Tag: digital health

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).

2025 Trends Shaping the Health Economy

Posted on by Jason Barry

Trilliant Health just released its 2025 Trends Shaping the Health Economy Report, delivering a uniquely holistic perspective on the healthcare market through the lens of supply and demand.

Here’s the state of play. Health expenditures are growing faster than the rest of the economy, and they’re projected to represent 20.3% of GDP by 2033. 

  • The U.S. spends more and gets less than peer nations, which might have been tolerable when our federal debt was at $800B in 1980, but definitely isn’t now that it’s at $37T.

What levers can we pull? This year’s 115 page analysis looks into six macro trends driving the healthcare economy, and underlines each of them with concrete stories from real-world data.

  • 1) Affordability concerns are reshaping demand. Medical prices are up 54.5% since 2009, and they’re pressuring patients and employers to weigh their options – especially when rates for an inpatient procedure can vary as much as 7x within the same facility depending on the payor (p. 19).
  • 2) Stakeholders are slow to adapt to demographic trends. Mortality rates among adults aged 18-44 have been rising as the fertility rate falls, shrinking the share of Americans with employer-sponsored coverage (p. 22).
  • 3) Specialty care intervention is incentivized over primary care prevention. In 2024, behavioral health visits rose 11.4%, while primary care visits declined 5.6%, marking the first time behavioral health utilization surpassed primary care (p. 43).
  • 4) Fraud, waste, and abuse are pervasive. The share of high-complexity ED visits has risen sharply, increasing from 36.6% to 47.8% of visits between 2018 and 2024, underscoring the financial impact of upcoding (p. 57).
  • 5) Alternative therapies are accelerating. GLP-1 utilization increased 745% from 2018 to 2023, while bariatric surgery volumes were flat to declining, illustrating how high-margin procedures face growing competition from medications (p. 86).
  • 6) If the industry won’t deliver value, the government will. Federal programs have consistently failed to bend the cost curve (MSSP savings are less than 1% of Medicare spending), and there’s mounting political pressure for top-down structural reform (p. 89).

The Takeaway

The U.S. healthcare system is at a crossroads. As Trilliant put it so nicely, the choice for all health economy stakeholders is whether to implement “radical change from the inside” or “to be subjected to such change by external forces.”

Bain & Company: Top Healthcare IT Priorities

Posted on by Jason Barry

Payors and providers are fighting different operational battles, but they’re using the same two-letter weapon to come out on top: AI, you guessed it. 

A joint report from Bain & Company and KLAS found that 80% of payors and 70% of providers now have an AI strategy in place, up from just 60% last year.

  • Providers are up against structural workforce shortages and rising patient volumes, while payors are contending with higher medical loss ratios and more regulatory scrutiny.
  • Bain and KLAS’ survey of 228 U.S. healthcare execs suggests that all signs point to one solution, and that’s deploying tech to improve margins.

Where are payors investing? Care coordination (57%) and utilization management (55%) were the top IT investment priorities for the second straight year.

  • Payors place total cost of ownership, functionality, and scalability ahead of suite convenience, so best‑of‑breed is still the default buying motion.
  • Plans are leveraging AI for everything from member engagement (35%) and enrollment (26%) to risk adjustment (26%) and prior auth automation (20%).

Where are providers investing? Revenue. Cycle. Management.

  • Half of providers ranked RCM among their top IT priorities, placing it above clinical workflows (34%) and EHRs (32%).
  • RCM = ROI. Accurate documentation and coding results in cleaner claims and fewer denials, which directly translates to higher revenue and lower expenses.
  • It’s also a match made in heaven for AI automation, and RCM currently represents the four most common AI use cases: ambient documentation (62%), clinical documentation improvement (43%), coding (30%), and prior authorization (27%).

Here’s the kicker. Providers cite EHR integration and interoperability as their biggest pain points, so most of them prioritize their EHR vendors for new solutions.

  • Only 20% of providers are primarily best-of-breed buyers, and two-thirds of Epic customers would choose an Epic option that’s “good enough” over a better competing product.

The Takeaway

It’s getting pretty hard to not be bullish on AI. There’s still plenty of uncertainty, but both payors and providers now seem to agree that inaction is the riskiest action.

Rock Health Q3 Overview: Signals Out of Sync

Posted on by Jason Barry

Rock Health’s always-excellent digital health market overview painted an interesting picture for Q3, with venture funding continuing to climb despite several “signals out of sync.”

We’re steady on the surface. Digital health startups raised $3.5B across 107 deals in the third quarter, outpacing last year by a decent margin and bringing the year-to-date total to $9.9B across 351 rounds [Chart: Q3 Funding].

  • Deal volume continued to slow, but fewer raises yielded larger checks. Q3 saw 107 funding rounds, down from 120 in Q2 and 124 in Q1.
  • The average raise in 2025 now stands at $28.1M (up from $20.4M in 2024), and we’ve already seen 19 mega-rounds above $100M – surpassing last year’s total with a quarter left to go.

The middle is murky. Rock Health rolled up its sleeves and calculated widely variable trends in mid-market funding.

  • Series B deal flow has thinned, with just 30 raises through Q3, compared to an average of more than 60 annually over the past three years.
  • As fewer startups reach Series B, those that do are stretching the range of what a B round can be. Series B deal sizes so far in 2025 spanned $11M–$210M ($199M) – the widest spread since the boom of 2021.
  • Pair that with the persistent prevalence of unlabeled raises, and the thinning Series B pipeline suggests that startups are traveling increasingly winding roads to reach scale.

Activity is concentrating around workflows. The biggest theme of the Q3 report was that Clinical Workflow and Non-Clinical Workflow are now 2025’s two most-funded value propositions, capturing a combined 42% of the total funding [Chart: Value Propositions].

  • A $1.3B lead separates these value propositions from the rest of the pack, and workflow tools now appear to be in a league of their own.

Startups are heading horizontal. The report also highlighted a growing group of startups pushing into adjacent workflows, such as Abridge’s partnership with Highmark Health (expanding into prior auths) and Judi Health acquiring Amino (moving into patient navigation).

  • M&A volume is up 37% from last year, with 166 acquisitions through Q3 (already topping 2024’s 121 total), in large part due to these horizontal moves. 

The Takeaway

The numbers look steady, but the market is also steadily splitting in half. That means that the real story going forward won’t be whether digital health startups can attract investors (they can), but whether companies can demonstrate the impact needed to land on the right side of the divide. 

Particle vs Epic: The Lawsuit Moves Forward

Posted on by Jason Barry

For the first time in history, Epic will have to face antitrust claims in court after it failed to dismiss Particle Health’s allegations that the EHR giant has been wielding its monopoly power to stifle competition.

Here’s the overly-simplified version. Particle combines health data from 270M+ patients’ medical records by aggregating “thousands of sources”… sources like Carequality.

  • Carequality is effectively one of the largest health information networks, facilitating data exchange between network members (like Particle) who agree to only query patient data for “Permitted Purposes” such as Treatment, Health Operations, or Public Health Activities.
  • The problem at the heart of the lawsuit arises due to the fact that Treatment is the only purpose that organizations like Epic are actually required to respond to, causing all sorts of companies to warp their true purposes to Treatment-shaped requests.

Particle vs. Epic. Particle’s case alleges that Epic used its EHR monopoly to hamstring competition in the market for “payor platforms,” which allow payors to retrieve patient data to make decisions about care and coverage.

  • Last spring, Epic said that Particle was allowing its customers to inappropriately label their Carequality data requests as Treatment, then proceeded to stop responding to EHR requests from 34 Particle customers.
  • Particle’s lawsuit alleged that Epic trumped up the Carequality accusations in order to block it from serving its payor platform customers.

Epic filed to dismiss all nine of Particle’s claims. On Friday, the judge sided with Epic on five of the nine claims, dismissing the allegations that Epic maintained a conspiracy to uphold its market dominance, as well as claims of defamation and trade libel.

  • However, the court declined to throw out all three of Particle’s federal monopolization claims, as well as a state claim that Epic had interfered with a business contract.
  • Those claims will move forward into discovery, and Epic will now have to turn over documents that can shed light on whether its practices withstand legal scrutiny.

The Takeaway

Get the popcorn ready. Epic’s motion to dismiss was only partially successful, meaning it will now have to actually admit, deny, or qualify Particle’s remaining allegations. That deadline is quickly approaching on September 16th – then the real legal fireworks can get started.

Microsoft MAI-DxO and the Path to Medical Superintelligence

Posted on by Jason Barry

In an action-packed week to kick off the second half of the year, no story grabbed more headlines than Microsoft’s MAI-DxO proving four times more successful than human doctors at diagnosing complex diseases.

Microsoft is on the path to medical superintelligence… at least according to their excellent blog post outlining its new MAI Diagnostic Orchestrator, better known as MAI‑DxO.

  • MAI-DxO acts like a “virtual panel of physicians” collaborating on a case, orchestrating multiple AI agents with specific roles like forming diagnostic hypotheses, selecting tests, and interpreting results. 
  • It then applies a “debate chain” to arrive at an explainable diagnosis, all while avoiding over-testing to keep costs under control.. 

New breakthroughs require new benchmarks. As AI gets to the point where it’s breezing through multiple choice benchmarks like medical licensing exams, Microsoft decided to introduce SDBench to better simulate routine clinical practice.

  • SDBench deconstructs 304 of the most diagnostically complex NEJM cases, requiring LLMs (and physicians) to begin with an initial presentation, ask follow-up questions, order tests (each with assigned costs), and agree on a diagnosis.

Here’s how MAI-DxO stacked up:

  • MAI-DxO: 85% diagnostic accuracy / $7,200 estimated cost per patient
  • OpenAI o3: 79% / $7,850
  • Gemini 2.5 Pro: 69% / $4,800
  • Claude 4 Opus: 68% / $7,000
  • Llama 4: 55% / $4,000
  • Human Physicians: 20% / $2,950

What’s the catch? The human physicians weren’t allowed to use the internet or any outside help, which probably simulates a deserted island workflow more than routine clinical practice. Each of the participants also happened to be generalists as opposed to specialists, giving another edge to the LLMs. 

The Takeaway

MAI-DxO might have the potential to deliver superhuman diagnostics in constrained settings, but that doesn’t mean it’s ready to replace doctors. As Microsoft pointed out in its own blog post, “clinical roles are much broader than simply making a diagnosis. They need to navigate ambiguity and build trust with patients and their families in a way that AI isn’t set up to do.”

Catching the Right Wave in Digital Health

Posted on by Jason Barry

The ocean of digital health innovation seems to have a wave of new trends breaking every year, which is why Rock Health teamed up with LG NOVA to give enterprises a framework for “discerning promising currents from passing swells.”

Riding the wrong hype cycle can strain health systems’ limited resources with costly implementations or investment mistakes, so Rock Health divided the digital health landscape into 50 segments to see which show the most promise based on:

  • Value potential (VP) – share of total digital health venture funding, disease burden (degree of economic cost), and addressable population size.
  • Capturable opportunity (CO) – funding velocity, funding concentration (share of capital already held by large companies), and market maturity.

The “Goldilocks” waves include segments that are big enough to support a large market and ripe enough (but not too ripe) for new entrants to gain traction. [Chart: Strongest DH Segments]

  • High VP, High CO: Weight Management stood out with the highest scores in both VP and CO. The disease burden and funding levels don’t get much higher, and the balance of early- and late-stage companies signals a strong market with room for new entrants. 
  • Low VP, High CO: Patient Adherence was docked for its smaller share of overall digital health funding, but stood out for its favorable funding concentration and market maturity.
  • High VP, Low CO: Disease Monitoring had the opposite mix. The segment enjoys a large slice of the funding pie, but most of that is getting eaten by a few mega companies.
  • Low VP, Low CO: Dermatology received the low marks across the board, with poor scores for funding velocity, disease burden, and overall share of funding.

To complement its framework, Rock Health analyzed over 70 digital health unicorns to find other success signals from waves that the industry is already riding. Unicorns tended to:

  • separate from the herd with larger Series C rounds (ex. Abridge)
  • support care delivery or access and are often consumer-facing (ex. Wheel)
  • be therapeutic area agnostic w/ broad addressable markets (ex. Included Health)

The Takeaway

Timing the digital health market is no small feat, but Rock Health’s framework provides a helpful tool for those looking to catch the best wave with their investments and implementations.

The Healthcare AI Adoption Index

Posted on by Jason Barry

Bessemer Venture Partners’ market reports are always some of the best in the business, but its recent Healthcare AI Adoption Index might just be its finest work yet.

The Healthcare AI Adoption Index is based on survey data from 400+ execs across Payors, Providers, and Pharma – breaking down how buyers are approaching GenAI applications, what jobs-to-be-done they’re prioritizing, and where their projects sit on the adoption curve.

Here’s a look at what they found:

  • AI is high on the agenda across the board, with AI budgets outpacing IT spend in each of the three segments. Over half (54%) are seeing ROI within the first 12 months.
  • Only a third of AI pilots end up reaching production, held back by everything from security and data readiness to integration costs and limited in-house expertise.
  • Despite all the trendsetters we cover on a weekly basis, only 15% of active AI projects are being driven by startups. The rest are being built internally or led by the usual suspects like major EHRs and Big Tech.
  • That said, 48% of executives say they prefer working with startups over incumbents, and Bessemer encourages founders to co-develop solutions with their customers and lean in on partnerships that provide access to distribution, proprietary datasets, and credibility.

The highlight of the report was Bessemer’s analysis of the 59 jobs-to-be-done as potential use cases for AI. 

  • Of the 22 jobs-to-be-done for Payors (claims, network, member, pricing), 19 jobs for Pharma (preclinical, clinical, marketing, sales), and 18 jobs for Providers (care delivery, RCM) – 45% are still in the ideation or proof of concept phase.
  • Providers are ahead in POC experimentation, while most Payor and Pharma use cases remain in the ideation phase. Here’s a beautiful look at where different use cases stand.

Bessemer topped off its analysis with the debut of its AI Dx Index, which factors in market size, urgency, and current adoption to help startups map and prioritize AI use cases. One of the best graphics so far this year.

The Takeaway

Healthcare’s AI-powered paradigm shift is kicking into overdrive, and Bessemer just delivered one of the most comprehensive views of where the puck is going that we’ve seen to date.

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