2023 Trends Shaping the Health Economy

There have been some amazing healthcare market updates published recently, but Trilliant Health’s 2023 Trends Shaping the Health Economy Report might just take the cake.

The expansive analysis highlights 10 trends that define the emerging landscape of the health economy, as well as the corresponding challenges for each stakeholder.

It goes deep… 147 pages deep to be exact, but it’s well worth the time if you can find it. That said, time is a hot commodity, so here’s the breakdown:

  1. The commercial coverage market continues to erode
  2. The physical and mental health of Americans is unraveling
  3. Drug and diagnostic investments signal emerging patient needs
  4. The tepid demand trajectory for healthcare services persists
  5. Consumer behaviors are starting to manifest in patient decision making
  6. The traditional care pathway is becoming disintermediated
  7. New models of care further constraining provider supply
  8. The monopolistic effects of provider M&A are overstated
  9. Employers are facing higher costs for less care
  10. The market yield has been revealed, and it’s lower than you think

Where do we go from here? Stakeholders that depend on the commercial population can no longer ignore the fact that healthcare is a negative-sum game, with costs outpacing the value that’s created. Demand is heading in the wrong direction, and we cover new entrants commoditizing services on a weekly basis. The way to “lose less” is to compete on value.

It’s the same strategy for every payor, provider, and pharma company. The tactics are what’s different. Pick your battles, cut losses early, and lose less frequently / by a smaller margin than the competition. There isn’t enough space to get into those here, but 147 pages definitely gets the job done. 

The Takeaway

These trends each stem from the fact that healthcare is a negative-sum game, and that every part of the health economy will be impacted by reduced yield. Demand is declining alongside the number of people with commercial health coverage, while at the same time new entrants are commoditizing services and making loyalty harder to capture. Although the answer to this problem isn’t nicely tucked away in the report, Trilliant does a masterful job highlighting the trends that might help find it.

Hint Introduces Hint AI at Annual Summit

Direct primary care seemed more alive than ever at last week’s Hint Summit, which brought together physicians looking to escape the fee-for-service “hamster wheel” and companies building the tools to make that possible.

That of course includes Hint Health, who introduced its new Hint AI solution to help DPC physicians focus on their patients by automatically generating visit notes.

For a quick refresher on direct primary care, it’s a membership model where providers offer a fixed monthly rate for their services, eliminating the need for payor involvement as well as the mountain of administrative work that comes along with it. 

  • DPC also allows physicians to work for their patients instead of the system, resulting in shorter waits for appointments and more time for each visit (45min vs. 18min for FFS).
  • Despite its advantages, DPC still represents less than 1% of US primary care, in large part due to the hurdles of standing up a practice without the usual foundation of payor revenue. That’s where Hint comes in.

Hint’s All-in-One platform automates membership management and billing, while also serving as an EHR, communications solution, and now an AI assistant. Basically DPC-in-a-box.

  • Every feature within the platform is designed to bring DPC physicians closer to their patients, which Hint AI accomplishes by automatically transcribing visit notes and generating summaries that can be directly embedded into the patient record.
  • Unlike similar tools used by the wider healthcare system, Hint AI is tailored to the unique complexities of direct care, ensuring that anyone practicing under the DPC umbrella has access to the same technology without having to make compromises for their use case. 

The Takeaway

AI built for traditional healthcare will center around the problems of traditional healthcare, and the clashing aims of payors and providers will undoubtedly create plenty of new tools that reinforce these systems instead of fixing the underlying issues. Direct primary care physicians work outside of this status quo, only adopting tech like Hint AI that makes a tangible impact on patient care, and making DPC a great place to keep an eye out for the innovations actually moving the needle on care delivery.

Awell Raises $5M to Bring CareOps to Healthcare

Nobody thinks about their patients and clinical workflows more than actual care teams, but many of these teams are still using a mix of spreadsheets and Google Docs to track their processes because they haven’t had any better tools. Awell just raised $5M in seed funding to give them those tools.

Awell is a low-code editor that lets providers design clinical workflows and patient journeys that embed into their existing tech stack. Picture drag-and-drop building blocks tied together with if-this-then-that logic that you can use to create your ideal workflow. Those blocks could be: 

  • Care Pathways – PROMs, risk scores, engagement, etc.
  • Triage – Questionnaires, calculations, messages
  • Onboarding – Eligibility checks, symptom assessments, reminders

By using a single platform for a variety of tasks, Awell prevents providers from having to combine multiple tools or stitch different solutions together with custom code.

  • Virtual-first providers use the platform to automate their workflows while retaining control of the end-user experience, with Awell’s APIs doing the heavy lifting on the back end. 
  • Traditional providers and tech-enabled services companies use the platform for a similar reason, to swap their PDFs and text-based guidelines for dynamic workflows. 

Although the self-service route has its drawbacks (providers have a lot on their plates and even no-code development might be intimidating), Awell makes a strong case that healthcare could be about to witness its own version of the DevOps transformation that redefined the software industry.

  • This shift, aptly coined as CareOps, involves introducing the same agile development framework that trades fragmented teams and lengthy deployment cycles for integrated dev/care teams and quicker software releases. (Plenty more on CareOps here).
  • The promise of that methodology goes hand-in-hand with Awell’s mission: break down the silos between clinicians and engineers so that everyone can participate in the creation of care processes that ultimately deliver better patient outcomes.

The Takeaway

It’s hard to imagine that the software industry ever managed to get itself tangled in more fragmented practices and inefficiencies than healthcare, but if improving workflows was the cure, a no-code automation platform seems like a great place to start. Awell now has $5M to help kick off the CareOps movement, and it just might make it happen if it can convince enough providers to roll up their sleeves and automate some manual work.

Walmart In Talks to Acquire ChenMed

Although we touched on Walmart’s rumored acquisition of ChenMed last week, the ongoing talks are continuing to drum up lots of conversation around the healthcare strategy of major retailers and the potential implications if the deal goes through.

Here’s a quick primer on Walmart’s healthcare strategy, which so-far can be bucketed into three themes: Medicare and MA health plans, primary care, and employer virtual care.

  • Back in 2018, Walmart looked into making one of the grandest entrances to the market imaginable with a $67B acquisition of Humana. When that didn’t materialize, it pursued a more balance-sheet-friendly approach by launching its own in-house Medicare and MA plans, as well as partnering with UnitedHealth on a co-branded MA plan.
  • Walmart Health then debuted in 2019, and it’s a more comprehensive offering than it seems to get credit for. The 30 current locations provide primary care, urgent care, labs, imaging, optometry, audiology, and even dentistry.
  • When Walmart scooped up telehealth provider MeMD in 2021, it began offering virtual primary care and behavioral healthcare through commercial payors and employers.

Enter ChenMed, a senior-focused primary care provider with over 125 clinics across 15 states, making it the last major M&A target in the space following CVS-Oak Street and Amazon-One Medical.

  • ChenMed also takes on full-risk risk for the cost of its patients’ medical care, incentivizing long-term relationships and preventive care as opposed to the typical retail clinic model focused on episodic needs.

The acquisition would stake Walmart’s claim in the primary care land grab, allowing it to continue its push into the ever-growing Medicare Advantage market while leveraging ChenMed’s proven platform instead of building from the ground up.

  • At one point, Walmart had ambitions to open 4,000 of its own clinics – plans that have since been scrapped – yet now only has four new locations planned for next year after a string of operating challenges caused it to pump the brakes.
  • With some of Walmart’s largest competitors diving head first into care delivery, and limiting the options of late entrants in the process, the timing makes sense to either go all-in or risk losing ground to the competition.

The Takeaway

The number of attractive primary care clinic operators isn’t getting any bigger, and Walmart’s window of opportunity is shrinking if it wants to take the side door into the industry. There isn’t much of a ceiling on the splash that Walmart’s $600B in annual revenue and 4,300 retail locations could make in healthcare, especially if it can pick up an operator like ChenMed with the expertise and track record to help pull it off.

DHW Q&A: The Road to Medication Success With Synapse Medicine

With Clement Goehrs, MD
CEO and Co-founder of Synapse Medicine

In this Digital Health Wire Q&A, we sat down with Synapse Medicine CEO and Co-Founder Clement Goehrs, MD to discuss the challenge of accessing up-to-date drug information and how that data can be used to improve care delivery.

With more medications hitting the market every week, providers face the impossible task of tracking countless new interactions, and software developers don’t have it any easier as they look to equip providers with the right tools for writing safe prescriptions. Dr. Goehrs co-founded Synapse in 2017 to help them do just that, with easy-to-implement UI components making real-time drug data and decision support more accessible than ever.

Can you give the audience a quick introduction to Synapse Medicine and the story arch that brought us to your current solution set?

To put it simply, our mission is to make it as easy as possible to access medication information – wherever it is – and to help providers make the best clinical decisions using that data.

During my time as a physician, I saw first hand how difficult it was to find information for optimizing a prescription, and that we’re also facing a huge public health problem due to people dying from avoidable medication errors. Those are the problems we’re aiming to solve.

And when I say that we’re trying to make drug information easy to find, I mean for our end users (providers, pharmacists, nurse physicians), as well as our clients (usually EHRs, ePrecribers, or telemedicine companies – any type of software company building for clinicians that wants to add a drug information component).

Can you give us a deeper dive into Synapse Medicine’s clinical decision support solution, and walk us through what that user experience looks like?

One of the things that we understood very quickly was that providers don’t want to have multiple tools. That means that if you’re providing some kind of clinical decision support, and you want your end user to have the best experience, you also need to have a seamless integration inside the EHR.

You also have to be able to provide a wide range of tools without making the solution overly complex, and we do that with what we call components. Our components leverage our APIs with a UI layered on top for specific use cases, like drug interactions or side effects. That makes them easy to integrate and customize, but the user doesn’t even notice it’s a third party feature.

To give you an example, if a physician starts a prescription within the EHR, as they begin entering drugs they’ll start to see safety notifications on the side effects, potential interactions, and dosages. All of that is communicated in a way that’s easy to understand. 

No physician wants to see a pile of alerts, but they do want to have info on how to help their patients. So instead of just saying “there’s a severe interaction” like most tools do, we take it a step further by saying “you might want to divide that dose in half to avoid these side effects, and here are the publications supporting that decision.” That explanation is super important.

What are some of the big trends that you’re keeping your eye on, and how do you see them continuing to unfold going forward?

One of the main trends that I’m seeing is that there are a lot of legacy players, very big EHRs and software companies, that aren’t able to innovate at the pace they would like to because they have so much on their plate.

These companies face so many regulatory hurdles and have so many things they need to build, so with all the innovations and AI progress happening every day, more of them have been saying “we can’t keep building every single use case, and we are going to start working with companies that are focused on this specific problem.”

As more EHRs and telehealth companies start to integrate with other players to get the best of both worlds – breadth and depth of features – there’s a big opportunity for the startups working on those use cases.

Has there been anything that surprised you about the recent AI momentum, or as you implemented any new technology into your own platform?

AI is a fundamental part of a lot of what we do, and of course we continue to learn more about it every day. One project that we did with France’s equivalent of the FDA, and probably one of the first healthcare AI projects deployed at that scale, was to help monitor vaccine side effects and other drug interactions on a national level.

As we developed that algorithm, every time we made a major jump in performance, it was never because of the mathematical model. It was always because we ended up back at the data.

We understood the data very well from a medical point of view, and also had physicians on our team that could point out things like why we shouldn’t train the model on certain data. That’s what really enabled most of the fine tuning.

So for the short answer to your question: I’ve been surprised by how much truly understanding your field, and truly understanding your specific use case, is actually what makes AI smarter. It’s not just more data and a bigger model. I think the real progress wiIl come from the AI teams that have physicians and data scientists working together on performance.

What advice would you give to providers or startups that are thinking about improving their own prescribing strategy?

Number one, I would say to think deeply about the end user, about the physicians and the prescribers. That may seem trivial, but that experience is so important, and it’s surprising how often it gets overlooked.

Number two, think about scalability, particularly around adding secure data. What worked for 10 physicians in the beginning might not work as you scale. You’ll probably need better data, and you’ll probably want to do something with that data. If that data isn’t secure from the beginning, you’re going to lose a lot of time if you have to rebuild everything.

That brings me to number three: I wouldn’t recommend doing that by yourself. There are new drugs every week. There’s drug information all over the place, a lot of terminology, and few standards tying it all together. It’s a complex mess, and it would be a mistake to only consider the resources you would need to build it, because it’s maintaining it over time that gets really painful. You can probably avoid a lot of pain by having someone else do it.

For more on Synapse Medicine’s clinical decision support for medication success, head over to their website or reach out to [email protected].

NeuroFlow Picks Up Steam With New Growth Funding

When looking at the movers and shakers in the behavioral health arena, it’s hard not to include NeuroFlow in that conversation – especially after last week’s funding boost courtesy of Concord Health Partners.

The press release definitely leaned into the “unlabeled round” theme, offering neither a Series title nor a dollar value, although it did tag the funding for growing NeuroFlow “to match the increase in demand for its solutions” among health systems, payors, and government agencies.

NeuroFlow had previously raised a total of $57.8M, capital that was used to build out an AI-driven analytics platform that helps providers consistently screen for behavioral health issues, triage patients to appropriate care, and engage them between visits.

  • That platform enables NeuroFlow’s partners to overcome the usual hurdles to adopting an integrated behavioral health model, reducing the risks associated with undiagnosed conditions and helping them get out in front of potential issues before they escalate. 
  • The data collected through that process is then served to providers within their established workflows in the form of decision support, creating a nice feedback loop with the platform’s engagement component while helping create high-touch care journeys.

NeuroFlow’s story over the past year has been about partnership momentum, with a string of new names on the roster like Novant Health, Atlantic Health System, and Emory Healthcare.

  • Growth acquisitions also found a place in NeuroFlow’s playbook, and it recently picked up Capital Solution Design (Behavioral Health Lab) to expand its reach within the VA while gaining some valuable VA-specific EHR integration expertise.
  • The mission behind NeuroFlow is to make mental health a bigger part of physical health, and the latest investment will push that pursuit forward by funding new platform capabilities and quite possibly more strategic M&A.

The Takeaway

The behavioral health segment continues to remind us that it’s one of the most resilient corners of the digital health market, and NeuroFlow’s raise is the latest proof point that these startups can keep securing capital in an otherwise gloomy funding environment. NeuroFlow isn’t offering teletherapy and it’s not delivering care, but it seems to be carving out a nice niche with its “picks and shovels” approach to bridging gaps in the treatment journey for those that are.

What’s Behind the Medicare Slowdown?

Since Medicare coverage first took effect almost six decades ago, the program’s runaway spending has played a leading role in the story of the federal budget. Now, the end of that growth is stealing the spotlight.

An excellent piece in The New York Times highlighted how Medicare’s unsustainable climb reached a turning point in 2011, and for reasons that aren’t exactly clear.

In 2011, Medicare spending per beneficiary (MSPB) reached $13,159, nearly double the level it was at near the turn of the century.

  • If historical growth had sustained beyond that point, we’d currently be sitting at roughly $22,006 MSPB. Luckily, that’s not what happened.
  • Spending leveled out, and we now find ourselves at $12,459 MSPB, a nearly $4 trillion gap compared to previous projections… yet the underlying cause remains a mystery.

The trillion dollar question: what changed? The authors call out obvious shifts in Medicare policy, namely the Affordable Care Act in 2010, and its reduced Medicare payments to hospitals and payors with private Medicare Advantage plans.

  • While ACA was certainly a contributor, most of the reductions are attributed to a category that the budget office calls “technical adjustment,” which describe changes to a wide base of topics such as the expansion of cholesterol and blood pressure medicines.

The NY Times concludes that the true reason for the change is a hard problem that remains unsolved, but the smart folks on social media were quick to pick up where they left off, floating possibilities such as:

  • As MA lives increased, the types of MA plans also improved due to the phasing out of inefficient plan designs
  • Age of death increases stopped around this time, so US citizens aren’t living to older ages with increasingly complicated health issues 
  • The rise of ACOs started in 2012, although we just covered why that factor probably doesn’t account for a huge share of cost reductions

The Takeaway

Savings attribution has always been a fundamental challenge for the healthcare industry, underpinning many of the issues with value-based care and other alternative models. Now that we’ve found ourselves at an inflection point where Medicare spending is slowing but still outpacing the federal budget, the solution to that savings attribution problem will also be what lets us identify the levers that will keep the trend heading in the right direction.

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