There’s a rising disconnect between the guarantees being made about synthetic intelligence in well being care and what’s being delivered. In the event you’re a well being system chief, it’s time to take a discerning view—not as a result of AI lacks potential, however as a result of most of the options getting into the market are extra advertising and marketing than medication.
We’ve seen this dynamic earlier than.
Earlier this month, a fintech founder was charged with defrauding traders after selling an AI-powered procuring app as revolutionary. The pitch? One-click checkout from any web site, powered by proprietary AI. The truth? A workforce of people in a name heart within the Philippines manually processed transactions. The automation price? Almost zero.
It’s a cautionary story for well being care. Too many AI distributors are showcasing glossy designs with out the underlying functionality. They declare to be autonomous methods, when actually, they depend on primary automation—or possibly even guide labor—behind the scenes.
In the meantime, Rock Well being experiences that over the previous 5 years greater than $27 billion has been poured into AI-enabled digital well being startups. As AI rises to the highest of investor priorities, the well being care market is being flooded with options—lots of which provide little greater than automation overlays or clinician-facing dashboards. The result’s a crowded and complicated panorama the place it’s more and more troublesome to tell apart confirmed, scalable instruments from speculative or superficial choices.
As a doctor, I’ve seen firsthand that profitable know-how in well being care should do greater than analyze information or floor insights—it should orchestrate motion between the care workforce and the care receiver. That’s why we spent greater than a decade constructing foundational infrastructure to help the actual work of major care supply earlier than layering in synthetic intelligence.
Our platform now helps look after greater than 8 million sufferers, together with 1.5 million in value-based preparations, with over $10 billion in medical bills below administration. These usually are not pilot applications or prototypes. They’re scaled, operational methods delivering measurable outcomes.
Amongst our most superior companions, we’ve helped obtain complete cost-of-care reductions of 20 to 25 p.c. And maybe most significantly, 98 p.c of sufferers in these partnerships see their major care doctor every year. That degree of engagement isn’t pushed by a chatbot or interface—it’s the results of coordinated methods working behind the scenes to shut gaps and lengthen care.
Tom, our Major Care as a Service (PCaaS) answer, integrates information from 63 digital well being file pipelines and 75 payer feeds. With tens of billions of medical and client information factors normalized and in play, Tom permits clever automation primarily based on the aggregated medical file and predicted well being trajectory of particular person sufferers to help them and their care groups whereas executing well timed interventions.
We’ve centered on fixing the exhausting, structural issues—information high quality, system connectivity and workflow integration—as a result of with out these components, AI turns into simply one other layer of complexity. It could look spectacular, but it surely doesn’t meaningfully change how care is delivered or skilled.
Well being system leaders ought to ask pointed questions: How is the know-how enhancing affected person entry, care coordination or price administration? Can the seller present verified efficiency information and real-world use circumstances? What well being care expertise is informing their growth? How does the implementation not simply change current workflows however take into consideration a brand new approach of care supply? Options that can’t display significant, measurable impression ought to immediate nearer scrutiny.
Synthetic intelligence holds great potential to reshape well being care—however solely when it’s grounded in actual infrastructure, knowledgeable by medical experience and designed to function inside the complexity of care supply.
We didn’t begin with AI. We began with well being care. Then we constructed the methods to help it. Solely after that did we introduce clever instruments to increase the attain of the care workforce and assist shut the first care hole that stands at 2 billion hours yearly within the U.S. alone.
The actual work isn’t within the interface. It’s in every little thing behind it.
David Carmouche is a doctor govt.
