House Task Force AI Policy Recommendations

The House Bipartisan Task Force on Artificial Intelligence closed out the year with a bang, launching 273-pages of AI policy fireworks.

The report includes recommendations to “advance America’s leadership in AI innovation” across multiple industries, and the healthcare section definitely packed a punch.

The task force started by highlighting AI’s potential across a long list of use cases, which could have been the tracklist for healthcare’s greatest hits of 2024:

  • Drug Development – 300+ drug applications contained AI components this year.
  • Ambient AI – Burnout is bad. Patient time is good.
  • Diagnostics – AI can help cut down on $100B in annual costs tied to diagnostic errors.
  • Population Health – Population-level data can feed models to improve various programs.

While many expect the Trump administration’s “AI Czar” David Sacks to take a less-is-more approach to AI regulation, the task force urged Congress to consider guardrails in key areas:

  • Data Availability, Utility, and Quality
  • Privacy and Cybersecurity
  • Interoperability
  • Transparency
  • Liability

Several recommendations were offered to ensure these guardrails are effective, although the task force didn’t go as far as to prescribe specific regulations. 

  • The report suggested that Congress establish clear liability standards given that they can affect clinical-decision making (the risk of penalties may change whether a provider relies on their judgment or defers to an algorithm).
  • Another common theme was to maintain robust support for healthcare research related to AI, which included more NIH funding since it’s “critical to maintaining U.S. leadership.” 

The capstone recommendation – which was naturally well-received by the industry – was to support appropriate AI payment mechanisms without stifling innovation.

  • CMS calculates reimbursements by accounting for physician time, acuity of care, and practice expenses, yet fails to adequately reimburse AI for impacting those metrics.
  • The task force said there won’t be a “one size fits all” policy, so appropriate payment mechanisms should recognize AI’s impact across multiple technologies and settings (Ex. many AI use cases may fit into existing benefit categories or facility fees).

The Takeaway

AI arrived faster than policy makers could keep up, and it’ll be up to the incoming White House to get AI past its Wild West regulatory era without hobbling the pioneers driving the progress. One way or another, that’s a sign that AI is starting a new chapter, and we’re excited to see where the story goes in 2025.

Redesign Raises $175M Venture Building Fund

Launching a healthcare company is hard. Launching dozens of them is even harder, but that’s exactly what Redesign Health plans to do after raising $175M for its largest fund to-date.

Redesign isn’t a venture capital firm, although it’s funded more digital health startups than most VCs. It’s not an accelerator, yet it’s launched more companies in the past six years than most pure startup studios.

Then what is it? Redesign is a “venture builder” that’s cultivated over 60 healthcare companies by supporting founders across three key areas:

  • Redesign’s hands-on approach starts with an in-house research lab / analyst team that helps look into sectors, identify challenges, and validate business cases.
  • An established network of relationships with health systems, payors, and other health tech companies gives founders an accelerated path to commercial traction.
  • Redesign equips startups with operational resources ranging from executive placements to branding services to fine-tune operations throughout every stage of growth.

The new fund will allow Redesign to partner on companies at the intersection of technology and the investment themes where it believes “innovation can drive the greatest impact”:

  • Addressing the healthcare labor shortage
  • Accelerating value-based and longitudinal care
  • Advancing healthcare interoperability
  • Preparing for an aging population
  • Eliminating barriers to health equity
  • Expanding sites of care
  • Growing the insured population
  • Driving healthcare personalization and consumerization

Since getting its start in 2018, Redesign’s portfolio has reached more than 15M patients and generated over $1B in revenue, producing some big name players like metabolic health startup Calibrate and VBC cardiology company CardioOne (acquired by WindRose earlier this year).

  • There’s been a few bumps along the way – including layoffs as Redesign slowed its launch pace to weather the post-pandemic downturn – but the new fund is a good sign that it expects smoother sailing from here.

The Takeaway

Healthcare startups have high upfront capital requirements, steep steps between business stages, and difficulty recruiting the seasoned executives needed to reach scale. Although those problems will never magically disappear, Redesign now has a $175M magic wand to make them a whole lot more manageable.

Rock Health’s Innovation Maturity Curve Heading Into 2025

Rock Health is wrapping up the year in style by updating its Innovation Maturity Curve with the hottest trends of 2024, and sharing its predictions for what lies ahead.

The curve uses three major data categories to plot digital health innovations:

  • 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

Here’s how 2023’s biggest trends progressed over the course of the year:

AI in Healthcare (Maturity Score: Developing) – Digital Health Wire readers know the AI hype cycle is still in full swing, with AI-first digital health startups landing $3.3B in venture capital through the end of Q3. AI partnerships also surged (Rock Health counted 80+, an undercount if anything), but 2024’s plateau in research activity gave another sign that we’re transitioning to practical applications and commercialization. 

  • Keep an eye on: We’re entering a phase of AI consolidation, with cutthroat competition for major accounts in segments like ambient documentation. As Big Tech inks their own partnerships and juggernauts like Epic double down on new features, “AI enablement will become table stakes across solutions rather than a core differentiator.”

Digital Obesity Care (Maturity Score: Developing) – Moving up from “Nascent” on last year’s curve, the conversation around obesity care has been transformed by GLP-1s and contributed to a rise in digital platforms to help patients access treatment and support.

  • Keep an eye on: Increased competition necessitates differentiation. With GLP-1 access still in flux, players need to build momentum with more than just prescribing (precision treatment planning, biometric tracking, support for co-occurring conditions like PCOS).

Food as Medicine (Maturity Score: Emerging) – FaM moved from a niche term to a buzzword (props to Rock Health for helping it happen), with category funding doubling on-year after big raises from players like Foodsmart ($200M). Payors, providers, and grocers contributed to over 30 new FaM partnerships this year.

  • Keep an eye on: FaM innovation is closely tied to reimbursement models for food delivery and nutrition consultations, so continued success hinges on sustained policy support. Assuming that happens – seems likely given the Make America Healthy Again chatter – 2025 could be another huge year.

The Takeaway

With the digital health recalibration now (mostly) behind us, Rock Health expects 2025 to give innovators a chance to demonstrate a measurable impact on outcomes and continue their trek along the maturity curve. The whole report is well worth checking out for details on smaller up-and-coming categories like new wearable form factors, digital twins, and climate tech.

Soda Health Cracks Open $50M of Funding

Soda Health is cracking open $50M of Series B funding to shake up supplemental benefits.

Medicare Advantage plans deliver $131B/year in benefit funds for transportation, fitness, and grocery programs – yet the impact often falls flat due to an outdated tech infrastructure that makes it difficult for members to take advantage of their benefits.

Soda’s Smart Benefits platform unlocks the full potential of these programs by rebuilding their core infrastructure with a modern payments stack and an expansive retail network:

  • Members get a user-friendly way to understand where and how to use their benefits.
  • Payors can scale benefit programs supported by Soda’s network of 50k retail locations (including Kroger, Albertsons, CVS) to optimize utilization and lift STAR ratings.
  • Retailers get more member traffic to offer health products, food, and pharmacy services.

The secret ingredient is the retail network, which provides the data underpinning Soda’s biggest differentiator: personalized patient engagement. 

  • Soda’s “first-of-its-kind open loop fintech infrastructure” tracks item-level purchases in real time, allowing it to reward members for using their benefit dollars on products approved to fill gaps in their care.
  • By connecting supplemental benefits with insights from retail data, Soda is uniquely positioned to deliver tailored outreach for closing care gaps (by encouraging preventative screenings, improving medication adherence, etc.).

The fresh funds will accelerate Soda’s expansion into new CMS-compliant benefit categories and add some extra fizz to its gap closure strategies, which will reportedly allow it to enter risk-based structures with MA and Medicaid plans.

The Takeaway

Soda isn’t here to build a better supplemental benefits platform, it’s here to rebuild the category from the ground up using a stronger infrastructure of retail partners, patient engagement, and care gap closure. Climbing utilization trends and dwindling capitation rates are pressuring MA plans from multiple fronts, so the time is right for a refreshing approach.

CB Insights 2024 Digital Health 50

CB Insights unveiled its annual Digital Health 50 rankings of the most promising private digital health startups, and this year’s list certainly included many of the industry’s brightest stars.

Here’s the methodology / our disclaimer: The final cut was selected from a pool of 10k+ applicants based on “proprietary metrics” – Commercial Maturity and Mosaic Scores – along with data on partnerships, growth stats, and market adoption. (CB Insights is of course happy to share this data with its customers, but promises that being one of them doesn’t land you a spot on the list.)

With that out of the way, here’s a look at the Digital Health 50 (high-res version):

CB Digital Health 50

It’s tough to compare this list to last year’s given the ever-evolving categories and methodology, but CB Insights called out four key themes for the latest cohort:

  • AI is becoming foundational infrastructure: 36 of the 50 companies are building AI products, ranging from operational automation high-flyers like Laguna to specialized healthcare LLMs like Hippocratic AI. No surprises here.
  • Workflow efficiency is a key priority: 19 of the companies are streamlining administrative or clinical tasks, spanning document processing startups (Tennr) to ambient AI heavyweights (Abridge). These players seem like an obvious inclusion, but the same could be said last year when ambient AI was nowhere to be found.
  • Diagnostic innovations dominate: 11 companies comprised this year’s largest category, developing next-gen diagnostics across imaging (Airs Medical), pathology (Proscia), and non-invasive diagnostics (Alimetry). Diagnostics was in a three-way tie with Clinical Intelligence and Virtual Care, although the categories have some hazy boundaries. 
  • More specialized platforms: Virtual and hybrid care representation doubled in this year’s cohort, reflecting the shift from general telemedicine toward condition-specific virtual models in areas like mental health (Talkiatry) and cancer care (Resilience).

The Takeaway

Lists like these never fail to get pushback because of the methodology or glaring exclusions, but this year’s cohort feels pretty well aligned with the high momentum names that keep popping up in our own coverage. Major congrats to the companies that were included.

Real-World Lessons From NYU’s ChatGPT Roll Out

NYU Langone Health just lifted the curtain on its recent ChatGPT experiment, publishing an impressively candid look at all of the real-world data from its system-wide roll out.

A new article in JAMIA details the first six months of usage and cost metrics for NYU’s HIPAA-compliant version of ChatGPT 3.5 (dubbed GenAI Studio), and the numbers paint a promising picture of AI’s first steps in healthcare. Here’s a snapshot of the results:

Adoption

  • 1,007 users were onboarded (2.5% of NYU’s 40k employees)
  • GenAI Studio had 60 average weekly users (submitting 671 queries/week)
  • 27% of users interacted with GenAI Studio daily (Table: Usage Data)

Use Cases

  • Majority of users were from research and clinical departments
  • Most common use cases were writing, editing, data analysis, and idea generation
  • Examples: creating teaching materials for bedside nurses, drafting email responses, assessing clinical reasoning documentation, and SQL translation

Costs

  • 112M tokens were used during the six months of implementation 
  • Total token cost was $4,200 ($8,400 annualized)
  • Divide that cost by the 60 average weekly users, and it’s under $3 per user per week 

While initial adoption seems a bit low at 60 weekly users out of the 40k employees that were offered access, the wide range of helpful use cases and relatively low costs make ChatGPT pretty close to a no-brainer for improving productivity.

  • User surveys also gave GenAI Studio high marks for ease of use and overall experience, although many users noted difficulties with prompt construction and felt underprepared without more in-depth training.

NYU’s biggest tip for GenAI implementations: continuous engagement and education is key for driving adoption. GenAI Studio saw large spikes in new users and utilization following “prompt-a-thons” where employees could practice and get feedback on prompt construction.

The Takeaway

For healthcare organizations watching from the wings, NYU Langone Health was as transparent as it gets regarding the benefits and challenges of its system-wide roll out, and the case study serves up a practical playbook for similar AI deployments.

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