Month: May 2024

Atropos Series B Bridges Evidence Gaps

Posted on by Jason Barry

It’s a bad day to be an evidence gap, with Atropos Health closing $33M in Series B funding to transmute real-world data into real-world evidence.

Atropos accomplishes this alchemy by quickly producing retroactive observational studies using an evidence platform of 200M+ patient records, as well as a partner network packed with big names like Mayo Clinic and Clarify.

  • These publication-grade “Prognostograms” are used by both providers (e.g. to answer clinical questions using individually tailored RWE) and life science orgs (e.g. to emulate clinical trials that otherwise would have taken a lot longer).
  • Forbes has a solid write-up of the secret sauce on the backend – plus a nice Greek mythology lesson on the three fates whose scissors can either end or extend the lives of mortals, one of which is named Atropos.

The fresh funding will fuel a trio of initiatives centered around new ways to democratize access to RWE, which naturally includes a healthy dose of generative AI.

  • Atropos plans to “further its stake” in value-based care by continuing to invest in tailored evidence to guide clinical decisions (see its recent partnership with Arcadia), notable given that “the low hanging fruit” of VBC is mostly gone and providers are now looking for more support with complicated patients to succeed in risk-based contracts.
  • The Atropos Evidence Network is pushing into oncology and specialty care through new partnerships with McKesson and Cencora (formerly AmerisourceBergen), and Atropos intends to “double down” on life sciences collaborations after finding traction with everything from R&D to commercial use cases.
  • The full launch of ChatRWD is now slated for this summer, which is an LLM-independent framework built to eliminate hallucination risk while slashing the time needed to produce reports using a chat-based interface. A pending publication will back the great branding with some actual data in the coming months.

The Takeaway

Healthcare doesn’t have any problem generating data, but it’s proven to be a massive challenge to turn these troves of data into actionable evidence. Bridging that gap isn’t exactly a small undertaking, but Atropos now has $33M to make it happen.

A Delicious Primer on Food-as-Medicine

Posted on by Jason Barry

Rock Health dished up a fantastic primer on the food-as-medicine market, serving as a helpful cheatsheet of which trends will stay fresh the longest, and which ones are already stale.

Fertile grounds for new FaM models have been created by shifting consumer behaviors around diet and wellness, with 20% of US adults saying the pandemic prompted healthier choices. [Graphic: Three eras of food-as-medicine]

  • Payors are also grappling with the rising costs of treating the nearly 50% of Americans with diet-related illness, and FaM offers an avenue to reign these in without pricey medications like GLP-1s.
  • Policy changes have also planted the seeds for growth, with new initiatives helping scale FaM programs like medically tailored meals. One wild stat is that FaM partnership volume in the last 18 months has surpassed that of the prior seven years combined.

As the FaM market begins to sprout, startups are facing an increasingly complicated menu of funding sources and potential partners

Value chain segment #1: Food access

  • Food and supply chain – Providers of healthy groceries, prepared meals, or digital marketplaces for third-party products, including delivery partners and food “farmacies” that fill clinician’s produce prescriptions. Examples: Mom’s Meals, Uber Health
  • Service navigation – Services that refer consumers to food access programs and support enrollment, often through community orgs like FQHCs. Examples: Findhelp, Unite Us

Value chain segment #2: Nutrition care

  • Medical nutrition counseling – Virtual or in-person nutrition counseling with dietitians to provide tailored nutrition plans and resources. Examples: Foodsmart, Season Health
  • Behavior change support – Tools for tracking diet and outcomes, educational content, and recommendations. Includes non-digital services like nutrition and cooking classes. Examples: Heali, SeekingSimple

Value chain segment #3: Program enablers

  • Fintech – Targeted tools and vouchers (category-restricted to healthy products) that enable consumers to use food benefits provided by their health plan. Examples: Solutran, Soda Health
  • Data and food benefits management – Data on consumer behavior or food products to help payors optimize benefit design, measure program impact, and inform engagement strategies. Examples: DietID, NourishedRx

The Takeaway

The food-as-medicine market is turning into a “cornucopia of innovation,” but founders looking to take advantage of new funding mechanisms now have to separate the wheat from the chaff when it comes to business models and potential partners.

Augmedix Takes Hit As Ambient AI Heats Up

Posted on by Jason Barry

Augmedix just reported Q1 results that managed to axe its share price in half, an interesting turn of events given the company’s role as the bellwether for the white hot ambient AI space.

There’s plenty to unpack when the only publicly-traded medical scribe company takes a hit like that despite beating expectations for both EPS and revenue, which jumped 40% to $13.5M.

The simple explanation? Competition. Augmedix saw “a slow-down in purchasing commitments” as providers evaluate competing offerings, prompting it to cut its full-year revenue forecast to between $52M and $55M (down from $60M to $62M).

  • During the investor call, Augmedix said that 42 companies currently offer GenAI medical documentation solutions, leading to a ton of noise and just as many pilots.
  • Although the increased demand from health systems is promising for the overall sector, it doesn’t exactly translate to success for established players when nimble startups like Nabla, Abridge, and Suki start swarming in on the action.

Augmedix is shaping its strategy around a product portfolio that lets providers choose the right tool for their needs, expanding beyond Augmedix Live (human scribes, high cost) with Augmedix Go (GenAI scribe, low cost) and Augmedix Go Assist (GenAI + human review, medium cost).

  • The push into GenAI has apparently been a double-edged sword. Augmedix reported that strong uptake for its new AI products might result in slower revenue growth as customers transition away from its high-margin Live solution.
  • New products tailored to specific settings will be another focus, as seen with the recent debut of Augmedix Go ED following a pilot-turned-implementation at HCA Healthcare. As scribing tech becomes commoditized, expect to see more players differentiate on setting / specialty.

The Takeaway

If there’s one lesson to learn from Augmedix’s first quarter, it’s that business is booming in the ambient AI space, but that doesn’t benefit incumbent leaders when it also attracts hungry competitors looking to feast on the same momentum.

Cross-Market Mergers Aren’t For the Patients

Posted on by Jason Barry

Make sure you’re sitting down for this one, because new research suggests that cross-market hospital mergers aren’t doing patient wallets any favors.

To investigate the impact of cross-market mergers on both prices and quality, researchers rounded up 214 hospitals that acquired hospitals further than 50 miles away, then compared them to 955 control hospitals without any merger activity during the study period. This was also the first study to use claims data to back its findings.

Six years after acquisition, acquirers had increased their prices for patients by an average of 12.9% relative to control hospitals, yet saw no discernible impact on mortality or readmissions.

  • The impact was even higher among serial acquirers with at least four separate acquisitions, which increased prices by a steep 16.3%. This wasn’t a small subset either, representing 45% of the M&A hospital group.
  • On top of that, there was a 21.8% price increase when the target’s market share was greater than the acquirer’s (vs. 9.7% when the opposite was true), which makes sense as smaller acquirers have more to gain from acquiring an entity with more market power.

There have been a couple of other studies examining the impact of cross-market mergers, but this was the first to use claims data to untangle some of the factors driving the price effects (serial acquisitions, target size) while showing no significant impact on quality.

Although the mechanisms behind the price effects weren’t within scope, there are a few potential reasons that likely contributed.

  • Common customers – If the target and acquirer hospitals both share the same customer, having a larger operational footprint improves bargaining power (e.g. employers need provider networks that span multiple patient markets if they have employees in multiple markets).
  • Tying – A health system with a strong position in one market could tie its services to a second market (e.g. a cutthroat system could operate at a loss in a second market to drive out competitors while staying afloat using margin from its primary market).
  • Change in control – Acquirer hospitals are able to increase prices at the target because it wasn’t maximizing profit for whatever reason. Given the increases this study shows at the acquirers themselves (which by definition didn’t change control), this one is probably ruled out.

The Takeaway

All-in-all, the evidence is mounting that competing hospitals don’t make massive acquisitions for altruistic reasons (earth-shattering, we know). If the scale wasn’t already tipped toward needing more antitrust scrutiny of cross-market mergers, this study seems to get us past the usual conclusion of “more research is needed.”

K Health Introduces First-of-its-Kind AI Knowledge Agent

Posted on by Jason Barry

Clinical AI is stepping up to the big leagues, and K Health is the team that’s taking it there.

In an exclusive interview with Digital Health Wire, K Health CEO Allon Bloch took the lid off his company’s new AI Knowledge Agent, a first-of-its-kind GenAI system purpose-built for the clinical setting.

On the surface the AI Knowledge Agent looks and feels like a familiar medical chatbot, with a simple search bar interface for the user to ask natural language questions about their health. It isn’t until you see the responses that you realize you’re looking at something entirely unique.

The AI Knowledge Agent is about as far away from a rules-based chatbot as you can get. The agent is composed of an array of large language models enhanced by K Health’s own algorithms, carrying several major differentiators from today’s standard AI applications:

  • It incorporates the patient’s medical history grounded by their EHR to provide highly tailored responses, enabling a level of personalization that’s impossible to match for standalone models (i.e. a diabetic and a heart failure patient will see different answers to the same question, using their own history, potential adverse drug interactions, etc.).
  • It will be embedded into health systems to serve as a digital front door that intelligently routes patients to the right place to resolve their needs, reaching everything from primary care and specialists to labs and tests within the same interface.
  • It’s optimized for accuracy by using curated high-quality health sources, then leverages multiple specialized agents to verify the answer matches the sources and the EHR data is appropriate. It will even tell you that it doesn’t know the answer rather than hallucinate.

In head-to-head testing against top tier foundation models, K Health’s multi-agent approach led to answers for sample medical questions that were 9% more comprehensive (included clinically crucial statements from the “gold standard” answer) and had 36% fewer hallucinations than its closest benchmark, GPT-4. 

  • Strong results, especially considering that the AI Knowledge Agent shines brightest in real-world situations where it can personalize its answers using EHR context.

For possibly the first time ever, GenAI has reached the point where it can support actual clinical journeys, delivering answers personalized to the patient’s medical history while connecting them directly to required care. The era of Googling symptoms then calling your doctor feels like it’s finally coming to an end.

The Takeaway

We’re very much in the opening act of clinical AI, and understandably cautious providers are only just beginning to test the waters. That said, it’s easy to imagine that we’ll one day look back at launches like K Health’s AI Knowledge Agent as key moments for building trust and confidence in the AI systems that reshaped care delivery.

The 50 Best Digital Health Newsletters, Influencers, and Podcasts for 2024

Posted on by Jason Barry

We’re dedicating today’s top story to bring you an updated list of the people and publications that we rely on to find the most interesting digital health stories from across the web. Assuming that you already subscribe to Digital Health Wire, these are the 50 other newsletters, websites, and podcasts to follow if you want to keep up with the latest and greatest in healthcare.

Although we stay on top of all the mainstream outlets and digital health journals, some of the best content is usually found just off the beaten path. We’re a newsletter, we love newsletters, so we’re kicking things off with our favorite healthcare newsletters. 

When we’re done rounding up the headlines from the major news sites and back out of our morning newsletter rabbit hole, we can count on finding more fresh perspectives from these specialty publications and blogs.

These days most of our favorite content isn’t published, it’s tweeted. These all-stars are the ones doing the tweeting.

And finally, the podcasts that let our ears take over when our eyes are tired from all the blogs and tweets. We have a soft spot for founder interviews, B2B trends, and long form conversations.

It’s a lot to keep up with, but if you want the best digital health news out there, these sources will do more than get you started. You can also subscribe to Digital Health Wire and we’ll do the heavy lifting for you:)

PS – This list could easily have been a top 100, so if there’s a publication or news source that we’re crazy for not including, hit reply and let us know!

Transcarent Lands $126M Series D

Posted on by Jason Barry

Although Transcarent was already a unicorn, it might be about to grow another horn after landing $126M in Series D funding at a $2.2B valuation.

The Transcarent platform makes it easy for employees to access all of their care needs using a single convenient interface – their phone – while also simplifying how employers provide and track that care.

  • The platform connects members to comprehensive experiences including Everyday Care, Pharmacy Care, Surgery Care (through partnerships with health systems and ambulatory care providers), and Behavioral Health Care.
  • At a time when point solution fatigue is crippling employers and telehealth companies are imploding due to a lack of downstream revenue from other services, Transcarent’s approach definitely has a few things going for it.

The fresh funding will be used to accelerate Transcarent’s AI capabilities, support commercialization, and more than likely acquire other companies (plus the customers they bring along with them).

  • Transcarent apparently had upwards of $100M in the bank before closing the latest round, but it would appear that $226M is a more comfortable starting point when you’re looking to build-out your AI and sign some new partnerships.

The reason behind the AI push is the interconnected nature of the platform itself, which has already enabled several AI features that are harder to pull off with a more narrow approach.

  • For example, if a doctor on Transcarent’s platform reports that a patient has sinus pain, the AI will flag their seasonal sinus infections in their medical history, and can then pull the prescriptions they’ve used in the past – expediting both diagnosis and treatment.
  • If Transcarent’s last phase of growth was about reaching the scale to make that happen, the next phase will revolve around rolling out as many of these features as possible.

The Wire

If you needed any more proof that the market is looking for platforms instead of point solutions, Transcarent’s valuation should give you plenty. Both employers and consumers want a single platform to manage healthcare, and it turns out that providing one leads to good things.

How Walmart F—– Around and Found Out

Posted on by Jason Barry

White flags are flying left and right, with Walmart announcing its retreat from care delivery less than a full week after Optum made a similar surrender.

Walmart’s five-year foray into primary care is ending with the closure of 51 health centers, the shuttering of its telehealth service, and the cancellation of any active ambitions in the space.

  • The press release chalked up the “difficult decision” to a challenging reimbursement environment and high operating costs, which ultimately made the business unsustainable.

The abrupt finale arrives shortly after Walmart laid out plans to nearly double its footprint to 75+ health centers by the end of 2024, as well as several other marquee announcements.

  • As recently as November, Walmart was inking health system partnerships with the likes of Orlando Health, and Bloomberg was even reporting on a potential acquisition of ChenMed that would have opened the doors to the Medicare Advantage market.

So what happened, and why couldn’t the nation’s largest retailer succeed in delivering care to the millions of underserved patients where it already has a presence? Mainly because retail clinics aren’t set up to succeed.

  • Scaling brick-and-mortar clinics is simply a low margin endeavor. Reimbursement is low, provider costs are high, and the telehealth piece looks more commoditized every day.
  • Even with Walmart’s economies of scale and armies of foot traffic, the system it was operating in doesn’t incentivize preventative care, but rather expensive procedures that it didn’t offer in-house.

The perfect storm of inflating costs and shiny technology that fails to actually reduce those costs is proving too much for retailers and telehealth companies alike. The only ones succeeding seem to have an edge that makes it possible:

  • They have access to better rates (One Medical’s health system relationships)
  • They have boosted margins from marking up generics (Hims & Hers)
  • They control premium through value-based care arrangements
  • They have some form of subscription revenue

The Takeaway

The moral of Walmart’s story is that even if you have all the best ingredients, the meal is still only going to be as good as the recipe. Having groceries and doctors under one roof doesn’t lead to more health visits if people don’t want to see a doctor where they get their groceries.

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