Luke Hejl

This Fierce Healthcare article by Heather Landi captures something that’s becoming impossible to ignore. AI adoption in healthcare isn’t being pulled forward by hype. It's being pushed by reality: https://lnkd.in/d-CahUXQ Economic pressure, workforce shortages, and consumer behavior are converging. Patients are already using AI to understand symptoms, coverage, and next steps. Clinicians are already using AI to synthesize information. Health systems don’t get to decide if this happens — only whether they meet people where they are or stay on their heels. What resonated most is the idea that “low-stakes” workflows are the proving ground. Documentation, billing, triage, prep instructions. These are areas where the alternative today is often nothing. No call. No follow-up. No guidance. Compared to that baseline, thoughtfully deployed AI isn’t risky — it’s responsible. But the next phase matters more. As AI moves into higher-impact workflows, the bar shifts from speed to trust: accuracy, determinism, feedback loops, and accountability. Healthcare doesn’t need AI that sounds confident. It needs AI that knows when it’s wrong and improves continuously. The biggest takeaway for me: consumer behavior has already crossed the threshold. Once patients expect answers at 10 pm on a Friday, the system has to adapt. The laggard era is ending — not because technology is perfect, but because the status quo is no longer viable. AI won’t replace clinicians or health systems. But those who learn to wield it — as guides, not gatekeepers — will define what healthcare looks like next.

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This week, Bessemer Venture Partners published their 2026 #Healthcare #AI ROI Scorecard, which is based on a survey of 226 healthcare executives and 65 use cases. The results are coming in twice as fast as buyers modeled, averaging 3.5x within about a year and exceeding expectations in roughly 40 percent of use cases. When #AI is implemented in the #back #office, revenue cycle leads with a 4x ROI, and two-thirds of those workflows are already running as semi- or fully autonomous agents. These are the measurable tasks: claims, billing, and prior authorization. #Clinical #AI is a different story, with 2.9x returns and only 4 percent autonomy. Only 46 percent of executives trust AI to support clinical decisions, and 77 percent override its suggestions more than half the time. Liability still rests with the treating clinician, and nearly half of payers will not fully reimburse for autonomous care. None of this has to do with model quality. It is about trust, evidence, and payment, and that is what makes it solvable. The report identifies four things that would close the gap: - stronger clinical validation evidence (67 percent), - transparent reasoning (53 percent), - patient-specific performance data (47 percent), and - native EHR integration (44 percent). For those developing clinical AI, buyers have essentially written a roadmap. Source: https://lnkd.in/eVk6Vr2i by Sofia Guerra and Steve Kraus Nina Capital

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88% of Americans think healthcare is becoming less affordable. Most assume it's a pricing problem. It's not. It's a design problem. I sat down with Adam Siskind from ZS Associates, who surveyed 12,000 patients and 1,500 providers across 7 countries. What he found is hard to ignore. CMS is the largest payer in the world — yet it doesn't exert the purchasing leverage that other governments do. Other countries make explicit trade-offs between cost and quality. In the U.S., that question stays politically charged instead of operationally resolved. Affordability trends aren't random. They reflect deliberate system design choices. COVID didn't create the crisis. It just stress-tested choices that were already baked in. That's not a market failure. It's a structural consequence. 🎧 Full episode linked in comments.

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The Duke-Margolis Institute for Health Policy featured Twin as a validated case study in its new Health Value–Evidence Quality framework. The bar is rising for proving both clinical outcomes and cost impact in the real world. Better health and lower total cost of care should move hand in hand. Read the publication: https://lnkd.in/efbX-Y7E

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Something to note from Menlo Ventures's incredible AI in healthcare report....their data confirm what many of us in health systems already feel coming: AI adoption will INCREASE administrative volume before it reduces it. Payers expect, in the next 12–36 months: 63% major jump in call volume 50% more codes per claim 40%+ higher claim volume 38% more prior auths 31% more appeals + resubmissions When documentation gets easier, volume is going to skyrocket. Implications we’re already planning against: - AI adoption doesn’t remove work inherently; it redistributes it across the ecosystem. Workflow redesign is critical. - Providers need guardrails to prevent over-generation of documentation and requests. More noise helps noone. - Startups must show cross-stakeholder ROI, not siloed productivity gains... - Health systems need a system-wide AI playbook, or every local win creates a downstream backlog. This next 2-3 years will either widen payer–provider tension or force real alignment. I'm not counting on the latter. Curious how others are preparing.

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Always a pleasure to speak to Cole about Healthmap! I hope you enjoy our reflections on 2025 and view of emerging trends in 2026.

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Most healthcare innovation doesn’t fail because of the technology. It fails because of policy timing. A new CMS rule. A reimbursement shift. An FDA signal. A congressional hearing. Suddenly the adoption curve changes. The challenge for healthcare leaders isn’t just tracking policy. It’s understanding what it means before the market reacts. That’s why we launched HealthPulse at MWW Health. An AI-powered policy intelligence and communications platform built for healthcare leaders navigating regulatory complexity. HealthPulse helps organizations: • Monitor real-time signals from CMS, HHS, FDA, and Capitol Hill • Translate policy developments into communications and market strategy • Identify risks and opportunities earlier than competitors • Align policy insight with adoption, reputation, and growth In healthcare, the organizations that win aren’t just innovative. They see policy coming first. If you’re at HIMSS this week, I’d love to connect. 📍 We’ll be at the Swaay.Health Lounge inside the Healthcare IT Today booth (#6453). Drop me a note if you want to talk about how healthcare leaders are starting to use policy intelligence as a strategic advantage. #HIMSS #HealthIT #DigitalHealth #HealthPolicy #AI #HealthcareInnovation

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Our convo with Dr. Tomi Kolade, Assistant CMIO at UTHealth Houston, was a MASTERCLASS in many things, but especially TRAINING clinicians on Healthcare IT. In our recent episode of The Digital Patient, we dug into: 1/ The truest measure of a digital tool’s product-market fit is the immediate volume of panic and complaints received when the tool goes down for just five minutes. 2/ The future of EHR education is not in classrooms, but in AI-driven interfaces that instantly customize the software to the individual clinician’s preferences and practice style. 3/ Health systems often waste resources filing tickets for "broken" Healthcare IT when the root cause is actually a user knowledge gap that requires recurrent, personalized education rather than technical fixes. 4/ Healthcare IT trainers must recognize that a clinician's difficulty in learning new software often stems from the high-stakes anxiety of managing human lives and NOT a lack of intelligence or capability. 5/ Before deploying AI scribes to fix documentation burdens, health systems should first look inward to see if simply redesigning note requirements and workflows would solve the problem without new technology. 6/ AI has the potential to actually RE-HUMANIZE medicine by handling administrative burdens and even suggesting empathetic phrasing, allowing doctors to return to making eye contact with patients. 7/ A radical solution to interoperability is shifting the ownership model so that patients hold their medical records like a bank account, granting temporary access to providers only when needed. All this in the episode and much, much more! Link to the episode in the comments below 👇

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