Month: March 2025

PHTI Delivers Mixed Reviews on Ambient Scribes

Posted on by Jason Barry

The Peterson Health Technology Institute’s latest technology review is here, and it had a decidedly mixed report card for the ambient AI scribes sweeping across the industry. 

PHTI’s total count of ambient scribe vendors stands at over 60, but the bulk of its report focuses on the early experiences and lessons learned from the top 10 scribes across leading health systems.

According to PHTI’s conversations with health system execs, the primary driver of ambient scribe adoption has been addressing clinician burnout – and AI’s promise is clear on that front.

  • Mass General Brigham reported a 40% reduction in burnout during a six-week pilot.
  • MultiCare reported a 63% reduction in burnout and a 64% improvement in work-life balance.
  • Another study from the Permanente Medical Group found that 81% of patients felt their physician spent less time looking at their computer when using an ambient scribe.

Despite these drastic improvements, PHTI concludes that the financial returns and efficiency of ambient scribes remain unclear.

  • On one hand, enhanced documentation quality “could lead to higher reimbursements, potentially offsetting expenses.”
  • On the other hand, the cumulative costs “may be greater than any savings achieved through improved efficiency, reduced administrative burden, or reduced clinician attrition.”

It’s a bold conclusion considering the cost of losing a single provider, let alone the downstream effects of having a burned out workforce. 

PHTI’s advice to health systems? Define the outcomes you’re looking for and then measure ambient AI’s performance and financial impacts against those goals. Bit of a no-brainer, but sound advice nonetheless. 

The Takeaway

Ambient scribes are seeing the fastest adoption of any recent healthcare technology that wasn’t accompanied by a regulatory mandate, and that’s mostly because of magic that’s hard to capture in a spreadsheet. That said, health systems will eventually need to justify these solutions beyond their impact on the clinical experience, and PHTI’s report brings a solid framework and standardized methodologies for bridging that gap.

Navina Lands $55M to Bring AI Insights to VBC

Posted on by Jason Barry

As the number of providers transitioning to value-based care continues to grow, the need for timely clinical intelligence is climbing right alongside it, and Navina just landed $55M in Series C funding to become the definitive source for AI-driven insights.

Navina’s AI clinical intelligence platform aggregates data from a wide range of sources like the EHR and medical claims to equip clinicians with real-time recommendations for improving care quality and financial outcomes.

  • The copilot supports decision-making from the back office to the bedside, delivering insights directly within existing workflows at the point of care. This article does a good job laying out some of Navina’s levers for driving success in VBC.
  • By surfacing relevant patient information in an accessible format, Navina aims to not only improve diagnostic accuracy and care gap closure, but also to reduce burnout and administrative burdens.

Some of providers’ biggest barriers to VBC adoption are the overwhelming amounts of disparate data sources and the documentation requirements needed to produce results. It turns out that offloading these pain points is a solid strategy.

  • Navina has quickly grown to serve over 10k medical professionals delivering care to 3M patients across 1,300 clinics, and was just named #1 Best in KLAS for Clinician Digital Workflow.
  • It’s also racking up a lengthy partner roster of big names in the VBC-enablement arena, including both Agilon and Privia Health.

Navina is now setting its sights on larger provider orgs and health systems, as well as expansion into new markets across specialty care, payors, and pharmaceuticals.

  • The fresh funds were also earmarked for the 2025 flavor of the year – AI platform enhancements – and it sounds like ambient scribing is first up on the docket.

The Takeaway

Providers are increasingly getting compensated for the quality of the care they deliver rather than the volume of services they provide, but fragmented data and inefficient manual workflows have been holding back the transition. Navina now has another $55M to connect the dots to VBC success for any organization looking to make the leap.

DispatchHealth Acquires Hospital-at-Home Provider Medically Home

Posted on by Jason Barry

DispatchHealth is acquiring fellow hospital-at-home provider Medically Home to give more patients access to their preferred hospital bed: the one they already have at home.

DispatchHealth delivers full-service high-acuity care to patients across the country by sending clinicians directly to the patient’s own bedside.

  • The company’s tech platform supports diagnostics and treatment, as well as care coordination with health systems and payors.
  • Since being founded in 2013, Dispatch has treated over 1.2M people in 20 states, reportedly resulting in 58% ED avoidance and a 98% patient satisfaction rating.

Medically Home has a similar value proposition, with technology, logistics, and support services that “are unmatched in making hospital-level care possible outside of a hospital’s four walls.”

  • It also boasts an impressive list of health system investors like Cleveland Clinic, Mayo Clinic, and Kaiser Permanente.
  • The financial terms of the agreement weren’t disclosed, but Medically Home appears set to be folded into DispatchHealth when the acquisition closes mid-year 2025.

The combined company – AKA DispatchHealth – will provide in-home care across 50 major metropolitan areas through partnerships with nearly 40 health systems.

  • The move brings both companies’ tech and clinical expertise under one roof, which is expected to open up over 62k bed days and reduce total cost of care by up to 30% over a 30-day period (unclear how much of that is offloading work to family members).
  • The merger also reflects a growing trend toward consolidation in this space, where scale is crucial for reaching sustainable growth, even if it means joining forces to get there.

The clock is ticking. The acquisition arrives as the future of the federal hospital-at-home program hangs in limbo. Congress extended the program just a jew weeks ago, but only for another six months.

The Takeaway

The U.S. population isn’t getting any younger, and aging patients have been vocal about preferring care from the comfort of their own homes. In that context, DispatchHealth’s acquisition of Medically Home makes a lot of sense, and a successful merger could support the case for a long-term extension when the current hospital-at-home waiver expires in September.

Dr. Oz Sheds Light on Potential Priorities at CMS

Posted on by Jason Barry

Dr. Mehmet Oz appears to have passed his Senate testimony with flying colors, and the surgeon-turned-TV-personality’s confirmation as CMS administrator seems all but locked in.

The nearly three hour testimony wandered through a range of topics with a direct impact on digital health, giving us a first look at what might change – or get axed – in the years ahead.

  • Prior auth topped the hit list. The most concrete policy idea that Oz offered was limiting the number of procedures subject to prior auth in Medicare Advantage to 1,000, a steep reduction from ~15,000 today. Oz said the “pre-approval process is expensive and wastes time,” especially when we have AI that can “pretty quickly adjudicate whether you should have to wait even a day to have the medication that will get you out of pain.”
  • AI was a major theme throughout the testimony. Oz plans to use AI to help doctors “optimize care” and focus on their patients, making several references to its ability to augment treatments and cut down on paperwork. He also said “we should be using AI within the agency to identify [fraud] early enough so that we can prevent it.”
  • Medicare Advantage was another big focal point. Oz cited MedPAC research showing that MA is more expensive than traditional Medicare, but attributed much of the cost to upcoding from payors. He promised to hit the problem head-on with an AI hammer.
  • Medicaid was a mixed bag. While Oz said he fully supports the program, he also agreed that spending has gone off the rails since the ACA, and was in favor of implementing work requirements. Oz sidestepped questions about potential cuts by saying “the way you protect Medicaid is by making sure that it’s viable at every level,” which includes having enough practitioners, compensating them fairly, and improving patient access.

The Takeaway

It’s hard to take the other side when a charismatic doctor vows to fix a broken healthcare system, but it’s also tough to tell the difference between empty promises and real reform until action backs it up. Part of that will have to wait until the actual confirmation, but as Oz put it, “part of this is just recognizing there is a new sheriff in town.”

AI Misses the Mark on Detecting Critical Conditions

Posted on by Jason Barry

Most health systems have already begun turning to AI to predict if patient health conditions will deteriorate, but a new study in Nature Communications Medicine suggests that current models aren’t cut out for the task. 

Virginia Tech researchers looked at several popular machine learning models cited in medical literature for predicting patient deterioration, then fed them datasets about the health of patients in ICUs or with cancer.

  • They then created test cases for the models to predict potential health issues and risk scores in the event that patient metrics were changed from the initial dataset.

AI missed the mark. For in-hospital mortality prediction, the models tested using the synthesized cases failed to recognize a staggering 66% of relevant patient injuries.

  • In some instances, the models failed to generate adequate mortality risk scores for every single test case.
  • That’s clearly not great news, especially considering that algorithms that can’t recognize critical patient conditions obviously can’t alert doctors when urgent action is needed.

The study authors point out that it’s extremely important for technology being used in patient care decisions to incorporate medical knowledge, and that “purely data-driven training alone is not sufficient.”

  • Not only did the study unearth “alarming deficiencies” in models being used for in-hospital mortality predictions, but it also turned up similar concerns with models predicting the prognosis of breast and lung cancer over five-year periods.
  • The authors conclude that a significant gap exists between raw data and the complexities of medical reality, so models trained solely on patient data are “grossly insufficient and have many dangerous blind spots.”

The Takeaway

The promise of AI remains just as immense as ever, but studies like this provide constant reminders that we need a diligent approach to adoption – not just for the technology itself but for the lives of the patients it touches. Ensuring that medical knowledge gets incorporated into clinical AI models also seems like a theme that we’re about to start hearing more often.

Hinge Files for Long-Awaited IPO 

Posted on by Jason Barry

When the digital health market needed a hero, Hinge Health answered the call.

Hinge officially filed for its IPO, braving the biggest stock market downturn in recent memory to pull the tech-enabled services category out of a years-long slump.

  • It’s a bold move, but Hinge has the business to back it up. Using a combination of virtual care and AI, Hinge delivers MSK treatment programs with comparable outcomes to traditional physical therapy at a fraction of the cost.
  • Hinge has apparently been able to automate 95% of MSK care delivery, saving its clients (primarily employers and payors) an estimated $2,387 per member per year.

Diving into the S-1, Hinge grew its revenue by 33% to $390M in 2024. It also managed to cut its net loss from $108M down to just $12M, generating 77% gross margins in the process.

  • Hinge reported 532k members and ~200M contracted lives across 2,250 clients, and counts nearly half of the Fortune 500 as clients. 
  • Great stats all around, but a nice soundbite from the S-1 was that “current contracted lives only represent 5% of our total addressable market,” and Hinge is now on the hunt for more growth through commercial plans and Medicare Advantage.

Even with the impressive metrics, Hinge’s last private valuation came in at a rich $6.2B at the height of the pandemic, meaning that it’ll need around a 15X revenue multiple just to match it.

  • It’s not out of the question, but Hims & Hers has been one of the lone bright spots for public digital health companies, and it’s trading at just 5X revenue.

The entire tech-enabled services market feels like it hinges on this IPO, at least if you’ve been following this week’s reaction to the S-1.

  • Hinge is going to be the first health tech startup to go public since Waystar last June, and VCs have been hesitant to invest in the category given the lack of major exits.
  • If Hinge’s debut goes well, it would restore some much-needed confidence in the market, and potentially even kick off a revival in the dormant IPO landscape.

The Takeaway

Hinge is a true disrupter, with an outcomes-driven alternative to traditional physical therapy and a ton of momentum in one of healthcare’s largest markets. We’ll definitely be rooting for them when they ring the bell.

Stress Testing Ambient AI Scribes

Posted on by Jason Barry

Providers are lining up to see if ambient AI can live up to its promise of decreasing burnout while improving the patient experience… and researchers are starting to wonder the same thing.

A new study in JAMA Network Open investigated whether ambient AI scribes actually decrease clinical note burden, following 46 clinicians at the University of Pennsylvania Health System as they used Nuance’s DAX Copilot AI ambient scribe from July to August 2024.

  • Researchers combined EHR data with a clinician survey to determine both quantitatively and qualitatively whether ambient scribes actually make a positive impact.

Here’s what they found. Over the course of the study, ambient scribe use was associated with:

  • 20.4% less time in notes per appointment (from 10.3 to 8.2 minutes)
  • 9.3% greater same-day appointment closure (from 66.2% to 72.4%)
  • 30.0% less after-hours work time per workday (from 50.6 to 35.4 minutes)

It’s tough to argue with the data. Ambient scribing definitely moves the needle on several important metrics, and even the less clear-cut stats still had a positive spin to them.

  • Note length was 20.6% greater with scribing (from 203k to 244k characters/wk)
  • However, the percentage of documentation that was typed by clinicians was 29.6% lower compared to baseline (from 11.2% to 7.9%)

The qualitative feedback told a different story. Even though clinicians reported feeling more engaged during patient conversations, “the need for substantial editing and proofreading of the AI-generated notes, which sometimes offset the time saved” was a recurring theme in the open-ended comments.

Ambient AI received a net promoter score of 0 on a scale of -100 to 100, meaning the clinicians were as likely to not recommend it as they were to recommend it.

  • 13 clinicians would recommend ambient AI to others, 13 wouldn’t recommend it, and 11 didn’t feel strongly either way.

The mixed reviews could mean that the ambient scribe performed better/worse for different users, but it could also mean that some clinicians were more diligent at checking the output.

The Takeaway

The evidence in favor of ambient AI scribes continues to pile up – even if the pajama-time reductions in this study didn’t live up to the promise on the box. Big technology shifts also come with adjustment periods, and this invited commentary did a great job highlighting the “real risk of automation bias” that comes with ambient AI, as well as the liability risk of missing its errors.

HIMSS 2025 Recap, Launches, and Major Announcements

Posted on by Jason Barry

It’s the final day of HIMSS 2025 in Las Vegas, and although the exhibitors are still diligently manning their stations, most of the announcement cards have already been dealt and it’s time to round up the biggest stories from the show.

HIMSS centered around the familiar themes of digital transformation, cybersecurity, artificial intelligence, and workforce development, but the single biggest trend landed at the intersection of all four: agentic AI.

The industry is embracing AI agents everywhere from the bedside to the contact center, and it was amazing to see how quickly last year’s hallucination worries gave way to what feels like a pedal-to-the-metal approach to new AI rollouts. 

You would have been hard pressed to find a dozen booths in the exhibit hall that didn’t mention AI, and the same could be said about the announcements from the show.

HIMSS 2025 major announcements, launches, and partnerships:

  • 1upHealth debuted the latest release of its 1up Platform, which introduces a modern lakehouse architecture designed to scale with healthcare’s growing data needs and improve control over real-time management and analytics. Check out our interview with CEO Andrew Boyd for the full overview.
  • Arcadia is bringing its longitudinal patient data to League’s CX platform to let healthcare orgs deliver individualized health recommendations and activate consumer engagement through AI and behavioral science. CEO Michael Meucci shares all the details.
  • eClinicalWorks can now connect and exchange data with PointClickCare applications in long-term and post-acute care settings to support remote and bedside physician encounters.
  • Elsevier expanded its flagship ClinicalKey AI clinical decision support solution through new workflow integrations with Epic and DrFirst’s iPrescribe platform, not to mention the launch of a dedicated mobile app.
  • Google Cloud rolled out new GenAI capabilities in Vertex AI Search for healthcare, including a multimodal search feature called Visual Q&A that ingests tables, charts, and diagrams to build a more comprehensive view of patient health.
  • InterSystems debuted its IntelliCare AI-powered EHR that includes an AI assistant to enable natural language commands, automatic patient history summarization, real-time note generation, and prepopulated billing codes.
  • Kontakt.io bolstered its Responsive Care Operations platform with Kio Agents, which help prioritize day-to-day management of patient flow, assets, and nurse staff while forecasting potential bottlenecks and dynamically redistributing resources in real-time.
  • Medallion enhanced its automated credentialing and compliance capabilities to support Joint Commission standards with electronic privileging workflow management and automated submission of privileging applications to partner hospitals.
  • Microsoft took the lid off Dragon Copilot, an AI assistant that combines the natural language voice dictation of Dragon Medical One with the ambient listening capabilities of DAX Copilot to support everything from documentation and after-visit summaries to referral letters and clinical evidence summarization.
  • Notable released the next generation of its Flow Builder, which rounds out the solution with a new Builder Assistant for AI-powered workflow creation, intuitive visualizations of data flowing through the automations, and granular role-based access controls.
  • Rush University System for Health expanded its partnership with Suki and will be deploying the AI clinical documentation assistant system-wide, allowing clinicians across 28 specialties to generate patient summaries and simplify coding.
  • RevSpring unveiled SeatMate, an AI assistant that guides customer service reps with intelligent scripting, infuses every conversation with patient insights, and enhances self-service through conversational chat capabilities.
  • Salesforce debuted Agentforce for Health, a library of pre-built agent skills to streamline tasks like benefits verification, clinical trial recruitment, provider search & scheduling, care coordination, and customer service.
  • Surescripts released its 2024 Annual Impact Report, highlighting its Touchless Prior Authorization capabilities that helped patients get medications faster by reducing the average time to approve a prior auth from over an hour to just 34 seconds.
  • symplr launched the first of many AI solutions coming to its symplr Operations Platform, a symplrAI Evidence Analysis chatbot designed to accelerate clinical research and streamline the medical device and technology decision-making process for health plans.
  • Talkdesk revealed its AI Agents for Healthcare, which not only automate common patient and member inquiries, but can also schedule appointments, verify benefits or prior auths, and manage prescription refills in any language.
  • TigerConnect announced the general availability of its TigerConnect Pre-Hospital solution that streamlines a wide range of EMS, ED, and transfer workflows to improve patient throughput and outcomes (think better prep for patient arrival and digitized transfer coordination).
  • Withings published an analysis of 3.4M smart scale users, finding that 38% of people classified as “overweight” and 2% classified as “normal” on the BMI scale actually have an unhealthy amount of fat – based on their body composition analysis – and should seek further screenings (6% of those with an “obese” BMI actually had a healthy body composition and should be considered “healthy”).
  • Wolters Kluwer Health is integrating UpToDate with Microsoft Copilot Studio to deliver patient-specific, evidence-based medical content through Microsoft Dragon Copilot ambient listening and other point of care workflows.
  • Zoom announced the public beta of Zoom Workplace for Clinicians, building on its partnership with Suki to automatically generate visit notes for both virtual and in-person appointments by simply clicking on the ‘Clinical Notes’ icon in the Zoom Workplace app.

We hope that everyone had an awesome time if you made it to Vegas, and welcome all of our new readers that we met at the show. Stay tuned for a deeper dive into some of these announcements next week.

OpenEvidence Closes $75M in Series A Funding

Posted on by Jason Barry

OpenEvidence might be the new kid on the medical chatbot block, but it’s already “the fastest-growing platform for doctors in history,” and $75M of Series A funding just made it the youngest unicorn in healthcare.

Founder Daniel Nadler describes OpenEvidence as an AI copilot, with an experience that feels similar to ChatGPT yet is actually a “very different organism” due to the data it was trained on.

OpenEvidence functions as a specialized medical search engine that helps clinicians make decisions at the point of care, turning natural language queries into structured answers with detailed citations.

  • The model was purpose-built for healthcare by exclusively using training data from strategic partners like the New England Journal of Medicine – no internet forums or Reddit threads in sight.
  • The kicker? It’s available at no cost to verified physicians and generates its revenue through advertising. 

Happy users are their own growth strategy, and OpenEvidence claims that 25% of doctors in the U.S. have already used the product since its launch in 2023. It’s also adding 40k new doctors each month through word-of-mouth referrals and glowing reviews of its ability to:

  • Handle complex case-based prompts
  • Address clinical cases holistically
  • Provide really good references

The 1,000 pound gorilla in this space is Wolters Kluwer and its UpToDate clinical evidence engine. 

  • Although Wolters Kluwer has been inking partnerships with companies like Corti and Abridge to bring new AI capabilities to UpToDate, OpenEvidence is built from the ground up as an AI-first solution.
  • If WoltersKluwer is an encyclopedia, OpenEvidence is ChatGPT, and it’ll be interesting to watch the plays that both sides make as they battle for market share.

The Takeaway

OpenEvidence isn’t a solution in search of a problem, it’s a sleek new tool addressing an immediate need for plenty of providers. It’s rare to see the type of viral adoption that OpenEvidence managed to generate, which is a good reminder that many areas of healthcare change slowly… then all at once.

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