Ben Green, MD

Assuming the chart is accurate, or close. Let's realize that insurance provides no treatment and other than paying the bills does exactly nothing for health. They like to call themselves health plans, so we don't call them bill payers. Then there are many other forms of intermediary that also do not provide any care or health. The system has converted from transactions to financially support caregiving, into caregivers and patients supporting profit taking transactions. This is upside down.

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Here’s your recap of last week’s health IT news 🗞️ Notable partnerships 🤝 • Kaiser Permanente is partnering with Innovaccer to incorporate their population health and AI platform        • MUSC Health adopted Andor Health’s ThinkAndor in its ED to reduce wait times and “leaving without being seen” rates.      • Upperline Health is partnering with Navina to improve clinical workflows and improve the accuracy of patient histories.      • Intermountain Health deployed Nuance Communications DAX Copilot, an AI ambient scribe solution.      • PA Clinical Network is partnering with Guidehealth  to improve outcomes and care quality while improving physician efficiency. Product updates 👩🏼‍💻 • Klara released a new patient intake product for athenahealth users.    • Baton Health released Universal Primary Source, giving users access to hundreds of primary source databases for credentialing.    • InsightRX released InsightRX Apollo, an analytics platform that provides insights on clinical performance.    • Trovo Health launched with a $15 million seed round, offering specialty-specific AI combined with clinical experts to help practices add to their capabilities.    • Quest Diagnostics acquired PathAI’s diagnostic laboratory business (PathAI Diagnostics) to improve Quest’s oncology services.    • GenHealth.ai launched its Automated Prior Authorization platform.    • Veradigm® is partnering with MedEvolve, Inc. to make its suite of products available to Veradigm users.    • CLEW announced availability of a newly FDA-approved patient surveillance platform. Posts we enjoyed 👏 • Eric Topol, MD shared a compelling piece reviewing the state of research on AI in medicine. In short, we’re seeing our first early evidence that AI can reduce mortality as a research endpoint, but large language models are not yet the panacea we’ve been promised. (https://lnkd.in/e6hK-4mr)    • Nikhil Krishnan of Out-Of-Pocket shared a deep dive on Stedi, which converts X12 EDI into JSON-based APIs for healthcare tech developers. (https://lnkd.in/eqS9V5zW) --- Want to stay in the loop? Sign up for the Elion Briefing to get all of the latest healthcare tech news delivered to your inbox 📬 👉 https://bit.ly/49z6AUW

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A whirlwind of activity last week at the America's Physician Groups conference. Lots of solid insights shared by health system leaders. Some notable thoughts: +++ Artificial intelligence is intelligent in different ways: By now, we all know ai has a diverse set of use cases, incorporated in different applications and tools. But there are fundamental differences in how the intelligence itself is brought to life. Examples include: - Predictive AI, used to forecast future outcomes by leveraging historical data. Shout out to UCLA’s CKD/ESRD early intervention protocol (Joycee Berin) and Diagnostic Robotics’ intelligence care post-dicharge journeys (Kira Radinsky) - Protocolized AI, used to automating a user’s administrative load by using a set of detailed, pre-defined rule sets. Thanks to ARC for sharing their experience using Elaborate 's automated outpatient lab summaries (Manish Naik) - Generative AI, used to create new content. Great overview of ambient documentation at MGB as well as Cedars’ Sinai talking through its medical ontology model powering acute triage (Caroline Goldzweig) Across system leaders and experts, there was clear agreement that the first step to implementing intelligence intelligently is defining the ‘jobs to be done’. That way, internal and external stakeholders are clear on what they're solving for when they architect the solution.  +++ Scaling AI takes time and rigorous observation: Market leaders describe a phased pilot approach that allows clinicians to build confidence and system leaders to measure ROI before deploying systemwide. Loved hearing Rebecca Mishuris outline MGB’s novel approach of piloting two solutions against one another, to pressure test implementation, workflow, and value creation. +++ Proving ROI continues to be challenging: Lots of vendors using lots of different metrics to prove value, but the majority of leaders agreed that estimating the ROI of these new tools today is part science, part art. Demonstrating the ROI of the “soft” metrics around provider burnout and retention seemed to be a big opportunity, especially for investment in more efficient primary care and PCP wellbeing. After all, PCPs drive referrals to specialty-level care (and higher reimbursements) for health systems. Appreciated Anurang Revri's overview of how working team setup can also impact ROI estimates. +++ Value-based care = tools + humanity: VBC will require not only implementing tools to support clinical documentation, risk capture, upcoding, etc, but also humanizing interactions to engage patients. Countless examples, but one that made me smile was a depression focused chat bot responding in the following interaction: - Context: post-discharge check in Bot: Hi Freida, how are you feeling today after your surgery?  Patient: I’m having a tough time, am in a lot of pain.  Bot: Well, it can’t be that bad, I’m sure it will get better with a positive mindset!    🤣 🤣 🤣 Can't wait for next go-around!

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Manatt, Phelps & Phillips, LLP's take got me: "CMS is recognizing the role of digitally enabled care in improving access and outcomes." They also propose these new models "present health tech companies with opportunities to target new markets" because of the new/extra funding—such as viewing state Medicaid offices as new partner opportunities, which I've been seeing a lot of talk about recently in my feed. What do you think? I guess being in New Mexico, where almost half of our state is covered by Medicaid, Medicaid and MCOs have been a primary strategic partner/target market for 15+ years, and a somewhat omnipotent source driving most investment and initiatives. ------------------ More about the models: The Transforming Maternal Health (TMaH) model will issue agreements to up to 15 state Medicaid agencies to develop and implement a whole-person approach to pregnancy, childbirth, and postpartum care. The Innovation in Behavioral Health (IBH) model will develop and implement state-administered approaches which integrate behavioral, physical, and social supports to coordinate and manage care for Medicare and Medicaid beneficiaries with moderate-to-severe mental health conditions or substance-use disorders (SUD). I thought to myself, "wait, aren't we already doing that?" But they clarified: through the new models, CMS is encouraging states and providers to invest in technology and supporting infrastructure. ------------------ 🎉 What I'm excited about: Continued support for entities to get connected and the continued case for HIEs to expand their capabilities. Specifically, EHRs, HIEs, and remote patient monitoring (RPM). AND.... 🎉 "Additionally, CMS will support states with implementing data infrastructure to enable collection of Health-Related Social Needs (HRSN) data and referral to support resources." ------------------ 🤯 What I didn't realize: "It is estimated that only 6% of behavioral health facilities and 29% of substance use disorder treatment centers in the U.S. utilize EHRs, whereas nearly 4 in 5 office-based physicians (78%) leverage an EHR platform today 🤯 I'm having a hard time following along with all the new models coming out of CMMI, though 😉 Interesting piece all around, good info.

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Robin Goldsmith thanks so much for having Sameer Berry, MD, MBA on your show to talk about Oshi Health and our innovative care for #digestivehealth conditions. Such a great conversation around the challenges in #gastroenterology and how new care models like ours address them in ways that are a win for all stakeholders. #valuebasedcare #accountablecare #wholepersoncare

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In a recent report, only ~20% of healthcare executives claimed that they fully trust their data. At Fullsteam Health, we think that % is way too low. We're committed to reversing this trend with our automated data curation platform which was initially developed at Duke to address this very issue and allow for fast access to data that is needed and that has been cleaned, grouped, and continually monitored. https://lnkd.in/epWvPTDV

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There’s a category we believe is getting too little attention when it comes to AI in healthcare: AI Clinical Documentation Integrity (CDI) While AI ambient scribes and autonomous medical coding solutions have gotten most of the headlines, we’d argue AI CDI is equally impactful when it comes to quality care and accurate billing. For those not familiar, CDI ensures that clinical documentation accurately reflects the patient’s medical condition and the provided care. Historically, CDI was a manual slog, with dedicated CDI specialists, nurses, and physicians painstakingly reviewing patient charts to ensure documentation supported the care delivered. Today, AI is reshaping this landscape. While it’s still early days, we’re seeing three primary approaches to applying AI when it comes to CDI: 1️⃣ CDI + ambient scribing—an AI ambient scribe and AI CDI assistant operate simultaneously, generating comprehensive notes and surfacing codes for physicians to review at the point of care. (Example: Ambience Healthcare’s AutoCDI) 2️⃣ CDI via real-time diagnosis support—diagnoses are suggested at the point of care based on clinical data in the EHR, with auto-generated documentation and audit trails. (Example: Regard) 3️⃣ CDI via an AI-driven post-coding / pre-billing review—the entire patient record is ingested and analyzed against what is coded, surfacing suggestions for revenue and quality opportunities. (Example: SmarterDx) To date, AI in healthcare has focused primarily on administrative use cases. With the increasing adoption of AI CDI solutions, we’re now taking a step closer to clinical workflows. As clinicians get used to AI-suggested diagnoses in the CDI context, it will be interesting to see if this increases their comfort with AI playing a role in clinical care. Here's our working list of AI CDI vendors. Anyone else we should add? • Ambience Healthcare • Brellium • Iodine Software • Regard • Semantic Health • SmarterDx   

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It’s hard to believe its over 2 years since we went live with the worlds first fully cloud native ecosystem in Amazon Web Services (AWS), more than 3 years since we started the implementation and more than 5 years since beginning our journey too getting health systems out of the data center. How far we’ve come. And it’s STILL getting CHEAPER and BETTER by the day!!! Have a listen to the discussion!

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Digital Front Door is a term I would love to see our industry stop using. It's long past the time for our industry to recognize that we need to BE digital, not just have a digital option - because that's what people expect from us. Limiting digital to a front door also perpetuates one of the biggest issues we have in healthcare today; requiring people to already know they have an issue and knowing where to go to find care. There is no single off the shelf solution to move us from a sick care system to a health care system, but there is an open standards architecture that we should ALL adopt so that we can innovate faster, modernize experiences and bring all kinds of companies together to create a more intuitive and proactive consumer experience.

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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

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Blue Health Intelligence, a data analytics and software company, undertook an evaluation of almost 170,000 unique GLP-1 users for weight loss, notes less than half of those prescribed stay on the medication for 12 weeks or more. Younger adults were less likely to continue the drug, whereas those who were prescribed the medication by an endocrinologist or obesity medicine specialist were more likely to continue for longer. Indeed, this data states 30% of patients dropped out of treatment after the first four weeks, and 58% at 12 weeks. Those who dropped out are unlikely to achieve clinically meaningful weight loss.  The likelihood of continuance was further exacerbated for those with health inequities or who lived in underserved health regions. The data comes from Blue Cross Blue Shield Association members participating in Plans that provided coverage of these products, from 2014 through to end of 2023. Razia Hashmi, vice president for clinical affairs at Blue Cross Blue Shield wants to ‘…paint a clearer picture of what makes somebody successful.’ The missing piece here is why the patients stopped – side effects, failure to achieve initial weight loss, stigma and discrimination, or coverage issues related to cost and access. My longtime friend, colleague and bariatric surgeon at Stanford University, Dr. Dan Azagury rightly states ‘…The goal is for patients to stay on this for a significant amount of time. Most likely… beyond 12 weeks.’ https://lnkd.in/ediQskQx

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🆕 Episode: Continuing our recap of HIMSS 24, host Angelo Kastroulis sat down with Nicholas Stepro of Arcadia. In this clip, they touch on the topics of value-based care, social determinants, and AI in the healthcare setting. You can catch the full podcast with this link 👇 or on any major platform. https://lnkd.in/eYt2suhf #healthcare #data #analytics #sdoh #ai #himss24

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📡 What’s ambient signal, and how can it help address social determinants of health? Arcadia’s Chief Product and Technology Officer, Nicholas Stepro, explains in this episode of the Counting Sand Podcast. 🎙️ Give it a listen to learn how: ➡ Data and analytics provide an understanding of performance and identify areas for improvement in healthcare ➡ Artificial intelligence can be used to enhance healthcare efficiency and effectiveness ➡ Trust and transparency can lead to the adoption of AI in healthcare

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#telemedicine, #Walmart Health Instead of viewing telemedicine as just a convenient, stand-alone option, we should integrate it into multi-channel care models that blend in-person with asynchronous (e.g., messaging, RPM) and synchronous (e.g., chat, phone, video) virtual care.

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I want to thank @HealthAIInsights for publishing my idea on how AI can assist in everyday oncology clinical workflow. I joined Watson Health nearly ten years ago with the desire to improve the daily experience for patients and oncologists alike. With the shortage of oncologists becoming an increasingly critical issue, it is imperative that we develop safe, efficient and effective tools to assist in everyday patient care. #AI #cancercare #oncologyworkflow #healthcareai #healthaiinsights

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🔍 Reducing Costs and Enhancing Safety in Healthcare 🔍 Patient misidentification can cause a cascade of problems, from misdiagnosis to administrative chaos. Dr. Sean Kelly, our Chief Medical Officer, talks about the significant impact this issue can have on healthcare. Imprivata is dedicated to providing solutions that ensure accurate patient identification and improve safety across the board. Share the importance of addressing patient misidentification in healthcare. Find out more about our solutions: https://ow.ly/Um9F30sEhAL #PatientSafety #HealthcareInnovation #Imprivata #PatientIdentification #Healthcare

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I’ve seen a lot of buzz about how AI will change the nature of patient-provider relationships — and is this a good thing or a bad thing? Here’s the thing. AI should EMPOWER the patient-provider relationship — and support the development of trust between patients and providers. Example 👇 At the bedside, clinicians can partner with their patients face-to-face. But even then, various factors present significant challenges to cultivating trust. For instance, one survey conducted by PatientPoint found that half of Americans are afraid to ask their healthcare providers questions about conditions and symptoms. So how do healthcare professionals extend these relationships beyond the hospital? Chatbots can seem sterile in their automated responses, but the right AI-backed technology can use natural language processing (NLP) to communicate with patients at a human level. AI can help interpret and respond to patient questions and concerns, and flag the right care team member when more assistance is needed. AI should empower a trusting patient-provider relationship. Not replace it.

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Over the past several months, Naomi Goez and I did a deep dive into opportunities for innovation within health systems. Throughout that time, we had conversations with innovation executives across four of the top healthcare systems in the U.S. including Mayo Clinic Ventures, Hackensack Meridian Health, Cone Health Ventures, and University Hospitals Ventures to understand current strategies and priorities in order to hone in on our investment thesis. Our goal was to arm health tech founders with the inside perspective on the critical investment areas for US hospitals to help navigate towards product-market fit and solve the industry's most pressing challenges. Health tech is a core thesis area for us at Forum Ventures, as we think technology will play a major factor in improving patient outcomes, providing more accessible care and driving better financial results for health systems. We've already made quite a few health tech investments over the last 10 years and plan to make many more over the coming years. Links to download the report, check out the market map, and submit your company are all in the comments. Thank you to our contributing experts Shai Ran Sapir, Technology Development Manager at Mayo Clinic Ventures, Sandra Powell-Elliott, Chief Innovation and Commercialization Officer at Hackensack Meridian Health, David Heenan, Managing Director at Cone Health Ventures, and Matthew Zenker, Director of Deal Flow and Investments at University Hospitals Ventures. #healthcare #innovation #healthtech #earlystage #healthtechfounders #healthcarestartups

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