healthcare, especially] is not in generating scientific evidence to verify technical potential, and even producing a pitch deck to sell said technical potential. It’s developing, and then managing, the Big System Change necessary to ingest and integrate our ability to produce promising technologies, which in turn produces better progress.
In related news, Optum Rx announced last month that it will eliminate 10% of prior authorizations, something nearly all of the physicians surveyed by the American Medical Association said resulted in care delays and had a negative impact on outcomes. Physicians also reported concerns that denial rates could grow further as insurers adopt artificial intelligence tools to review claims.
Technical invention is simple. Technical diffusion, not so much.
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John G. Singer is Executive Director of Blue Spoon, the global leader in positioning strategy at a system level. Blue Spoon specializes in constructing new industry ecosystems.