Jordan Kelley

“The thing I am most proud of is that because we built the entire tech stack that we own, from the member app, the company, the client dashboard, to electronic medical records systems and other internal tooling.   We enable providers to spend more time with the patient.” How much longer? 3x longer than the average primary care visit.   This week on the Digital Health Heavyweights Podcast I sit down with Joseph Kitonga, CEO and founder of Vitable Health. Joseph shares his journey from a family background in caregiving to creating a health plan that addresses the needs of underserved workers. He discusses the inspiration behind Vitable, his experience with the Thiel Fellowship, the prestigious Y Combinator,and the unique aspects of Vitable's direct primary care model.   “We are growing extremely quickly” The conversation also covers the challenges of hybrid care models, the importance of empathy in healthcare, and the company's growth trajectory. Joseph emphasizes the need for accessible healthcare and shares insights on building a successful startup in the healthcare space.   How is Vitable impacting clients? An average savings of about 12%   Takeaways ✨ Joseph's family background in caregiving inspired him to create Vitable Health. 💙 Vitable Health aims to provide affordable healthcare for underserved workers. 🎓 The Thiel Fellowship provided Joseph with the opportunity to focus on his startup. 🚪 Vitable's model reduces barriers to accessing primary care services. 📈 The company has about 100,000 members and is growing rapidly. 💻 Vitable's approach integrates in-home and virtual care effectively. 🤝 Building empathy through direct interaction with clients is crucial for Vitable. 🗣️ Joseph emphasizes the importance of talking to users to build a successful product. 🚀 The Y Combinator experience was pivotal for Vitable's growth. 🧘 Joseph practices mindfulness and reading to manage stress and maintain focus. Check out the episode and be sure to like comment and subsc https://lnkd.in/dVAzHMQZ

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Changing Healthcare's Innovation Playbook - Fascinating healthcare policy shifts creating opportunities for AI-native startups: 1. CMMI's aggressive push for digital health in disease prevention 2. FDA deploying GenAI to accelerate regulatory reviews! 3. Tension between deregulation demands and AI safety needs At C10 Labs, in healthcare we're backing founders building at these intersection of policy evolution, AI first thinking and technological capability. The winners will navigate regulation and leverage it as competitive advantage. Think where the puck is moving and build to it faster and better. #HealthTech #AIinHealthcare #VentureCapital C10 Labs

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Healthcare moves fast when the pain is obvious. EHRs took seven years with incentives while ambient scribes scaled in two years without subsidies. Providers and payers are building AI labs, which turns the buyer into a builder. Startups win by owning the workflow, delivering turnkey integration, proving ROI fast, and co developing with internal teams. Sell to the C suite, price on outcomes, and show repeatable production rather than pilots that never end. https://lnkd.in/gYxYDnBe

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Too many startups assume: 𝙩𝙝𝙚𝙧𝙚’𝙨 𝙖 𝘾𝙋𝙏 𝙘𝙤𝙙𝙚 → 𝙩𝙝𝙚𝙧𝙚𝙛𝙤𝙧𝙚 𝙩𝙝𝙚𝙧𝙚’𝙨 𝙖 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨. Reality is rarely that linear. Viability tends to unfold in fits and starts, shaped by payer coverage, provider workflows, and the real operational burden behind reliable billing. ⚙️📉 Inspired by Matt Kamen's excellent post on CPT adoption curves & the recent ACCESS discussion, we’re sharing our internal framework: 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐭𝐨 𝐀𝐬𝐤 𝐁𝐞𝐟𝐨𝐫𝐞 𝐁𝐞𝐭𝐭𝐢𝐧𝐠 𝐨𝐧 𝐚 𝐍𝐞𝐰 𝐁𝐢𝐥𝐥𝐢𝐧𝐠 𝐂𝐨𝐝𝐞 It goes deeper than payment policy — covering clinical and documentation requirements, enrollment and service mechanics, operational readiness, and the maturity of the CPT pathway. 🧠📋 If you’re evaluating a CPT-driven business model — or working with someone who is — comment “𝘾𝙋𝙏” below + DM me & I’ll share the document. 📄➡️ #startups #HealthcarePolicy #HealthTech #CMMI #ACCESSModel #Medicare #DigitalHealth

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Client Success Story: MedSure Health — Securing Patient Diagnostics with Honeypotz Confidential Computing TEE Client Overview MedSure Health, a fast-growing telemedicine startup, provides AI-powered diagnostic services to patients across North America. Their platform enables users to upload medical images and receive instant analysis from AI models, followed by virtual consultations with certified physicians. The Problem As MedSure scaled, they faced a critical challenge: protecting sensitive patient data during AI processing. Although data was encrypted at rest and in transit, it remained vulnerable during computation — a major compliance and trust issue, especially under HIPAA and GDPR regulations. MedSure’s CTO, Elena Ramirez, explained: “Our AI models needed access to raw patient data to deliver accurate diagnostics. But that meant exposing sensitive information during processing — a risk we couldn’t afford.” The Solution: Honeypotz Confidential Computing TEE MedSure partnered with Honeypotz Inc to integrate their Confidential Computing TEE platform into the diagnostic pipeline. Honeypotz’s solution offered: • Trusted Execution Environments (TEEs) that isolate and protect data during processing. • Remote attestation to verify the integrity of the computing environment. • Seamless integration with MedSure’s existing cloud infrastructure. Implementation Highlights 1. Secure AI Inference Medical images and patient histories are processed within Honeypotz’s TEEs, ensuring that data remains encrypted and inaccessible to unauthorized parties — even during computation. 2. Compliance Automation Honeypotz provided real-time attestation logs and audit trails, simplifying MedSure’s compliance reporting and reducing audit preparation time by 30%. 3. Patient Trust & Market Expansion With enhanced data security, MedSure launched in European markets, confident in GDPR compliance. Patient onboarding increased by 25%, driven by trust in the platform’s privacy guarantees. Results • Zero data exposure incidents since deployment. • 90% reduction in internal data access risk. • Faster regulatory approvals for new markets. • Improved brand reputation and patient retention. Client Testimonial “Honeypotz didn’t just give us a security solution — they gave us a competitive edge. Our patients feel safer, and our team sleeps better at night.” — Elena Ramirez, CTO, MedSure Health

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Why Now Is the Best Time Ever to Invest in Healthcare AI Startups By Andy Reid, Managing Partner, M3A Healthcare Ventures We are entering a once-in-a-generation window for investing in Healthcare AI—one where timing, technology, and major shifts in care are aligning to create outsized opportunities for early-stage venture capital. At M3A Healthcare Ventures, we believe this is the moment to invest boldly. 1. Healthcare Is Ripe for Disruption—And It Has To Be U.S. healthcare costs are projected to hit $7.2 trillion by 2031, yet outcomes lag behind every other developed nation. Workforce shortages, and fractured data systems create inefficiencies that AI is uniquely positioned to solve. • 25% of U.S. healthcare spending is administrative waste. • 90% of hospitals face staffing shortages in key roles. • Doctors spend 2 hours on documentation for every 1 hour with patients. AI isn’t a “nice to have” anymore. It’s becoming a critical tool for cost control, productivity, and quality improvement. 2. We’ve Entered the Platform Shift Era Apple Intelligence, OpenAI, and other foundation models have catalyzed a new generation of startups. In healthcare, this means real-time ambient documentation, predictive care, smart inventory management, and even AI-generated clinical trial design—all happening today. This is akin to investing in SaaS in 2006 or mobile apps in 2011. Except this time, the TAM is $4 trillion larger. 3. Buyers Are Ready—and They’re Buying Just five years ago, hospitals were wary of AI. Today, they’re budgeting for it. Health systems, ASCs, pharma, and insurers are deploying capital to integrate AI that: • Shortens revenue cycles • Boosts clinician efficiency • Reduces preventable readmissions • Enhances training and education with immersive tools In short: the demand isn’t theoretical—it’s contractually real. 4. Healthcare AI Has Multiple High-Value Exit Paths M&A activity is accelerating, and healthcare AI companies are being acquired by: • Strategics like Stryker (e.g., $130M for care.ai) • PE-backed rollups seeking operational efficiency • Big Tech, which is aggressively moving into healthcare These aren’t just tech exits. They’re life sciences, SaaS, and data infrastructure exits rolled into one—often with 3–5x higher revenue multiples. 5. We Have the Talent, Data, and Infrastructure The convergence of: • Open health data regulations (ONC Cures Act) • AI-native medical founders trained in both tech and care delivery • Decreasing costs and better modeling We finally have a clear runway to build and scale. The Next MedTech Unicorns Will Be AI-First The next wave will be built on data, AI, and automation. Investors who move now will back the next Teladoc, Intuitive, or Epic—except leaner, faster, and born in the AI-native era. #HealthcareAI #HealthTech #VentureCapital #DigitalHealth #AIinHealthcare #MedTech #ArtificialIntelligence #StartupInvestment #HealthTechStartups #VCFunding #AIStartup

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🚨 $320B Problem. Now a Reimbursable Solution. 📢 Now Raising $5M Series A | $25M Pre-Money | $7M Lead Committed 📈 Health Tech SaaS | 💥 New CMS Codes | 💸 Real ROI The U.S. healthcare system is hemorrhaging over $320 billion per year due to unmet social determinants of health (SDoH)—non-clinical barriers like food insecurity, housing instability, and transportation gaps. Most clinicians know these issues… but until now, they couldn’t bill for solving them. That just changed. In 2024, CMS unlocked reimbursement for addressing SDoH. Now there’s a platform built to automate the solution at scale. 🎯 Patient Discovery Solutions (PDS) ✔️ HITRUST Certified ✔️ EHR-integrated SaaS ✔️ Reimburses care teams + boosts patient outcomes ✔️ Three recurring revenue streams: ‣ SaaS licenses ‣ Pharma content & education ‣ Real-world data sales 🔒PDS early pledge of $7m by a legendary pioneer who built one of the largest healthcare PE firms on the planet (250+ companies, $27B raised) 📊 Forecast: $100M+ in bookings by 2029 🏥 TAM: 35,000 clinics | 750M patient visits/year This is where tech meets reimbursement meets ROI. 💡 Healthcare is one of the last industries to digitize effectively—yet the most ripe for disruption. According to McKinsey, healthcare SaaS is 5–10 years behind fintech and enterprise SaaS. PDS is the bridge forward. 📩 Now raising $5M Series A at a $25M pre-money valuation. Lead investor has committed $7M. Time-sensitive, market-ready, and regulatory-backed. Patient Discovery Solutions (PDS) is an innovative, clinically validated SaaS platform that leverages AI-driven automation to transform patient engagement and optimize revenue workflows for healthcare practices, initially targeting the oncology market. Backed by strategic partnerships with PatientPoint and Cencora (a Fortune 10 healthcare leader), PDS enjoys exclusive, immediate access to 65% of oncology practices, ensuring rapid market penetration and significant barriers to competition. With a diversified revenue model—comprising SaaS subscriptions, pharma-sponsored advertising, and patient data monetization—PDS is projecting annual revenues of $100 million by 2029. 📩 Interested in learning more? Feel free to connect or message me directly here on LinkedIn for an introductory conversation. Note: This is not an offer to sell or a solicitation of an offer to buy any securities. All inquiries will be directed through proper channels. 👉 Another transformative opportunity by Ventura Partners Wealth Hub 🌐 www.venturapartnersllc.com #HealthcareInnovation #SaaS #VC #PrivateEquity #FamilyOffice #Linkedin #Money #Investment #DigitalHealth #ValueBasedCare #PatientEngagement #HealthEquity #VenturaPartners

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“30% of every $1 in US health care goes to admin fees of some kind.” In theory, this should be able to go down to 3% over the next decade as AI Process Platforms disrupt SaaS & bureaucratic 20th century enterprise services - in most other industries transaction costs have dropped to this level.

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𝐑𝐚𝐢𝐬𝐞 𝐌𝐢𝐥𝐥𝐢𝐨𝐧𝐬 (𝐁𝐲 𝐇𝐮𝐬𝐭𝐥𝐞 𝐅𝐮𝐧𝐝) A practical, founder-first guide to how early-stage fundraising actually works—based on real investor behavior, not pitch theory. Key Takeaways: 1️⃣ Fundraising is a system: Targeting, sequencing, and momentum matter more than a great story. 2️⃣ Signals beat effort: Investors react to traction, clarity, and risk reduction—not hustle or long decks. 3️⃣ Mechanics decide outcomes: Timing, dilution, and investor selection compound far more than valuation. Bottom line? Fundraising isn’t about persuasion—it’s about engineering proof and leverage. P.S. Want a PDF of Raise Millions? Get it free: https://lnkd.in/guuxKa-J ♻️ Repost to help people in your network. 💡 Follow Alejandro Cremades for more strategy insights.

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Stop optimizing for the wrong metric. We treat “how much have you raised?” as the scoreboard. Most founders aren't deciding between venture capital and nothing. They're deciding how much control, pressure, and optionality they're willing to trade for speed. VC works for a narrow slice of businesses and founders, but startup culture has normalized it as the aspiration, not the option. For underrepresented founders especially, that normalization comes at a real cost. Chasing VC often means reshaping your business, your timeline, and sometimes your values to match someone else's growth model. You're told that's ambition, but for many founders it's actually misalignment. If we accepted that most companies are non-VC led by default - funded through revenue, angels, debt, or creative hybrids, our ecosystems would look very different. We'd build instruments, communities, and support systems designed for sustainable growth, not just "unicorn" outcomes. Raising money is a tool, not a virtue. Control is a strategy choice, not a lack of ambition. Have you chosen a non-VC path? Intentionally or by necessity?

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If you’re pitching “physician practice” software, your TAM is probably fiction. Latest numbers on ACO and Medical Home adoption expose a hard split most healthtech founders gloss over: “physician practice” isn’t one market. It’s three and the gap between segments will drain your runway if you ignore it. Snapshot: Solo practices: 8.5%–24% adoption across all VBC models Multi-specialty groups: 36.7%–47.7% Hospital-owned practices: 34.7%–46.3% (vs. 17.5%–36% for physician-owned) . What this means for founders: Your TAM is a mirage: Modeling “200,000 physician practices” as your addressable market? Garbage. Solo and small independent practices are not buying ACO-adjacent tech at scale. Sales cycles are stratified: Selling into solo practices? Prepare for churn and long-tail closes. Multi-specialty and hospital-owned groups move faster—if you’re mapping pilot success with one segment across all, you’re modeling bankruptcy. Contract value is tiered: Hospital-owned = higher ACV, more mandates, less price sensitivity. Independent = self-funded, price-anchored, higher churn risk. Your pricing strategy needs three SKUs: Milestone-linked contracts tied to ACO metrics will land faster with multi-specialty/hospital-owned. Solo practices? You’re pushing rope. Consolidation is accelerating: Hospitals now own nearly half of U.S. practices; corporate (PE, payers) ownership grew 86% from 2019–2021. If your product roadmap ignores the ongoing corporate land grab, you’re building for extinction. Five Tactical Recommendations: Re-cut your TAM by segment: Stop selling the “unified” physician market story. Investors don’t buy it—neither should you. Model three separate funnels: One for solo, one for physician-owned groups, one for hospital-owned/multi-specialty. Pricing, churn, and ARPU will diverge. Build accordingly. Align pilots to segment triggers: Hospital and multi-specialty: tie pilots to value-based reimbursement or ACO participation milestones. Solo? Low-touch, hands-off, minimal investment—otherwise you’ll bleed out in onboarding. Build for rapid payer/data integration: Large integrated systems demand it. Solo practices won’t pay for it. Track consolidation by market: Don’t waste resources on the “independent” segment in MSAs where hospital or PE roll-up is already at 60%+. Markets collapse, and so will your customer base. Bottom line: If you’re not segmenting your plan by practice type and ownership before you pitch, model, or build, well your burn rate will punish you faster than the market will. If a founder hands you a TAM slide treating all practices as fungible, they’re stuck in 2010. Push for segmentation on every metric that matters, or pass. Value-based care is here. But like capital, it’s not evenly distributed. Build and fund accordingly. #Healthcare #Startups #ValueBasedCare #PhysicianPractice #TAM #VBC #HealthTech #OperationalTruth #NoFiction

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OpenAI just launched for healthcare. The technology isn't new - but what just changed is massive: Last week, OpenAI announced: • Optimized APIs for healthcare • ChatGPT Health for consumers. • The acquisition of Torch, an EHR startup. But what everyone's missing is that most of this already existed. • The APIs were already available. • The technology has been ready for months. So why does this announcement matter? 1. It validates the market. When a company like OpenAI publicly declares they're entering healthcare, that's a signal. When they make a healthcare acquisition, it's even clearer. Every healthcare investor, every clinic operator, every hospital system knows AI in healthcare is real and happening. 2. It educates the buyers. 90% of the clinic operators I talk to didn't know Open AI's APIs could already be set up to be HIPAA compliant. OpenAI just did the market education work that benefits everyone building in this space, including us at Entropy. 3. The implementation gap is still huge. OpenAI's announcement removes the knowledge barriers that kept many healthcare organizations from adopting AI. But here's what still breaks in the real world: What most healthcare organizations need is a system that learns how your clinic operates day to day. That adapts to change without engineers. That detects new providers and alerts the team. That knows who uses fax and who uses the portal. General-purpose AI - even healthcare-optimized AI - can't do that. That's what we're building at Entropy. OpenAI has validated the market. We're building what actually works in real clinics.

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I’ve spoken to over 2 dozen MDs at PE firms I can confidently say that the arb of figuring out how to implement Vertical AI at portfolio companies is very real right now It will fundamentally change underwriting for those who can do it predictably and unlock generational returns. Most are aware they need to act. Very few have.

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The White House and CMS just launched the Health Tech Ecosystem Initiative to make health data move in real time with 60+ major players on board from Google, Apple and OpenAI to Cleveland Clinic and CVS. Two main goals: 1. Interoperability Framework for secure, real-time exchange between systems. 2. Connected care tools for chronic care, digital check-ins and conversational AI. By early 2026, participating networks must: - Offer unified patient records. - Provide FHIR API access for apps and developers. - Let patients control their own data (no central database). - Launch app-based tools for viewing and sharing. This will create the baseline infrastructure for safe, AI-enabled health services and align big tech, providers and payers on shared rails. If it delivers, healthcare could start functioning more like the rest of the digital economy with patients actually in control of their own data. #healthcareai #patientdata

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