Debbie K. Chen, PhD

Big healthcare AI news yesterday as Tempus AI received the first-ever CPT code for an algorithm-only analysis of previously-sequenced, laboratory developed test transcriptomic data. TLDR: AI molecular phenotyping has a new business model. The PurISTSM test uses RNA profiling to identify molecular subtypes in patients with advanced pancreatic ductal adenocarcinoma, which may inform first-line therapy selection and management. While I'm skeptical that payer balance sheets are going to solve the "who pays for healthcare AI" problem, the reimbursement pipes for clinical AI are maturing. I am surprised to see more progress for usage-based vs. performance-based models given the many challenges with FFS economics. It will be interesting to see how payers assess the "medical necessity" and therefore reimbursability of clinical AI as these models come to market. https://t.co/eLe18SmihV

421

9 Comments

#BiomedTech #Startups #Funding Biotech Funding Surge: Top Startups Raise $2.9B in Q1 2024” -Record Funding: The top 20 healthcare-focused biotech companies collectively raised $2.9 billion in Q1 2024, marking a 161% increase compared to the previous year. -Market Confidence: Investors are making more confident bets on the market viability of promising healthcare biotechnology firms. -Focus Areas: Funding recipients include companies specializing in precision oncology, AI-driven drug discovery, cell and gene therapies, and novel approaches to treating autoimmune disorders. Alumis Alumis (formerly Esker Therapeutics) secured $529M in cumulative funding, focusing on precision immunology and targeted treatments for autoimmune diseases. Freenome Freenome, a leader in early cancer detection, raised $1.35B in total funding for its multiomics screening platform. #BiotechFunding #HealthcareInnovation #PrecisionMedicine #HealthTech #LifeSciences #InvestmentNews #HealthcareStartups #InnovationFunding Ahmed-digital doc- Otokiti MD, MBA, MPH Alister Martin Philippe GERWILL Umer Khan M. Karim Beguir Harvey Castro, MD, MBA. Gabriella Marcelja

3

What are some of the best examples of how AI is helping tackle and improve patient care? How is AI impacting patients in real time? These were some of the questions we tackled in a wide-ranging panel discussion at the recent Fortune Brainstorm Health conference. I came away inspired by the knowledge that we are actively deploying the technology in a multitude of ways, and as it evolves, its impact will only continue to grow. In a discussion moderated by Fortune’s senior writer Erika Fry, several of us shared insights into how it’s being utilized for precision care in women’s health, to assist clinicians with patient note-taking, in medical devices that deliver therapeutics, in assessing mental health, and in Carrum’s case, how it enables rigorous provider quality evaluations and in identifying patients at risk for chronic health issues even before they’re aware of it. # My take is that we can harness AI for virtually every component of patient care, but the human element is still key for the critical context we need to make decisions, and this is where care concierges who pull all the pieces together and steer the patients matter the most. AI has the potential to dramatically enhance the care concierge team's performance and help them serve patients more effectively. # Second, the challenge with healthcare claims data is that it’s not a clean set like it is in other industries like financial services. So cleaning up claims data is a project in itself. With patients facing critical health issues, weaving data into the mix needs to be done with care so it truly enhances the patient experience. We use AI to predict which members in a given population are on a path to an acute care event in the near future. This is where I see it truly making a difference - until now, health care has been sick care. But with sophisticated data analysis, we can upend that so health care is preventative care. Plus, data we currently generate from handling thousands of patients going through surgery and cancer care also informs all the potential ways to help future patients avoid pitfalls and navigate their care better. #fortunehealth #patientcentricai #patientexperience

48

2 Comments

Here’s your recap of last week’s health IT news 🗞️ 👇 🤖 AI Products • Emergency Services, Inc. + Augmedix Go ED: The emergency medicine group adopted the new ED-specific AI ambient scribe solution.    • Color + OpenAI: The cancer care tech company partnered with the GenAI giant to build a AI clinical decision support copilot.    • AKASA Medical Coding: The AI RCM vendor known for its AI prior auth tool AKASA Authorization Advisor released a new GenAI medical coding solution.    • Humata Health: The AI prior auth for providers vendor closed a $25M funding round led by healthcare org-backed funds The Blue Venture Fund and LRVHealth.    • Wellsheet + Concord Hospital Health System: The AI-enabled Smart EHR UI solution announced a client-reported 16.3% reduction in length of stay and 40% decrease in time spent in the EHR via its partnership with Concord Health, as well as the release of its new LLM-generated handoff summary feature. 🍎 VBC • BSIM Healthcare Services + Innovaccer: The healthcare provider—embarking on its first VBC contract—adopted the pop health data platform for analytics. 🩼 Durable Medical Equipment • Parachute Health: The DME e-prescribing and ordering solution released an update that integrates prior authorization. ⚕️Clinical Staffing • Matchwell + Indiana Hospital Association: The clinical staffing service partnered with the hospital member org to create the first state-wide resource pool for temp staffing. 🧑‍💻 Virtual and At-Home Care • Deaconess Health System + KeyCare: The Indiana-based health system adopted the Epic-based virtual care provider for around-the-clock virtual urgent care.    • UC Davis Health + Current Health: The health system launched a new RPM program for high blood pressure in partnership with Best Buy Health’s care-at-home platform. 🧠 Food for Thought: We came across a couple of good resources this past week on the current state of healthcare data information exchange: • This article in Health Affairs from Deven McGraw and Tina Grande provides a comprehensive overview of some of the patient health data abuses we've seen come to light in recent months, as well as a number of policy recommendations to improve the health information exchange landscape for all participants. https://lnkd.in/e_GEQ-JJ  (h/t Alya Sulaiman)    • This episode of Health Gorilla's InteropTalk gives a helpful update on the current state of affairs, with a particular focus on the state of trust across the health data exchange community and how the definition of "Treatment" may evolve. https://lnkd.in/e96AJG-5 (h/t Brendan Keeler) --- Reminder: you can sign up for the Elion Briefing to get the latest healthcare tech news delivered to your inbox each week 📬 👉 https://lnkd.in/e2UJ3ckP

35

2 Comments

AI has made good design more important than ever in healthcare. Why? Model performance alone doesn't guarantee clinical or financial value. A model can deliver a robust insight/output (accurate, reliable, complete, etc.), but clinician-users may struggle to use or integrate it in a real-world setting. As healthcare AI systems become compound machines, these design challenges amplify. Here are two simple examples: • AI systems that do not integrate seamlessly into EHRs, PACS, or pathology viewers may drive differential rates of utilization/adoption across sites, privileging some patients to a given algorithm without an underlying clinical rationale. • Imagine a model recommending a "next best step in care" that is not provided at a given hospital (e.g., due to lacking resources or infrastructure). Contextual and human factors can have a greater influence on whether the value of an AI intervention is realized, even when in silico model performance is compelling. There are two near-term opportunities here: 1) Healthcare AI model benchmarking should encompass "end-to-end systems," capturing nuances around system design, user experience, workflow integration, and ease of adoption. 2) It's time for AI-first design in healthcare – made possible by revisiting the unique capabilities of AI systems and their emergent behaviors to interrogate what new user experiences are possible. What are your favorite examples of AI-first design? #healthcare #ai #artificialintelligence #generativeai

60

7 Comments

Digital Health Wire has the news today on K Health's amazing momentum as the company is building on the debut of its AI Knowledge Agent with the close of $50M in equity funding led by Claure Group. K Health is on a mission to provide access to high-quality #medicalcare at scale by using AI to turn patient smartphones into the first stop along their care journey. The company's clinical-grade #AI for #primarycare takes patients through a personalized chat to walk through their symptoms, develops an assessment grounded in the #EHR, then delivers insights to providers to inform their diagnoses and treatments. This allows providers to practice at the top of their license and engage with their patients instead of spending valuable time manually piecing together relevant information. Digital Health Wire had the exclusive news on K’s AI Knowledge Agent when it was unveiled. This breakthrough tech is composed of an array of LLMs boosted by K Health’s own advanced algorithms, with key differentiators from standard AI applications. Congratulations Allon Bloch, Ran Shaul, Ethan Fischer, and the K Health team on this funding, which will be used to fuel more health system partnerships and continue sharpening K Health's first-of-its-kind AI, which should in turn allow it to make a compelling ROI case. https://lnkd.in/gvcyaFbU #digitalhealth #KHealth #AIinHealthcare #artificialintelligence #

16

1 Comment

Less than two weeks until #Synbiobeta2024! Find Matterworks at booth 416 in the Startup Pavilion, catch a Lightning Talk from CEO Jack (J.M.) Geremia, PhD on the main stage, and check out our digital poster. Additional details below. #syntheticbiology #machinelearning #artificialintelligence

8

As the discourse shifts from models to compound AI systems / agents, we need better AI benchmarks to evaluate multi-modal and multi-step task performance, especially in healthcare and life sciences. When we wrote the first paper demonstrating ChatGPT's performance on the USMLE, we chose the US Medical Licensing Exam as a benchmark for accessibility, speed, and ease. This benchmark was never intended to represent AI model performance on real-world clinical tasks. Today, I still see so many research teams and startups using benchmarks (like the USMLE) that are ill-fitted for assessing the true clinical or scientific performance and utility of the models they are developing for real-world contexts. Benchmark development may be seen as a "less sexy" area of research, but it is of paramount importance. Years after the rise of the transformer, we still lack adequate benchmarks for so many single-step tasks in biomedicine. With compound AI systems (i.e., architectures that integrate multiple AI models to perform complex tasks) emerging, we need new benchmarks for agentic behaviors. I'd argue that developing an agent with novel capabilities without at least proposing a companion benchmark (if an industry standard does not yet exist) may hinder the adoption of said agent, especially for high-stakes workflows. Designing more benchmarks that capture/simulate real-world clinical and scientific workflows will help us mitigate the major discrepancies observed between in silico and in vivo performance and better support safe + effective deployment of AI in biomedicine. There are already brilliant people focused here, and we need more. DMs are open if you're researching or working in this area of multi-step/multi-modal benchmarking in healthcare and life sciences! #healthcare #ai #artificialintelligence #generativeai

100

18 Comments

The Power of Data in Advancing Health Equity Data isn't just numbers—it's a roadmap to better health for all. By employing tools like surveys, electronic health records, and GIS, we can uncover deep insights into health disparities that affect marginalized communities. 🔍 Through meticulous data collection and analysis, we identify the gaps in healthcare access and outcomes. This critical information drives targeted policies, ensuring resources reach those who need them most. Let's commit to using data to forge pathways toward equitable health solutions. Join us in transforming insights into action. Together, we can create a healthier, more equitable future. #HealthEquity #DataDriven #PolicyChange #SocialGood

1

#Niche-focused #ventures in #HealthTech, such as those #targeting #underserved areas or #specific health conditions, offer several benefits. They can address gaps in the #healthcare system, provide specialized care, and #potentially integrate into broader #ecosystems for comprehensive healthcare solutions. For example, #JVEDTECHMedovation, could explore #partnerships with #niche #HealthTech startups to enhance offerings in healthcare #innovation.

1

Why I go to work everyday? Because it's not just a hype. Because AI can make for better diagnoses and a healthier world. Motivating to read from experts like Gaurav Singal, MD in Los Angeles Times about their view on the power of accurate diagnoses and the last bottleneck before breakthrough: subsidizing and financing broad clinical adoption. "AI should complement, rather than replace, the human expertise that already saves so many lives. The future of medical diagnosis doesn’t mean handing over the keys to AI but, rather, making use of what it can do that we can’t. This could be a special moment for diagnosis, if we invest enough and do it right." Proud to say we're AI diagnostics trailblazers at mediaire! Link to the full article below Henrik Michaely Guido Gleinser Andreas Lemke Marco Le Donne Carina Kaltenbach Cristian Stollberg Jörg Döpfert #AI #aidiagnostics #radiology #youandAI #medtech #deeptech #deeplearning

24

Halle Tecco, MPH, MBA it was really great to talk to you, Michael Esquivel and Michael Matly M.D. on Closing Time, and glad the JD didn't disqualify me (!). Thanks for the kind words and your optimism about Scene Health, our team was really excited to be featured on the pod. I agree that the digital graveyard of failed #medicationadherence solutions is growing and adoption and evidence have been major barriers. At the patient level the problem is going to be one of many things so your solution has to cover several issues (technique, behavior, confusion, etc). One cool thing about #medicaid and #publichealth is that cost is not one of those problems, as meds are covered! A lot of us Scene Health listen to Closing Time every week so keep it going...

12

1 Comment

Back with another deep dive: AI Medical Coding 🏥 👩🏽‍💻 To put it mildly, medical coding is a huge pain point. It’s expensive, inefficient, and error-prone, not to mention challenging to staff with high team member turnover. Over the last five years, fully autonomous medical coding solutions have emerged, promising to address many of these pain points. The idea is simple (but not easy): take the medical chart, fully code it leveraging several types of AI (e.g., NLP, machine learning, and deep learning), and send it directly to billing without human involvement. Recently, the technology has progressed from handling straightforward encounters in high-volume specialties (e.g., radiology and pathology) to tackling more complex visits, such as emergency medicine. However some areas, like inpatient facility coding, remain out of reach. Evaluating solutions in this space can be tricky. Key criteria to consider include: ↳ Breadth of coverage across specialties and code types ↳ Coding accuracy and automation rates (but be sure to define automation clearly!) ↳ Support quality and responsiveness ↳ Coding auditability and transparency ↳ Pricing (obviously) Here's our working list of AI Medical Coding vendors. Anyone else we should add? • Aidéo Technologies • Arintra • CodaMetrix • CorroHealth • Fathom • Maverick Medical AI • Nym • Phare Health • RapidClaims.ai • Synaptec Health

115

8 Comments

Today, Karoo Health is excited to announce the platform launch and 2024 roadmap for Kohere.ai, developed by industry-leading Product and Engineering leadership, our proprietary cloud-based platform that augments Karoo Health's proven model of care (MoC) for cardiovascular healthcare providers, payers, and patients. Contrary to many other VBC companies, which sunk enormous resources into building software and then tried to retrofit a care model around it, we built a value-based MoC that has already delivered results, and then developed Kohere.ai, cutting-edge, AI-enabled technology to amplify its strengths. Karoo Health continues to further a new paradigm in cardiovascular care, through the combination of our MoC, which has already shown industry-leading results, and Kohere.ai, to further supercharge these outcomes, for the benefit of our patients, and cardiologist, payer and other at-risk entity partners. Today, the future became significantly brighter for cardiovascular care! #valuebasedcare #cardiology https://lnkd.in/dx9eJJPd

81

13 Comments

Jeremy Knibbs and I caught up with Paul Wilder Bri Buch and Gurpreet (G.P.) Singh for a chat yesterday as we are watching the US interoperability journey with interest post the 21st Century Cures Act. We had the pleasure of Paul joining us at our Wild Health Cloud Summit in Sydney in 2022 for an armchair chat about what happens when you legislate to share health data using a stick and not a carrot. We were curious to see how things were tracking. CommonWell Health Alliance recently partnered with ELLKAY a nationwide leader in healthcare connectivity to support data exchange to 200 million patients across a network of 34 000 provider organisations in preparation for the next stage of their interoperability journey (TEFCA) the Trusted Exchange Framework and Common Agreement. The numbers seem mind boggling to us in Australia. Whilst Australia's population is a fraction of the US, we have not yet cracked the interoperability nut despite throwing billions $$ at the problem so we thought we would take a deeper dive on the US journey and our own as one of the themes at our WildHealth Summit in Melbourne on October 22nd. The program will be live next week and it’s one of our best yet! ( Watch this space!) As we can see from the Epic versus Particle dispute there is a lot we need to be across on our own journey to interoperability and a lot we can learn to avoid the same scars. #interoperability #datasharing #connectedcare

16

1 Comment

Ideally, we map #openEHR to #FHIR profiles and technically address the data capture and storage issue. Marrying the two could potentially address much of the profile proliferation issue that has yet to be solved. If we don't, what's the alternative for capturing the context and meaning of the data? Create yet another standard that must be mapped to FHIR, C-CDA, and HL7v2? There would have to be compelling reasons to do this to offset the unnecessary complexity and usability issues that would result. #StopTheMaddness #CrisisOfDesign

7

1 Comment

Product Positioning is often confused for Value Proposition and while some of the components overlap, both are necessary for a bulletproof go-to-market strategy. Check out the graphic below and work clockwise around the hive to ask yourself key questions about launching the next medical device in your portfolio👇🏼 Interested in learning more?  Let’s chat! Book here 👉🏼 https://lnkd.in/g92YA9WK _____ P.S. Enjoying my content? ⚕️Follow me for more tips on medical device commercialization and repost to share with your network. #medtech #gotomarket #medicaldevices #healthcareinnovation

12

2 Comments

My key takeaways from 3 days of learning with Lasa Health during the National Science Foundation (NSF) Innovation Corps kickoff: ✅ A strong #valueproposition is crucial for selling your #healthtech product. Your ideal target customer doesn’t really care about the technical details of your product: they want to hear about the outcomes they can achieve by using it. 😫 Your product’s value prop must address key customer pain points. Focus on critical problems that lack existing solutions: this will make your solution irresistible to prospective clients. 😵‍💫 Don’t marry your ideas or your tech. If your current solution doesn’t resonate with your ideal customers, be ready to pivot and adapt based on customer feedback. 👂🏾Never assume you know what your customer is thinking. No matter how well you think you know what they are going to say, they’ll often surprise you. Listen carefully and avoid making assumptions. (Fellow #clinicians: does any of that #business jargon sound oddly familiar to you? That’s because #healthcareproviders think like this all day, every day. We listen, pivot, and focus on outcomes.) #femtech founders, innovators, and teams: this is your reminder to stay laser-focused on the outcomes that matter to your future clients. If you build it, they won’t just come: you have to show them why you’ll make their work better, faster, stronger. 💪🏽 #clinicalconsultant #womenshealth #lgbtqhealth #startup #medicalinnovation #consulting #mentor ~~~~~~~~~~~~~~~~~~~~~~~~~~ Hey there! I’m Dr. Caitlyn Tivy, a clinical consultant and medical writer for women’s and LGBTQ+ health companies. I help femtech and queer health organizations develop scientifically accurate information and products. Ready to take your femtech or queer health company to the next level? Let’s connect! ♀ 🏳️‍🌈

16

6 Comments