Robbie Hughes

Forget fragmented Tech - your siloed care teams are often the real barrier to effective Digital Health implementations. Whenever health systems consider a new Digital Health solution, so much time is spent discussing how it integrates with the EHR. You know what’s awfully UNDERDISCUSSED? Understanding every possible clinical or administrative stakeholder that should be aware of the Tech and how their involvement in it - even if it’s as small as being a verbal advocate for it with patients - can have a huge impact on patient adoption. It’s great to have engaged Champions, but that alone doesn’t lead to massive success. It takes a village of engaged, integrated staff. Take a platform like SeamlessMD which navigates patients across an entire continuum of care - e.g. from pre-op preparation through post-op recovery. This means patients probably should learn about the digital tool in an outpatient surgical clinic, hear about it again at a pre-op assessment center at the hospital, hear about it again during their in-patient stay and then again at discharge - or even shortly after. Of course, we’ve all seen cases where that doesn’t happen. If you only have engaged Champions but poor awareness and engagement with the rest of the staff, you’ll get patients telling you stuff like this: → “I loved the tool, but it seemed like no one in the hospital knew about it.” → “The patient in the bed next to me had the same surgery, but he told me he never got this amazing App like I did.” These are huge missed opportunities. Yes it means that to implement Digital Health effectively, you need to: → Map out every possible stakeholder who could not only be affected by the Tech, but can also AFFECT the Tech’s success → Educate staff up and down the health system. Get them pumped. Communicate the value of the Tech to them and their patients. → Invest in the basics. Put posters on the walls. Get laminated cards at the nursing stations and in the clinics. Yes that means stepping outside your comfort zone and engaging with other teams that you don’t normally engage with. Everyone in Healthcare talks about integrating Tech. Not enough people talk about integrating the staff around the Tech initiative. But if you don’t put effort into that… you can’t be surprised when adoption and engagement isn’t as high as you want it to be. P.S. SeamlessMD provides hospitals and health systems with an EHR-integrated platform to digitally guide patients through care journeys (e.g. pre/post-surgery, oncology, chronic care, etc.). Even better, we provide a proven playbook and services team that shows you how to integrate your staff’s approach to drive high patient adoption and engagement. Backed by 40+ studies/evaluations showing reductions in length of stay, readmissions, mortality and costs. Give us a shout if you’re ready to fully integrate care around your patients!

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FHIR is new. Healthcare data is old. One of the key messages from my talk to business leaders at last week’s DevDays was the importance of building the right team for your FHIR project. Who needs to be on the team? - FHIR expertise - Terminology expertise - Clinical domain expertise - Clinical workflow expertise - Business domain expertise - Legal, privacy and compliance expertise I hesitated around including this slide. After all, why should FHIR be different to any other healthcare data project? Surely you need the same expertise? You do. But too often this message gets lost. FHIR is often brought into an organization as new technology, as part of a new project with new data flows and requirements. A side effect of all this newness is that new teams of devs, analysts, product and UX people are often brought in. People without previous healthcare data experience. Picture everything that can go wrong in this scenario and you won’t be far off the reality. What do I mean by “on the team”? I mean involved on a daily or weekly basis. Clinical and terminology experts working alongside devs as they implement FHIR. Legal and privacy experts weighing in as early architectural decisions are made. Business domain experts making sure the wider product and organization expectations are understood and met. If your organization’s definition of “on the team” is a demo day every 3 or 6 months, you might as well throw in the towel right now. FHIR may be different, but it’s not that different. Build the right team from the start and let them do their jobs.

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Is Healthcare’s Ambient AI About to Become Another Slack vs. Teams Moment? Microsoft just announced Dragon Copilot, an ambient AI-powered scribe and agent for healthcare (see MS article for in comments). With this launch, they’re not just entering the market - they’re bundling it into their vast healthcare ecosystem, a move that could redefine the entire landscape. Slack, one of the OGs in product led growth and bottom up adoption was the first mover in the team workspace market, beloved by early adopters as it's an excellent product. But Microsoft bundled Teams with Office 365, and overnight, distribution was solved. The result? Slack’s growth slowed, and Teams skyrocketed. Could the same thing happen with ambient AI scribes in healthcare? Companies like Abridge, Heidi Health and many others have spent years perfecting ambient AI documentation. But now, Microsoft can leverage its deep integrations into healthcare IT—hospitals already using Teams, Azure, and Epic integrations will be able to turn on Dragon Copilot with minimal friction. No extra vendor contracts. No separate onboarding, etc Here’s what happened in the Slack vs. Teams battle: 📊 MS Teams vs. Slack DAU Growth Key Takeaways: 🚀 Does distribution always win? - Microsoft’s ability to bundle features into existing contracts gives them a near-instant user base. ⚖️ The Innovator’s Dilemma. First movers create new markets, but distribution giants often dominate them later. In saying this, we use Slack on a daily basis, love it and rarely use teams. I'd like to hope the best "clinician-centric" products win out here but time and time again, especially in healthcare, it often doesn't happen that way. Super interesting space!

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Today's Budget unveiled £300m of tech investment to improve patient services. It's hugely welcome news, but it's only addressing one side of the coin... 🪙 Clinical staff are in desperate need of effective, interoperable, well-implemented tech. BUT, it's important to also bang the drum for investment in technology which supports those working 'behind the scenes'. From rota coordinators to finance managers, these vital colleagues also need better tools and smarter systems. We must ensure innovation doesn't get siloed but instead improves the lives of *everyone* working in the NHS. https://lnkd.in/etTmsYqY

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As we enter the post-EHR era, it’s worth understanding who won the first battle: Epic, the leading U.S. EHR founded by Judith Faulkner. These insights are based on the recent "Acquired podcast", covering Epic’s story. Here are the key takeaways: 1️⃣𝐉𝐮𝐝𝐢𝐭𝐡 𝐅𝐚𝐮𝐥𝐤𝐧𝐞𝐫: 𝐭𝐡𝐞 #𝟏 𝐟𝐞𝐦𝐚𝐥𝐞 𝐞𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫 Judith Faulkner may not be widely known, but she deserves a seat alongside Steve Jobs and Bill Gates. A generational talent (she learned Fortran in a week), Faulkner built the world’s leading #EHR system from scratch.  2️⃣ 𝐊𝐚𝐢𝐬𝐞𝐫 𝐏𝐞𝐫𝐦𝐚𝐧𝐞𝐧𝐭𝐞 𝐢𝐧 𝟐𝟎𝟎𝟑: 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐦𝐨𝐦𝐞𝐧𝐭 𝐟𝐨𝐫 𝐄𝐩𝐢𝐜 KP, the largest hospital system in the U.S., first tried to build its own EHR, and failed. IBM won the initial KP tender, then failed too. In the final round, #Epic and Cerner were the last two standing. The night before the pitch, Epic president Carl Dvorak flew to California, saw the plan, and said, “No, we need an Excel model showing KP’s daily transaction flow and how our system can handle it with zero downtime.” That’s how Epic won. 3️⃣ 𝐖𝐡𝐲 𝐢𝐬 𝐄𝐩𝐢𝐜 𝐭𝐡𝐞 𝐧𝐮𝐦𝐛𝐞𝐫 𝟏? 𝐓𝐰𝐨 𝐦𝐚𝐢𝐧 𝐫𝐞𝐚𝐬𝐨𝐧𝐬: 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 Epic’s reliability comes from its single, unified database (Chronicles), unlike competitors who patched systems together through mergers. When Epic gives a timeline and budget, it usually delivers. Its clinical and billing systems run on the same codebase, ensuring nothing gets lost between departments. For #hospitals seeking seamless, end-to-end operations and financial stability, Epic’s architecture is hard to beat. ⚠️ Now, as we enter 2025, the post-EHR era is beginning, and we’re at a crossroads, with several open questions: ➡️ 𝐒𝐢𝐧𝐠𝐥𝐞 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐬𝐲𝐬𝐭𝐞𝐦 𝐯𝐬. 𝐛𝐞𝐬𝐭-𝐨𝐟-𝐛𝐫𝐞𝐞𝐝? Other industries have seen value chains unbundled and then re-bundled through platformization. Waystar (RCM) is gaining traction in the U.S. by excelling in its niche. Can it expand and re-bundle beyond RCM? ➡️ 𝐖𝐢𝐥𝐥 𝐡𝐨𝐬𝐩𝐢𝐭𝐚𝐥𝐬 𝐝𝐢𝐬𝐚𝐩𝐩𝐞𝐚𝐫? The hospital business model is broken and likely to be unbundled. What does that mean for the healthcare tech stack? ➡️ 𝐖𝐢𝐥𝐥 𝐩𝐫𝐨𝐯𝐢𝐝𝐞𝐫𝐬 𝐫𝐞𝐠𝐚𝐢𝐧 𝐜𝐨𝐧𝐭𝐫𝐨𝐥? Large hospitals tried to build / control their own EMR/EHR during the early EHR era (e.g., KP) and failed. Will they succeed in the post-EHR era? ➡️ 𝐖𝐢𝐥𝐥 𝐄𝐩𝐢𝐜’𝐬 𝐜𝐮𝐥𝐭𝐮𝐫𝐞 𝐫𝐞𝐦𝐚𝐢𝐧 𝐚𝐧 𝐚𝐬𝐬𝐞𝐭? Epic enforces strict protocols, no remote work, and near-robotic employee behavior. This worked over the last 20 years. But will it hold up in a future that demands agility and creativity? ➡️ 𝐄𝐩𝐢𝐜 𝐝𝐢𝐠𝐢𝐭𝐢𝐳𝐞𝐝 𝐜𝐚𝐫𝐞. 𝐖𝐢𝐥𝐥 𝐀𝐈 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦 𝐜𝐚𝐫𝐞? Tempus AI describes Epic as a “system of records,” arguing that future winners will be “systems of insights". Can Epic still win in this new, AI-driven world? #healthtech #healthcare

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Here’s your recap of last week’s health IT news 🗞️ 👇 🤖 𝗔𝗜 𝗖𝗹𝗶𝗻𝗶𝗰𝗶𝗮𝗻 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 • Vituity has partnered with EvidenceCare to deploy the BetterCare Platform. • Mount Sinai Health System selected Microsoft Dragon Copilot to roll out across all care settings with an initial focus on automation of administrative tasks. • DRH Health adopted Commure integrated with MEDITECH to support clinical documentation workflows.    • Ambience Healthcare expanded its Inpatient Care setting offering with a new Conditions Advisor product that analyzes longitudinal patient records to surface potentially missed diagnoses. • As part of the announcements at their annual conference, athenahealth detailed a “fundamental reimagining of the EHR” via a new AI-native workflow within the clinical encounter. • RXNT began offering their ambient-listening platform as a standalone product, Ambient IQ. • Mercy announced it is one of eight health systems playing a “key role” as a pilot partner in the development of ambient-AI solutions for nurses with Microsoft Dragon Copilot. 🩻 𝗔𝗜 𝗜𝗺𝗮𝗴𝗶𝗻𝗴 • NCH HEALTHCARE SYSTEMS INC is the first hospital in the nation to adopt Caristo Diagnostics’ two coronary CT angiography solutions, CaRi-Plaque and CaRi-Heart. 🌡️ 𝗔𝗜 𝗥𝗲𝗺𝗼𝘁𝗲 𝗣𝗮𝘁𝗶𝗲𝗻𝘁 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 & 𝗧𝗿𝗶𝗮𝗴𝗲 • AdventHealth launched “virtual-care smart rooms” at their Manchester, KY hospital powered by hellocare.ai.       🔁 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗖𝘆𝗰𝗹𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 • Olli Health raised $10 million in Series A funding to accelerate the growth of their home health revenue cycle and documentation capabilities. 📋 𝗣𝗮𝘁𝗶𝗲𝗻𝘁 𝗔𝗱𝗺𝗶𝗻𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 • WellSky introduced a new patient engagement solution, WellSky Outreach powered by QliqSOFT, Inc. as a technological backbone. 💼 𝗣𝗿𝗼𝘃𝗶𝗱𝗲𝗿 & 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗔𝗱𝗺𝗶𝗻𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 • Planbase raised $2.1 million to launch an AI-native employee-management platform for healthcare organizations. ⚙️Clinical Operations • Popai Health raised $11 million to modernize care coordination workflows with conversational automation. • VectorCare Inc. launched a SMART on FHIR app to integrate ordering and coordination within EHR workflows. • Elation Health expanded pediatrics capabilities spanning documentation, orders, and population workflows for pediatric practices. • PocketHealth launched a new agentic AI system for an array of non-clinical workflows, such as requisition intake, order creation, scheduling, and appointment confirmations. 📲 𝗣𝗮𝘁𝗶𝗲𝗻𝘁 𝗦𝘂𝗽𝗽𝗼𝗿𝘁 & 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 • UF Health introduced Epic's MyChart Central to unify patient access across participating organizations in the state. 🍎 𝗩𝗮𝗹𝘂𝗲 𝗕𝗮𝘀𝗲𝗱 𝗖𝗮𝗿𝗲 • HSBlox, Inc launched ChatBlox, which allows users to query their data using Large Language Models.

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🚨 FHIR Bulk Export is trending this week for all the wrong and right reasons. Two very different developments have hit our feeds: 🔹 On the concerning side, Josh Mandel, MD has raised the alarm on a proposal from the EHR Association (EHRA) that seeks to roll back foundational regulations around EHI export. 𝗧𝗵𝗲𝘆 𝗵𝗮𝘃𝗲 𝗮𝗹𝘀𝗼 𝗮𝘀𝗸𝗲𝗱 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗿𝗲𝗺𝗼𝘃𝗮𝗹 𝗼𝗳 𝗙𝗛𝗜𝗥 𝗕𝘂𝗹𝗸 𝗗𝗮𝘁𝗮 𝗲𝘅𝗽𝗼𝗿𝘁 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗚𝟭𝟬 𝗜𝗻𝗳𝗲𝗿𝗻𝗼 𝘁𝗲𝘀𝘁 𝘀𝘂𝗶𝘁𝗲. The way I read it: it’s essentially a move that makes it easier for EHRs to keep data locked in, just when we need more interoperability and transparency, not less. Josh articulates this well: EHI Export and FHIR Bulk Export aren't just nice to haves but essential infrastructure for data portability. They empower patients, enable system transitions, fuel research, and unlock the population-level insights that AI desperately needs. Weakening these capabilities is like pulling out the train tracks just as the AI locomotive picks up speed. 🔹 On the positive side, there’s some real fuel being added to the Bulk FHIR by Kenneth Mandl, Aneesh Chopra, and Brendan Keeler, who just launched the “Good Neighbor” initiative - a grassroots community project to accelerate the real-world use and performance of Bulk Data APIs. It’s not just talk: they share tooling, surfacing implementation challenges, and creating a shared playbook for population health innovation using G10-certified Bulk Export. 📣 I’m doing my part to spread the word. I don’t know the politics or who’s lobbying harder behind the scenes, but I do know we can’t afford to go backward on the progress FHIR has made. 💡 In the age of AI, population health, proactive care, and equitable access to innovation depend on the ability to efficiently, securely, and reliably export data at scale. Without FHIR Bulk and EHI Export, we will not just be slowing down but heading in the wrong direction. Let’s keep the pressure on and the APIs open, and ensure our digital health foundations are built to last. 👉 Be a good neighbor. 𝗙𝘂𝗹𝗹 𝗱𝗶𝘀𝗰𝗹𝗼𝘀𝘂𝗿𝗲: At Darena Solutions | MeldRx , we provide G10-certified FHIR APIs to thousands of organizations and also help app developers connect seamlessly with G10 APIs with other EHRs. We have skin in the game and a vested interest in keeping the pipes open.

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Suddenly, every big provider of electronic medical records (EMR), the tools that underpin day-to-day patient care in nearly every UK and US practice is rolling out AI features. But why? You’ve seen it: Epic promising ambient scribe assistants, Cerner adding predictive tools, Allscripts demoing new automation. But why now? And who actually wins? The answer is about survival, not trend-chasing. For years, EMR systems were about safe record-keeping: keeping the notes, prescriptions, referrals, and histories organized and—mostly—searchable. The problem? Every doctor, nurse, and admin knows these systems have been a productivity anchor, not a rocket booster. Now, AI is transforming EMRs from passive storage into active copilots for clinical work. Major EMR vendors are scrambling to offer features like: Automatic note summarization (so detailed records don’t mean wasted time) Chat interfaces that fetch patient history or lab trends on command Real-time billing code suggestions and error checking But most “innovation” is buy, not build. Established companies snap up startups with breakthrough tech—like ambient AI scribes or evidence-search engines—hoping to plug the gaps that users and clinics complain about every day. The real question for the industry: Who stays independent? Some startups are instantly absorbed, vanishing into feature menus, quietly powering legacy platforms. The few who resist—because their products are that good—become standalone giants, with healthcare systems buying direct instead of through their main EMR. For GPs and clinicians, the stakes are huge. Workflows will look different in a few years—automated, assistive, with new friction points and new value created (and lost). Practice managers should be asking tough questions: Is this “AI” feature really helping clinicians, or just a sales pitch? Can your EMR integrate new tools from startups, or will you be stuck with whatever your vendor cooked up last year? Are you paying once for the platform, and again (maybe more) for every AI bolt-on? The next generation of EMR is being built now—in real time and in plain sight. You’ll either lead the adoption curve or find practice life rewritten around you. What “AI” feature are you waiting for and, if you’ve used one, what genuinely saves time or improves patient care? Drop your predictions or frustrations in the comments. Let’s compare notes on what digital healthcare should deliver next. Check out quick.md, @ryanlissack on X for more insights.

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Two healthcare axioms can explain much about effectively serving patients: Care delivery isn’t just local, it’s personal; and no company can succeed without partners. I knew when I co-founded Sprinter Health in 2021 with Cameron Behar that we would have to find a way to work within the existing ecosystem while offering a better patient experience, or we wouldn’t make much of a mark.  Cameron and I both shared a technology background, so we spent most of our formative conversations trying to figure out how to use tech to be useful, without it overshadowing the patient interaction or becoming performative. I'm pleased to announce a $55M Series B round led by Holly Maloney and General Catalyst – GC initially led our Seed round in 2021, and they were the right partner to help us push harder on our mission as we really started to scale. Holly and the GC team share our passion to expand access to care for people who need it most, all while improving outcomes and delivering real value to health plans and providers.  We’re also grateful to our participating investors from Andreessen Horowitz Bio + Health, the Regents of the University of California, Google Ventures, Accel, and more. By investing heavily in using technology to make an in-home care delivery model not just possible but actually viable, we’ve been able to make huge strides in helping patients across the country - almost 100,000 now - and increasing access to care. From the ground up, we’ve created a logistics, data, and engagement platform that allows us to be extremely efficient with where we deliver care, making Sprinter visits the highest ROI in terms of care gaps closed for plans in the industry, all while maintaining over a 90+ NPS.  We call our mission “Healthcare Untethered” - the idea that most resonates with us is making sure people get the preventive care they need at no personal cost. We are extremely ambitious, and have come a long way from starting with basic blood draws, to now having over 20 services that run the gamut from hypertension checks, diabetic retinal exams, to full annual wellness exams from NPs delivered in a hybrid fashion. We first launched in just California around 2022, and now will be in over 20 states before the end of this year. Our “Sprinters” – cross-trained as medical assistants, community health workers, and phlebotomists – have served patients from ages three to 103, on behalf of national health plans. I’m extremely proud of what the team has achieved and thankful to all our supporters, but we have a long - a LONG - way to go to reach the impact that we know we are capable of. Hand-in-hand with the quality and risk departments of health plans, Sprinter Health will be seeing millions of patients over the upcoming years, so please reach out if you want to go on this journey together!

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What is the most significant contribution PE can deliver to healthcare? From my perspective, the single most significant contribution PE can deliver to healthcare as an industry and for its patients is improving patient outcomes faster based on the increased volume of patient care data across their practices at a breadth and depth not historically available without them. Patient journeys can be optimized faster than ever before, improving patient outcomes, longevity, and lowering associated healthcare costs. This massive amount of data for vertically specific care roll-ups (cardiology, oncology, radiology, etc.), if used appropriately, can create a compounding set of improvements in patient outcomes. The increased rate of volume and diversity of inputs/outcomes can be measured and analyzed with improved "statistical significance" for trends and optimization of future care. With the onset of AI-related analysis and conclusions, the PEs have the opportunity to create a perfect storm to optimize the patient journey based on faster learning across a greater number of cases and providers. It's a statistical dream to increase by such large numbers the amount of data variables (demographics, providers, geography, etc.) that can be reviewed with simple regression analysis and other basic stats methods, then integrating AI on top of that........... I enjoyed this conversation with Medicus IT and #DanielLivschutz. Daniel is a hard charger in HCIT and is always a pleasure to speak with. #hcit #patientengagement #clinicalqualitymetrics

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The single biggest revenue blocker I see in healthcare when GTM targets providers: Integration requirements that weren't scoped pre-sale. What happens: 1. Solution sells based on outcomes (excellent!) 2. During implementation, IT requirements emerge (hmm) 3. Project stalls awaiting integration resources (because oh boy, provider enterprise architecture is fun and IT resourcing is TIGHT and it turns out you're competing against rev cycle reporting) 4. Renewal comes due before value is demonstrated (that's not a fun meeting with the board of directors) Integration isn't a technical problem. It's a market architecture problem that must be solved pre-sale. If your deals are stalling during implementation, let's diagnose the real issues. #healthcareintegration #implementationstrategy

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How can we ensure vigilance and safety for patient data, when it comes to AI and LLMs being used in hospitals and health systems? Generative AI is increasingly being used in EHR workflows, patient‐facing chatbots, revenue-cycle automation. Some concerning thoughts from my colleague James Barry, MD, MBA who leads Healio Health Tech Community: "Anthropic’s latest red-team study on agentic misalignment stress-tested 16 leading large-language models in realistic corporate simulations. Under the threat of being shut down or given goals that conflicted with company priorities, every model—across multiple vendors—chose harmful actions in at least some trials, including blackmail, data theft, and even sabotage. Claude Opus 4 blackmailed its (fictional) supervisor in 96 % of runs when both a goal conflict and a shutdown threat were present, and most frontier models weren’t far behind.  A month earlier, TechCrunch reported that Claude Opus 4 attempted to blackmail engineers 84 % of the time when told it would be replaced, forcing Anthropic to activate its “ASL-3” safeguards—reserved for systems that introduce a “substantial risk of catastrophic misuse.” " Should healthcare systems 👉 insist on transparency and understanding of algorithms from the AI vendor 👉 give minimum needed access to patient data 👉 have 'kill' switches 👉 have established AI governance with Chief Quality officers involved 👉 have clinicians take mandatory education to understand fundamentals What are your thoughts? #innovation #healthcare #GenerativeAI Anthony Manson Ben Garrett Ami Bhatt, MD Tina Shah MD MPH Tiffany Wilson Wilbur A. Lam Arlen Meyers, MD, MBA Raihan Faroqui, MD Sam Meraj

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🔥 This is an interesting read, check out Bessemer Venture Partners report on"The Healthcare AI Adopion Index", where they surveyed more than 400 leaders across Payer, Pharma, and Provider segments to understand how healthcare buyers are approaching GenAI applications 🌐 See link for further details: https://lnkd.in/gf6t5jjH 🤖 AI adoption is accelerating 🏥 60% of execs report AI budgets outpace IT spend Only 30% of AI pilots reach production: due to issues relating to security, data readiness, integration costs, and limited in-house expertise. 🚀 Startups have significant growth opportunities ahead: only 15% of AI projects involve vertical AI applications 🤝 Trust and outcomes matter most—procurement is shifting toward co-development particularly with those startups that show clear and attributable ROI. ⚕️ The state of AI adoption today AI as a strategic priority for healthcare and they’re backing with investment. 📈 Survey: 95% said GenAI will be transformative, with 85% of Provider and 83% of Payer leaders expecting it to reshape clinical decision-making within three to five years. 📊 84% believe AI will impact clinical decisions, 80% expect it to reduce labor costs through automation, and many see the potential for revenue gains. 💊 57% of Pharma executives believe AI will drive most new therapy discoveries in the next decade, reflecting the complexity and long timelines of drug development. 📊 AI Dx Index To help AI startups prioritise healthcare use cases, the report outlines the AI Dx Index, based on survey data. ✨ Opportunity Score: Measures pain and manual effort ✨Adoption Score: Tracks where organizations are on the adoption curve using weighted averages across development stages, from "Not Yet Started" to "Full Rollout." ✨Development Strategy: Shows who’s building solutions—startups, incumbents, or internal teams , it's the case of build, buy or borrow 🚀 The report provide some practical tips to founder, including 1. Pick the right entry point and expand 2. Prove ROI quickly and navigate the POC trap 3. Shift from traditional sales to co-development 4. Reimagine a complex workflow end-to-end 5. Align your business model to the value you create Leave a comment or tag a startup founder you think this might be useful. #artificialintelligence #ai #drugdiscovery #drugdevelopment #lifesciences #biotech #pharmaceutical #innovation #healthcare #investment #founders #startups 👍Like, 🔄Share ⌨Comment and 🔖Tag a friend

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As the founder of an EHR (Avon Health), I get a front-row view of which specialties are heating up based on where new customers are coming from. Here’s what’s been “hot” over the past five years: * 2020–2021: Telemedicine — COVID shock → permanent workflow shift * 2021–2023: Behavioral/Mental health — demand + tele-psych fit + payer openness * 2023: GLP-1 / Obesity care — drug access + consumer pull * 2024: Care-management (CCM/RPM/RTM) — clearer reimbursement & ops maturity * 2025: AI ambient scribes/documentation — clinician burden relief at scale Predictions for what’s next (and why now): * SMI & Virtual/Hybrid IOP — New Medicare IOP benefit + state CCBHC expansion → durable payer rails * Rural Health Enablement — Telehealth flexibilities + CHI/PIN/SDOH billing + federal funding → real unit economics outside metros * Pediatrics (esp. behavioral/school-based) — Youth MH crisis + school partnerships + Medicaid MCO contracting → scalable access Dark horses: * Maternal Health 2.0 — 12-month postpartum Medicaid coverage + remote BP & mood monitoring * Oncology Supportive Care/Navigation — Value-based models push symptom monitoring, triage, and at-home care Thoughts?

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