Tag: digital health

The Case for Primary Care as a Public Utility

Posted on by Jason Barry

What happens if primary care gets treated like a public utility – something that everyone can access as easily as running water?

A new article in JAMA paints a beautiful picture of what that might look like, and even colors it in with a roadmap for how to get there.

Primary care is a critical component of healthcare. It’s also far from universal.

  • More than a third of U.S. adults lack access to primary care, an eye-popping number that unfortunately makes more sense knowing primary care only sees 5 cents of every federal dollar spent on healthcare.

The authors frame up the issue perfectly. 

  • “Primary care has long fit awkwardly as an insurable risk in the marketplace. Insurance is designed to protect against large, unpredictable expenses. Yet primary care is largely predictable, similar to food, housing, and other common necessities.”

The proposed solution? A primary care common fund, which pools primary care spending from public and private purchasers and pays practices directly. Here’s the basic outline:

  • The common fund would comprise current primary care spending from payors, and include the additional spending that states invest into primary care in the future.
  • A state authority – much like a public utility – would administer the funds and pay practices directly.
  • The “pluralistic financing” of primary care would remain intact. Employers and individuals would continue to pay premiums for commercial plans, and Medicaid would continue to be financed by federal and state funds. On the back end, the state would redirect the primary care portion of payor premiums (their contribution) to the common fund.
  • A key point is that the common fund starts with no “new money.” Baseline contributions equal what purchasers are already spending on primary care (ex. Oregon has a primary care spending target of 12%, and would assess 12% of plan premiums). 
  • Payors would no longer need to compete on prices and benefits for primary care, but they’d still compete on their specialty and other lines of business.
  • People remain enrolled in coverage for non-primary care services, but the common fund “assumes responsibility for coverage and payment of primary care and accountability for its spending.”

The Takeaway

If the U.S. wants everyone to have access to the benefits of primary care, a good start might be making sure everyone has access to primary care. This paper charts a path to get there straight down the middle of single-payor and free-market approaches, and a “Medicare Advantage for Primary Care” feels more doable than ripping and replacing the entire system.

Nourish Cooks Up $100M of Series C Funding

Posted on by Jason Barry

Nearly 200M Americans are hungry for help managing a nutrition-related chronic condition, so Nourish just raised $100M of Series C funding to fill their plates with AI-native metabolic care.

Nourish is a proactive substitute for a reactive recipe. Its entire virtual metabolic clinic is purpose-built to tackle chronic conditions before problems start to escalate.

  • The care model revolves around nutrition-first interventions, but it’s the fully coordinated wraparound support that transforms access into better long-term outcomes.
  • The secret ingredient? Dietitians… plus AI, obviously.

Over the last four years, Nourish has grown into the country’s largest dietitian-led metabolic health clinic, with a roster of over 10,000 Registered Dietitians.

  • Every Nourish patient works with an RD to work through a comprehensive care plan – with lab testing, GLP-1 prescribing, and medication management all baked in if needed.
  • Patients also receive a personal AI agent to support behavior change and coordinate with other providers. These reportedly have “hundreds of thousands of MAUs and world-class engagement metrics.”
  • The RDs are equipped with their own AI agents to help surface insights, automate administrative work, and improve quality of care.

The outcomes are the main course. Nourish patients see an average of: 

  • 8% weight loss
  • 1.3-point A1C reduction
  • 31-point LDL reduction
  • 23-point systolic BP reduction

GLP-1s are the dessert people can’t get enough of. Despite demand for metabolic care exploding alongside the rise of GLP-1s, medication alone is rarely enough – only 46% of patients stay on GLP-1s at six months, and most who quit regain the weight.

  • Nourish’s care model shines here too. Over two-thirds of Nourish patients remain on GLP-1s at six months, and they lose 33% more weight on their way there.

The Takeaway

Nutrition support has been covered by insurance for over a decade, yet only a tiny fraction of those who could benefit ever actually use it. GLP-1s changed that demand equation, and Nourish just loaded its plate with $100M to give people the access they’re suddenly craving.

Medicare’s None the WISeR

Posted on by Jason Barry

Washington state just delivered an unfortunate crash course on U.S. health policy after the model aimed at “Wasteful and Inappropriate Service Reduction” led straight to higher costs and fewer treatments for seniors.

Does Medicare need prior authorizations? CMS designed WISeR to find an answer by testing whether bringing AI-driven prior auths (which are already widespread among private payors in Medicare Advantage) to traditional Medicare could cut down on wasteful spending.

  • The six-year pilot kicked off in six states on January 1st (AZ, NJ, OK, OH, TX, WA), targeting a list of 13 “low value” services with a high potential for fraud or waste – most notably orthopedic pain management procedures and skin substitutes.

Washington is already tapping out. Less than five months in, Senator Maria Cantwell (D-Wash.) had enough data to publish her new report on the “clear risks of AI in Medicare.”

  • Drawing on a Washington State Hospital Association survey of 16 hospitals, the report found that procedures previously approved within days are now taking 4 to 8 weeks. 
  • CMS’ own WISeR standards call for responses to providers within 1 day for urgent care and 3 days for routine care, both of which are now clocking in at 15 to 20 days.

You get what you pay for. WISeR compensates third-party administrators for each claim they deny, under the assumption that these denials account for the reduction in wasteful spending.

  • That obviously creates some adverse incentives, which the report eloquently framed up by saying the model “incentivizes WISeR contractors to weaponize AI-driven medical determinations not for the sake of efficiency… but to maximize profitability.”
  • As a result, Washington hospitals have had to add staff and increase hours to manage the surge in prior auths – not a great formula for lowering the cost of care.

The report went straight to the top. At a Senate hearing last week, Senator Cantwell made her case directly to HHS Secretary RFK Jr., who said “that kind of delay is unacceptable.”

  • He went on to say that prior auths are there to prevent the government from being “ripped off” by unethical providers and only applies to 5% of services in Medicare.
  • That might be accurate, but it doesn’t mean they aren’t high-volume services. A separate KFF analysis found that 86% of the 1.1M Medicare beneficiaries that used at least one of the services on WISeR’s list in 2024 received a pain management service.

The Takeaway

Reducing waste in Medicare is a worthy goal, but so far it looks like the best way to make it happen probably isn’t by adding prior auths to the program that many seniors specifically chose to avoid them.

The Rise of the Generalist-Specialist

Posted on by Jason Barry

Healthcare’s tidy hierarchy of specialties was formed by cognitive necessity. The corpus of medical knowledge is too massive for a single person to master and the clinical workforce was organized around it, but a new article in Health Affairs says it might be time for a redesign if AI removes that constraint.

AI is scaling specialist-level knowledge. Leading models are coasting through Board exams and polishing their clinical capabilities, which the authors argue will quickly scale specialist-level knowledge to the point where most specialty care can be delivered by PCPs.

  • They coined the term “generalist-specialists” for a new category of doctors that transcends narrow specialty definitions.

Clinical expertise is increasingly democratized. The authors see a future where AI-augmented clinicians can manage the full constellation of patients’ chronic conditions within disease-based domains rather than organ-specific specialties. They give a few examples:

  • Cardiometabolic Diseases – combines cardiology, endocrinology, and nephrology
  • Infectious & Inflammatory – rheumatology, infectious disease, & gastroenterology
  • Primary Care: spans OB/GYN, internal medicine, and pediatrics.

That could have some major benefits. Instead of shuffling a diabetic patient between an endocrinologist, cardiologist, and nephrologist, a generalist-specialist could manage the full cardiometabolic picture.

  • That means fewer handoffs, faster diagnoses, and lower co-pays. It would also unlock a ton of specialty capacity for the patients that need it most.
  • Consolidating care under fewer clinicians would also be a tailwind for value-based care, although it would likely increase utilization in a fee-for-service world by converting deferred, fragmented, or incomplete care into a cohesive billable treatment.

AI isn’t the only barrier to making that happen. Everything from med schools and malpractice standards to credentialing and referral systems would need to be completely overhauled.

  • The generalist-specialist vision also assumes that specialists will be on board with either becoming quasi-PCPs or upskilling to ultra-complex care. Definitely not a given.
  • Patient safety concerns also go without saying, but the AI will probably be pretty decent by the time we have cardio-endocrin-nephrologists putting together the care plans.

The Takeaway

AI could easily bring specialist knowledge to generalist fingertips, but if overworked PCPs are going to start also being OB/GYNs it will take more than a fancy LLM to get there.

Why AI Vendors Struggle to Compete With EHRs

Posted on by Jason Barry

Anyone who has ever tried selling AI into health systems will tell you that it’s tough to compete with EHRs, but a new article in JAMA makes the case that it’s actually gotten too tough – and it might be time for regulators to step in.

Most markets reward the best products. The healthcare industry has a funny way of preventing that from happening, and EHR vendor dominance is a textbook example.

  • EHRs hold advantages across infrastructure, workflow integration, procurement, and pricing that make it difficult for third-party tools to gain a foothold.
  • A 2025 Health Affairs study backed that up by showing that 79% of U.S. hospitals use AI models from their EHR vendor, compared to just 59% that use AI from third-party developers.
  • A Bain report drove the point home. Two-thirds of Epic customers said they’d pick a “good enough” Epic option over a better competing product.

These EHR advantages are a natural feature of the market. That said, it’s up to regulators to decide whether the status quo is serving patients and the overall healthcare system. The JAMA authors argue that it doesn’t, and offer three areas where targeted policy could level the playing field.

Infrastructure – Integrating AI tools into clinical workflows requires real-time data access and the ability to survive EHR upgrades intact, both of which are dramatically easier for EHR vendors – particularly as data fields get added or removed.

  • Potential Policy – Mandate broader API adoption so third parties can access EHR data on equal footing, and use existing EHR certification and interoperability frameworks to do it.

Workflow and Usability – The authors specifically flag EHR vendors’ edge in understanding the trade-offs of allocating limited screen real estate to new AI tools, something that’s harder for third parties to gauge from the outside looking in.

  • Potential Policy – Require EHR vendors to offer more robust developer sandboxes – similar to Apple’s iOS developer environment – so third parties can build and test without operating at a structural disadvantage.

Procurement and Pricing – Long-standing health system relationships give EHR vendors a streamlined path through procurement, as well as the leverage to “use pricing structures that incentivize adoption.”

  • Potential Policy – Although this is the hardest area for a policy fix, the authors suggest that improving transparency around AI performance could at least help health systems make more informed decisions regardless of where a tool comes from.

The Takeaway

EHRs are in a powerful position, and companies in powerful positions have a long track record of making life harder for their competition. Healthcare is too important of an industry to not have the best products rise to the top, and this article offers some sound strategies to make sure that stays possible.

Inside the World’s First One-Man AI Unicorn

Posted on by Jason Barry

We officially have our first one-man, billion-dollar AI startup, and it’s in healthcare… for better or worse.

It was hard to be online last week without stumbling across the New York Times profile on “How A.I. Helped One Man (and His Brother) Build a $1.8 Billion Company.”

The article tells a shimmering tale of AI entrepreneurship. The 41-year old founder took just two months, $20k, and a dozen AI tools to get his startup Medvi off the ground.

  • Medvi plays at the intersection of two trends that seem almost engineered to mint new billionaires: agentic AI and GLP-1s.
  • The online telehealth provider offers GLP-1s for weight loss, with an army of AI agents handling everything from website copy and design to ad images and customer service.
  • It had 300 customers in its first month, generated $401M in its first full year (2025), and revenue is now on track to hit $1.8B after the founder doubled the headcount by hiring his brother.

Medvi is basically dropshipping healthcare. They’re in the business of acquiring customers, not delivering care. The entire clinical infrastructure runs through turnkey partners.

  • CareValidate manages the physician licensing and prescriptions.
  • OpenLoop handles the pharmacy fulfillment and shipping.

Here’s what NYT forgot to mention. The article notes that Medvi’s founder was “nervous to talk publicly” about the company and hasn’t exactly been waving his momentum around.

Some solid sleuthing from digital health’s finest offers a few hints as to why that might be:

  • Medvi (or partners with a conveniently long leash) spun up 800+ fake doctor Facebook accounts to aggressively advertise their meds. Not great.
  • They’re named in a lawsuit alleging a nationwide scheme to manufacture and promote a fraudulent, unapproved oral tirzepatide pill. Also not great, allegedly.
  • Their onboarding accepted a user with a February 31st birthday, then told them they had a 94% chance of hitting their goal weight of 200lbs starting from 7’11” and 350lbs. Yikes.

Sam Altman called it. The OpenAI CEO was spot on with his prediction that AI would quickly let solo founders generate billions by eliminating the inefficiency seen at larger orgs. Unfortunately in healthcare, much of that “inefficiency” is in place to protect patients.

The Takeaway

Is it impressive that one founder and a little grayhat marketing can now do billions in revenue? Yes. Should we be dropshipping healthcare through predatory ad funnels? Probably not. 

Amazon Health Connect Sends AI to the Back Office

Posted on by Jason Barry

If the competition for the back office was already hot, it’s a certified wildfire after last week’s debut of Amazon Health Connect. 

Amazon is pitching Amazon Connect Health as a purpose-built agentic AI solution for the administrative work that gets in the way of care. That’s definitely not fun to read for all the companies that had the same tagline on their booth at ViVE.

It comes with five capabilities straight out of the box: 

  • Patient verification
  • Appointment scheduling 
  • Pre-visit summaries
  • Ambient documentation
  • Medical coding 

What’s the core use case? AWS Director of Healthcare AI Naji Shafi says it’s the entire patient journey.

  • When a patient calls to book an appointment, Amazon Connect Health answers immediately, confirms their identity, checks their coverage, and lines up the visit while they’re still on the line.
  • Before the visit, it reviews their complete medical history across care settings, then surfaces previsit insights like active conditions or trends that might be relevant to closing care gaps.
  • During the visit, it drafts clinical notes for provider review in real-time, with every detail linked back to the moment in the conversation where it was discussed.
  • After the visit, it generates patient-friendly summaries and the medical codes needed for billing, allowing the visit to be payor-ready and submitted within minutes.

But wait, there’s more. Amazon Connect Health integrates natively with Epic, and connects to 100+ EHRs and 35+ HIEs through data integration partners like Redox.

  • It’s also built entirely on AWS HealthLake, the cloud giant’s FHIR data repository that’s now getting new agentic capabilities to help convert records into standard formats.

Early users love it. Amazon One Medical was the perfect sandbox for polishing Amazon Connect Health in clinical settings before opening it to outside partners. It shows in the results.

  • UC San Diego Health is saving a minute per call, diverting 630 hours a week from patient verification to direct support, and slashed call abandonment by 30%.
  • Netsmart’s EHR supports more than 1,300 community provider orgs, and it saw ambient documentation adoption skyrocket 275% – and better staff retention as a result.

The Takeaway

There were already tons of agentic AI solutions competing to automate healthcare’s administrative waste, and now there’s one that’s bankrolled by the biggest bookstore in human history. It’s a crowded space, but $1 trillion per year is also enough bloat to go around.

OpenAI Jumps Into Healthcare Arena With ChatGPT Health

Posted on by Jason Barry

If OpenAI wasn’t already a major healthcare player, the launch of ChatGPT Health definitely just made it one.

It’s the gamechanger everyone saw coming. OpenAI even teed up the launch with a report showing that 40M people are already using ChatGPT for healthcare advice on a daily basis. 

ChatGPT Health is about to take that a massive step further. 

Here’s a look at the core features:

  • ChatGPT Health operates inside a dedicated health environment with additional privacy layers (conversations aren’t used for model training, optional two-factor authentication).
  • Users can securely upload their complete medical records (courtesy of b.well).
  • Users can connect apps to inform answers (Apple Health, Function, MyFitnessPal).
  • The model uses longitudinal health data, labs, and visit summaries to help spot trends.

OpenAI is moving beyond general health advice. The extra clinical context gives ChatGPT Health the ability to give better answers at scale, and that’s good news for patients.

A few of the most obvious benefits for patients include:

  • Empowering them to take a more active role in their care.
  • Helping them uncover trends in their overall health.
  • Reducing confusion around test results.
  • Reinforcing care plans between visits.
  • The list could go on for a while.

ChatGPT Health isn’t actually HIPAA compliant. Then again, it doesn’t need to be.

  • Consumer health apps like ChatGPT Health aren’t covered by HIPAA, and to OpenAI’s credit it appears to have done a great job with the necessary disclaimers.
  • The dedicated health environment was also developed with input from 260+ physicians, and it leverages a physician-authored framework for safety, clarity, and escalation.

The question now is, who’s accountable when things go wrong? Millions of patients are about to start showing up to visits armed with advice from ChatGPT Health, which means its AI fingerprints will be all over their questions, concerns, and even clinical decisions. The tech might be ready. The governance isn’t.

  • When ChatGPT Health mentions an unproven treatment and a patient follows through, or interprets a worrying lab value as benign, who carries the liability?
  • OpenAI? The physicians who authored the safety framework? The patient who followed the advice? It’s tough to say, but providers – and their patients – still need a clear answer.

The Takeaway

Everyone wants a doctor in their pocket, and ChatGPT Health just filled that role for millions of patients… even if OpenAI explicitly told them it wasn’t up for the job.

Crystal Ball Compilation: Digital Health in 2026 

Posted on by Jason Barry

Welcome back to the first Digital Health Wire of 2026! The healthcare industry doesn’t take any days off, but we hope our readers managed to catch a break over the holidays to recharge for the big things to come in the new year.

The past few weeks have had plenty of fortune tellers predicting what those big things will be, so we’re kicking off the year with a compilation of the clearest crystal balls.

Let’s get right into it.

CommonSpirit Health – Five Health Tech Predictions for 2026, Dr. Minal Shah

  • Favorite Forecast: In 2026, AI projects without strategic alignment are heading straight to the pilot graveyard. When organizations chase what’s possible instead of what’s strategic, they burn human capital on change efforts that never scale to real impact.
  • Big Idea: “Platform vs. point solution is a false dichotomy – and I think we’re asking the wrong question. The real question isn’t which approach to take. It’s whether we’ve done the hard work of understanding what the organization actually needs before we choose a path forward. That means moving from ‘what can we do with AI?’ to ‘what should we be doing with AI?'”

Out-of-Pocket – Out-Of-Pocket’s 2026 Predictions, Nikhil Krishnan

  • Favorite Forecast: Intellectual property lines will be drawn for AI. We’ve already seen a ton of legal battles around copyrights, but the dealmaking is just getting started.
  • Big Idea: “Healthcare has a TON of companies that have copyrights and IP ownership over critical parts of healthcare information. OpenEvidence for example has signed several agreements with medical societies, NEJM, etc. Who will the AMA partner with for CPT codes? Which companies will the EHRs partner with to license their data?”

Second Opinion – Healthcare in 2026, Christina Farr & Annalisa Merelli

  • Favorite Forecast: The largest digital health companies will start flocking to CMS’ new ACCESS program to find a better business model in Medicare, while also duking it out for a slice of the available rural health funding. 
  • Big Idea: “There’s no question digital health companies will be the beneficiaries, particularly given that the executive and policymaker running Medicare – Chris Klomp – has an entrepreneurial background and formerly sat on the board of venture-backed Maven Clinic.”

Becker’s – How the AI conversation will change in 2026, Zachary Lipton

  • Favorite Forecast: Clinical decision support has been trapped in a frustrating middle zone for years: better than manually searching guidelines, but worse than talking to a specialist. CDS will finally start evolving beyond search with contextual awareness.
  • Big Idea: “This is the year CDS evolves past glamorized search. Next-generation CDS will reason jointly over medical literature, the patient’s record and current visit context, helping clinicians apply knowledge, not just retrieve it.”

Forbes – 10 Healthcare Industry Predictions For 2026, Sachin Jain

  • Favorite Forecast: Healthcare’s AI revolution will hit speed bumps. While AI has shown considerable promise for relatively straightforward uses like ambient dictation, its application in other domains will be more challenged and problematic.
  • Big Idea: “Agentic AI holds significant promise, but legacy operators will be slow to change deeply ingrained processes, values, and attitudes. AI snake-oil salespeople (fueled by venture capitalists chasing outsized returns) have flooded the zone, a phenomenon that is sure to fuel false starts and threaten the pace and depth of true organizational change in the short-run.”

Hospitalogy – 8 Predictions for Healthcare 2026, Blake Madden

  • Favorite Forecast: In 2026, enterprise buyers will start demanding consolidation. The operational model shifts from “best of breed for each use case” to “who can orchestrate AI across our entire administrative and clinical workflow?”
  • Big Idea: “This is where the Palantir playbook becomes relevant. The firm is already working with HCA and others to deploy AI infrastructure that spans clinical, operational, and financial domains. The value proposition isn’t any single algorithm. It’s the orchestration layer that ties disparate data sources into unified decision support.”

Notable – Healthcare’s pivotal year for AI transformation, Dr. Aaron Neinstein

  • Favorite Forecast: New practices will be built from scratch around AI Agents to support panel sizes three to five times larger at equal or higher quality and dramatically lower cost. At the same time, human connection will take center stage again.
  • Big Idea: “AI will handle pattern analysis and routine adjustments, so clinicians can shift from memorizing facts to focusing on meaning… Because of this, nurses, MAs, and care coordinators will move up the value chain, as they can spend more time on empathy, clinical judgement, and complex situations rather than administrative tasks.”

The Takeaway

Healthcare still has its fair share of challenges, but it has just as many tailwinds pushing it toward new solutions. Cheers to everyone making those solutions a reality in the new year.

Rock Health: Innovation at the Turn of 2026

Posted on by Jason Barry

Rock Health is wrapping up the year in style by updating its Innovation Maturity Curve with the hottest trends of 2025 and sharing its predictions for what lies ahead.

The curve uses three major data points to plot innovation:

  • Research volume – gauges the potential of a topic through PubMed publications.
  • Venture funding – tracks investment as a leading indicator of commercial interest.
  • Partnership activity – uses industry partnerships as a proxy for commercial traction.

The pace is picking up. Here’s a look at the categories that defined the year:

Longevity (Maturity Score: Developing) – Companies are pushing past one-off diagnostics to see whether personalized baselines can anchor ongoing care. Function Health just hauled in a massive $298M Series B for its “operating system for human health,” and other players like Hone Health have started expanding their models with in-home services.

  • Keep an eye on: How much will insights on hormones or heart health translate into adjustments that patients actually act on? Rock Health expects this segment to hinge on turning long-arc patterns into timely guidance that’s both credible and valuable.

Mental Health Chatbots (Maturity Score: Emerging) – Some AI chatbots might be shutting down, but just as many are doubling down. Slingshot burst onto the scene with $93M to build “the world’s first foundation model for psychology,” and incumbents like Spring Health have even started launching bots to evaluate the safety of other bots.

  • Keep an eye on: Regulatory scrutiny is intensifying as states begin banning AI-driven therapy. Some startups might be able to navigate the roadblocks, but Rock Health thinks others might pivot to lower-risk territory like keeping patients engaged between visits.

Health Benefits 2.0 (Maturity Score: Emerging) – OOP spending continues to climb, while employers just notched the steepest benefit cost increase in 15 years. Those pressures cracked a window for non-traditional models to gain traction, such as ICHRA frontrunners Thatch and Venteur.

  • Keep an eye on: The benefits pressure cooker is heating up in 2026, which means this category isn’t going anywhere. As more costs shift to consumers, Rock Health anticipates the benefits experience to start looking even more like a set of adjacent marketplaces rather than a single plan.

The Takeaway 

Digital health is moving faster than ever, and AI is only going to keep accelerating innovation. Rock Health’s full report is well worth checking out for more details on these categories and other up-and-coming segments like wearables (smart rings are especially hot), precision medicine (digital twins had a big year), and climate health (think allergies and air pollution).

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