Dunstant K.

The hardest conversation in digital health fundraising isn't about your technology. It's about proving your revenue model works in healthcare's unique buying environment. When investors ask for "traction," they're really asking: Can you navigate the 18-month sales cycles, the committee-based purchasing decisions, and the risk-averse culture that defines healthcare procurement? Most health tech founders think traction means pilot programs with impressive user metrics. But healthcare buyers evaluate technology differently from other industries. They care less about your AI capabilities and more about whether you can reduce their cost per patient encounter or improve their HCAHPS scores. The gap between pilot interest and contracted revenue in healthcare is significant. Clinical champions support your solution, but procurement teams seek proof of ROI. IT departments are concerned about the challenges of integration. Finance requires budget justification that withstands annual planning cycles. Real traction in healthcare means demonstrating three things investors understand: Your pilots convert to paid contracts at predictable rates. You've proven your solution integrates without disrupting clinical workflows. Your customers can measure and defend the value you deliver internally. The challenge isn't developing better healthcare technology. It's creating a revenue model that fits healthcare's operational realities. Health systems don't invest in innovation just for the sake of it. They acquire solutions to address specific operational issues that affect their finances or clinical results. Your traction story should reflect this purchasing behavior. The companies that successfully scale in digital health aren't necessarily the ones with the most advanced technology. They're the ones who understand healthcare's unique market dynamics and build their go-to-market strategy accordingly.

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Great to join health industry leaders at the AI Health Conference 2026 organized by the Pitt School of Business. A clear consensus emerged: AI is rapidly transforming every industry, and healthcare will be among the most impacted. Recent advances in agentic AI systems are accelerating this shift, enabling AI to move beyond single models toward coordinated systems that support real clinical and operational workflows. However, the key challenge ahead is not only capability, it is trustworthy, reliability, governance, responsible management, evaluation, and implementation of these principles. It will be critical to safely integrating these technologies into healthcare practice.

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Healthcare incentives are messy — complicated, opaque, and often counterintuitive. Too often, the conversation lacks nuance. We over-index on financial motives and consumerism while underestimating how entrenched referral patterns really are. A recent NEJM Catalyst study from Zeke Emanuel, Amol S Navathe, and colleagues tests some of those assumptions. They looked at whether a behaviorally informed, physician-focused interventions could increase referrals to high-value settings: places that deliver equivalent or better quality at below-market cost. The program combined: ▪️ Individualized referral goals ▪️ Meaningful financial incentives ▪️ Coaching on high-value facilities ▪️ Monthly performance feedback Results after one year: ▪️ Significant improvement only in radiology (+18.7% to high-value sites) and cost savings for radiology (19% / $145 per referral) and elective orthopedics (23% / $2,590 per referral) ▪️ No meaningful change for labs, GI, or new specialist referrals These mixed results highlight two ground truths: healthcare incentives are complex, and not all services are equally “switchable.” A few thoughts: ▪️ Physician referral patterns are deeply entrenched and based on personal relationships and habit. ▪️ Radiology procedures may be viewed as a commodity — an MRI is an MRI. Psychological switching costs are lower. ▪️ Generalizing the results is difficult. Physicians locked into vertically integrated health systems are incentivized to capture referrals, irrespective of quality or cost. ▪️ Financial incentives are important, but small ones don't change behaviors and large ones nullify cost savings. ▪️ The study confirms what we already knew: site-of-service drives cost variation — hip replacements from $20k to $98k in a single market. The authors are skeptical of patient-facing approaches like price transparency tools, noting physicians and practices often control the referral path. Others might point to care navigators, Centers of Excellence, and DTC models as counterexamples. Aligning incentives is critical — but first, we have to agree on what the “right” incentives even are. (Article link in comments)

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Here’s your recap of last week’s health IT partnership and product release news. 🗞️ 👇 (Part 1 of 2 - this was a busy week for health IT announcements!) 🤝 𝗣𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗻𝗲𝘄𝘀: • UMass Memorial Health is expanding Mednition KATE AI system-wide. • Stanford Health Care is using Atropos Health to surface personalized evidence at the point of care.    • MetroHealth System selected Pieces for inpatient and outpatient settings.    • TriHealth selected Reveal-Dx and announced a clinical study to evaluate real-world impact.    • Cleveland Clinic announced it would be using AKASA's coding AI assistant and CDI tool.    • Allegheny Health announced its first "touchless" prior auth with Humata Health.    • Sentara Health is expanding its use of Andor Health.    • Albany Med selected Honest Health as its ACO enabler. 🚀 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗡𝗲𝘄𝘀: • Videra Health launched AI-powered Group Notes • Cedar released an agentic AI solution to handle patient billing calls. • Relatient launched a conversational AI feature for automating patient scheduling calls. • Zocdoc released Zo, a voice AI agent that handles ��inbound scheduling calls. • CliniComp integrated enterprise-wide PACS with its Intrinsic AI solution suite. • Viz.ai announced Viz 3D CTA, which converts computed tomography angiography scans into AI-enhanced 3D images for neurovascular visualization.    • Limbic launched Limbic Intake Agent, a voice AI agent that handles patient intake. • CoreCare launched Pre-Admit to help SNFs assess referrals. • NeuroFlow published new research showing the efficacy of its solution in recognizing suicidal ideation. • Get Well announced an AI patient assistant to support inpatient care navigation and discharge.    • Digital Medicine Society (DiMe), Duke University, University of North Carolina at Chapel Hill, Fitbit (now part of Google), + ŌURA announced a collaborative aimed at helping prevent relapse and reduce deaths from opioid use disorder using wearable technology. 𝗥𝗲𝗺𝗶𝗻𝗱𝗲𝗿: you can always catch the full details of each of these announcements in our weekly Elion Briefing (sign up at Elion [dot] health [slash] newsletter).

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The White House is proposing healthcare reforms projecting $36B+ in savings and double-digit premium reductions, with a focus on patient clarity and choice 👀 The Great American Healthcare Plan will: 👉enable Americans to pay drug prices closer to what other countries pay through most-favored-nation pricing 👉make more medications available OTC, reducing cost and friction 👉 send healthcare subsidy dollars directly to people, instead of routing them through insurers 🧐 👉funding cost-sharing reductions that may ⬇️ ACA premiums by 10%+ 👉require insurers to explain coverage, denials, overhead, and wait times in plain English 👉require providers that take Medicare or Medicaid to clearly post prices and fees 📌Details: https://lnkd.in/eR5d4nQ9

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Introducing the Health Innovation Strategy Framework After two decades of building health startups, advising Fortune 500 life sciences firms, and designing care delivery programs at scale—I've distilled what works (and what fails) in transforming healthcare. 💡 That’s why I created the Health Innovation Strategy Framework—a blueprint to help healthcare leaders and organizations move beyond the buzzwords and into measurable outcomes. This framework is designed for: Health tech founders navigating go-to-market chaos Provider groups launching digital-first services Employers, payers & PBMs aiming to improve access, cost & experience Investors evaluating scalable models in a complex care ecosystem Organizations looking for the next best health innovation to partner, adopt or acquire 📊 Core pillars: •Innovation Culture and Infrastructure •Partnership Readiness •Product-Market Fit in Healthcare •Regulatory & Payer Navigation •Clinical Workflow Alignment •Patient Engagement •Sustainable Growth Strategy Here’s a quick look ⬇️ I’ll be diving into each of these in subsequent posts. 🔍 Want to see how this applies to your organization? 📬 DM me or contact me directly for a custom Innovation Readiness Assessment. Let’s build smarter, faster, and with real impact. #HealthcareInnovation #HealthTech #PartnershipStrategy #DigitalHealth #GoToMarket #ValueBasedCare #HealthEquity #LifeSciences #StrategicGrowth #HealthStrategy

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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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An MSO leader told me: 'We have fee-for-service, capitation, shared savings, and direct pay contracts. We have no idea which ones actually make money.' Sound familiar? Digital health companies scaling across markets often end up with a portfolio of payment models: Fee-for-service with traditional payers Value-based contracts with progressive ACOs Direct pay arrangements with self-insured employers Hybrid models with Medicaid managed care The successful ones? They track performance across ALL models: ✓ Margin analysis by contract type  ✓ Administrative burden per payment model  ✓ Cash flow predictability across payers  ✓ Scalability assessment for each arrangement Enabling doubling down on your most profitable contracts types and sunsetting the ones bleeding money. We want to get you paid consistently. Good growth means knowing which arrangements serve your mission and which just serve your ego.

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🏥⚖️ Hospital ownership isn’t just a business decision—it’s a health equity issue. Rhode Island’s Attorney General is setting a bold precedent by adding strict conditions to the sale of two safety-net hospitals, pushing back against private equity’s growing influence in health care. 📉 Prospect Medical Holdings, backed by private equity, left hospitals with $6B in debt and deteriorating infrastructure—while investors extracted $600M in dividends. 📈 The new deal requires $50M in capital investments, expanded oversight, and accountability safeguards to protect underserved communities. 🗣️ “Without public accountability, there’s no clear line between investment that heals and investment that harms.” 🔗 Read the full article here: https://buff.ly/AOv7iU5 #HealthEquity #HospitalJustice #ReedeScholars #PrivateEquityWatch #CommunityCare

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