Ignition by RocketTools

Dan McCoy, MD

Healthcare is getting optimized by AI. But optimized for whom? Ignition by RocketTools breaks down the systems, incentives, and technology reshaping how care gets approved, denied, and paid for — with data, not hype.

  1. 18h ago

    How One Reused Password Cost Change Healthcare $2.5 Billion (Healthcare Security, Part 1)

    In February 2024, hackers walked into the largest healthcare clearinghouse in America through a Citrix portal that didn't have multi-factor authentication. They used credentials stolen from a previous breach — someone, somewhere, had reused their password. Within hours they had ransomware running. Within days, pharmacies across the country couldn't fill prescriptions. The ransom payment was $22 million in Bitcoin. The total cost to UnitedHealth Group is now over $2.457 billion. The number of Americans whose data was exposed is 192.7 million — roughly 58% of the country. And it all started with one reused password. This is Part 1 of an 8-part Healthcare Security series. In this episode I walk through why your password habits are probably just as dangerous, why "47 logins" understates the reality for healthcare executives, and the four password managers I actually recommend — with the honest tradeoff on each, and no affiliate links. I also explain why a single patient record sells for $250 on the dark web while a credit card goes for $5, and why your AI tool account in 2026 holds more sensitive information than most of your work files. In this episode: The Change Healthcare breach timeline and what Andrew Witty admitted under oath to CongressWhy password patterns ("FirstName2024!" and friends) are now exactly what attackers test firstThe 47-logins-on-average problem for healthcare execs and why the real number is higherThe four password managers I'd recommend: Dashlane, 1Password, Proton Pass, and Bitwarden — pricing, tradeoffs, who each is right forA four-step action plan you can run this week, starting with one email to your IT team📺 Watch on YouTube: https://youtu.be/N62kieISWiI 📝 Read the director's cut companion post on Substack (deeper on Witty's Senate testimony, the dark web pricing texture, and the AI tool risk section I had to cut for time): https://open.substack.com/pub/danmccoymd/p/the-872m-password-mistake-was-actually Next week, Part 2: why CISA and the FBI told Americans to stop using SMS-based MFA, the authenticator app I switched to after leaving Microsoft Authenticator, and the small piece of hardware I added on top. I'm Dan McCoy. Ignition by RocketTools is the podcast for healthcare executives, physicians, and AI builders trying to think clearly about where this is all going.

    9 min
  2. 4d ago

    The Target Story Isn't About Coupons. It's About Healthcare AI.

    Twelve years ago, a Target statistician built a model that could predict pregnancy from 25 shopping items. The story usually gets told as a privacy parable. I'm telling it differently — as a preview of how healthcare AI is going to work for the rest of our lives. Your smartwatch can already flag atrial fibrillation days before a cardiologist would. It can detect depression weeks before clinical scoring catches it. It can spot cognitive decline six to twelve months before you notice. The science isn't the question anymore. The question is who gets to see what comes out of the model — and whether we build the governance before the surveillance economy locks in. In this episode I get into: • Why Andrew Pole's 2012 Target model was a dry run for what's coming in clinical AI • What the wearable accuracy numbers (70–95%) actually mean — and where they get softer than the headlines suggest • The function-creep economy that's already running: CGM data sold to ad partners, period-tracking app subpoenas, life insurers bidding on de-identified wearable sets • The 99.98% problem — why "de-identified" data isn't • Habit-disruption windows: the real case for early-detection surveillance in healthcare • Four policy moves that would change the data-broker incentive structure overnight Full written companion with sources and citations: danmccoymd.substack.com Watch on YouTube: https://youtu.be/LbE6TbGIzIY I'm Dan McCoy. Ignition by RocketTools is the podcast for healthcare executives, physicians, and AI builders trying to think clearly about where this is all going. New episode every week.

    11 min
  3. 6d ago

    The 9-Person Insurance Company and the Real Line in AI-First Healthcare

    Y Combinator has a name for it: burn tokens, not headcount. A health insurance company called Decent runs with nine people total. Twofold does revenue cycle management with three. Deep Cura Health handles patient scheduling, prior authorization, and insurance verification with two humans and seven AI agents. The AI-first model is real. It's working. And in healthcare, every one of these companies has made the same quiet choice: they're attacking admin, not clinical. This episode unpacks why — and why the conventional wisdom ("admin is safe to automate, clinical isn't") is the wrong frame. The real line isn't admin versus clinical. It's decision support versus decision making. IBM burned $4 billion learning the difference with Watson Health. The next generation of healthcare AI companies will either learn from that, or rebuild the same trap with better UX. What's covered: How AI-first companies are quietly rewriting healthcare staffingWhat IBM Watson Health actually got wrong — and why "the AI was wrong" misses the lessonWhy most "decision support" products today are decision-making in a trench coatThe payment-model problem nobody is pricing: a 5,000-patient panel breaks fee-for-serviceThe companies positioning themselves on the right side of the line🎥 Watch on YouTube: https://youtu.be/9fHKQqm15qo 📝 Companion essay (with the receipts I had to cut for length): https://danmccoymd.substack.com/p/the-part-of-ai-first-healthcare-that

    6 min
  4. May 21

    Are the Blues AI-Ready? Blue Cross vs. the Optum Platform Race

    In March 2026, the Blue Cross Blue Shield Association published research blaming hospitals' AI billing tools for $2.3 billion in added healthcare costs. It was a grievance — not a strategy. And it stands in sharp contrast to 1981, when the same Association faced a national-platform problem and built something: BlueCard, the shared claims-routing layer that turned 36 independent regional plans into the reason one in three Americans carry a Blue card today. This episode asks the contrarian question: in an AI world, is the Blues' patchwork of 36 plans a fatal weakness — or the exact architecture the future rewards? What we get into: Why Elevance and Highmark are racing in opposite directions (multi-vendor horizontal vs. Epic single-stack vertical) — and what the other 34 plans aren't doing The plan-level wins that already shipped (BCBS Minnesota, Illinois, Arkansas) — and why none of them are federated The federated-learning research that says the Blues' structure is the ideal AI architecture — including a peer-reviewed BCBS Louisiana study where regional models beat national algorithms The Optum problem: what happens if UnitedHealth builds the AI equivalent of BlueCard before the Blues do Three concrete signals to watch by the end of 2027 Full companion essay on Substack with sources and the three-signal checklist: https://open.substack.com/pub/danmccoymd/p/blue-cross-built-the-last-healthcare Watch the video version: https://youtu.be/LCrRFqTTtuo Connect with me at RocketTools.io for AI Strategy Consulting and podcast or speaking engagements.

    16 min
  5. May 20

    The Hospital Cost Crisis: How Washington Banned Cheaper Care

    You've been told American healthcare is expensive because of greedy insurers, pharma profits, or the cost of innovation. That story is incomplete to the point of being misleading. The largest single driver of US healthcare spending isn't drug companies — it's hospitals. And hospital prices haven't merely risen; they've grown roughly 3x faster than overall inflation since 2000. No sector does that for two decades by accident. In this episode, Dan McCoy MD breaks down the three federal policy choices that designed America's hospital pricing crisis: • ACA Section 6001 — the 2010 ban on new physician-owned hospitals, the one competitor proven to be roughly a third cheaper. $2.2B in planned development killed; 75 hospitals never built. • Certificate of Need laws — still active in 41 states, letting incumbent hospitals veto their own competition. • Site-specific Medicare payment — paying hospitals 2–3x what it pays a physician office for the identical service. Add a starved FTC (~13 challenges out of ~561 hospital mergers from 2010–2015) and you get the result: ~97% of metro areas with highly concentrated inpatient markets, and prices that rise 15–30% higher than competitive ones. It isn't a mystery. It's a mechanism. If you run a health plan, here's the takeaway: your hospital costs are set by market structure, not market forces — and the policy landscape (site-neutral reform, Certificate of Need repeal) is finally starting to shift. 📺 Watch the video version: https://youtu.be/aWtOw8PxHTU 📝 Full research sources, all 12 cited studies, and a bonus analysis of the political economy of hospital lobbying — on the Substack Subscribe so you don't miss the next episode. This episode is for educational and informational purposes and is not medical, legal, or financial advice.

    10 min
  6. May 4

    21st Century Cures, 20th Century Accounting: Why a $3M Gene Therapy Just Broke Insurance

    A 6-month-old named KJ Muldoon just received the first personalized CRISPR gene therapy ever made — designed, manufactured, and administered for his exact mutation in six months. Nature named him to the Top 10 People Who Shaped Science of 2025. The miracle is real. The financing model isn't. Gene therapies run $2M to $3.5M each. Insurance contracts are annual. Gene therapy benefits last a lifetime. The employer who pays in year one rarely sees the savings — average commercial plan tenure is three years. In this episode: — Why the "gene therapy tsunami" narrative is overstated (EBRI's numbers tell a different story) — The free-rider problem and why annual contracts can't price lifetime cures — The concierge medicine paradox: we pay $3M to cure you, but won't pay $300/mo to keep you healthy — Four financing models worth knowing for 2026: gene-therapy-specific stop-loss, outcomes-based agreements, risk-pooling platforms, and performance-based annuities — How AI is compressing drug development timelines — and why that compounds the budget problem We have 21st century cures and 20th century accounting. Eventually, one of those has to change. Watch the full video: https://youtu.be/ap2XjNf3LN0 Read the Substack companion piece: https://open.substack.com/pub/danmccoymd/p/21st-century-cures-20th-century-accounting Full sources and the deep dive: danmccoymd.substack.com

    12 min

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Healthcare is getting optimized by AI. But optimized for whom? Ignition by RocketTools breaks down the systems, incentives, and technology reshaping how care gets approved, denied, and paid for — with data, not hype.