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{/if}Hey Hospitalogists!
Before we get into it, big news: I launched a podcast.
It’s called Claims Denied, and it follows my personal journey to learn everything there is to know about the business of healthcare. |
Every week, I’m sitting down with healthcare leaders to talk shop about emerging trends in health system transformation, health tech startups changing the game, and scalding hot takes on the future of the industry.
The conversations have been incredible (you can check out a little teaser below) and I can’t wait for you all to hear them. I hope you’ll subscribe on Apple or Spotify and, if you know someone I should talk to, send ‘em my way. I’d love to chat.
Also, I’d love to know…
Who’s going to ViVE next month? I’m curating a small group of healthcare leaders for a happy hour on Feb 22. The rooftop venue is unreal, but the true value is the people you’ll meet. If you’re swimming in any of these industries, I’d love to have you join me: - health systems
- physician groups
- ACOs
- payviders
Can you make it? Let me know!
OKAY, enough admin. Let’s talk everyone’s favorite topic: AI readiness. |
Was this email forwarded to you? |
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What would you rank as the top 2 or 3 signals to know whether your org is ready for AI implementation (e.g., leadership buy-in, data maturity, budget, clear use cases)? Please feel free to elaborate! |
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Jeanne Duke - Fractional CAIO
“Our AI implementation team starts with a presentation and evaluation at the C-level. Any org is ready at any time. The question is ‘what are we ready to do now to start?’” |
Jayesh Srivastava - Chief of Staff
“1. Definitely leadership buy-in, but across all domains (not just tech or product), with the shared understanding of how AI can improve value to the org (e.g., reduce costs via efficiency, increase revenue by generating more leads, etc.).
2. A clear set of shared principles that guide AI discovery & transformation so the org isn't caught chasing shiny objects or bringing a half-baked solution to a fake problem.
3. Sober decision-making around build / partner principles so the org is internally investing where it matters and partnering where it makes more sense.” |
Anonymous “What type of AI? Ambient AI to support clinicians reduce administrative burden and get billing out the door faster? Look at your revenue cycle data. Diagnostic AI? Much bigger question, what are patient outcome quality metrics vs. budget ability?”
Hospitalogy members can join this discussion here. Not a member yet? Apply to join here. |
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James Hereford - President and CEO, Fairview Health In an upcoming ep, I sat down with James for a wide-ranging convo about Fairview’s strategy, including where they’ve been able to win with AI. Three quotes I loved:
The People-Process-Technology Triad:
“The place where we usually make the mistake is we fall in love with the technology and forget the people in the process part. So those three have to be in concert, right? The people, the process, and the technology have to work together.”
His biggest implementation failures:
“Paving the cow paths,” AKA, deploying tech without fundamental workflow transformation. “You can’t [throw] the technology down and then [wonder] why nothing happens. Why it doesn't get picked up and leveraged in the way that was anticipated.”
Giving employees agency: “The question for us is how much are we going to lean into this and really be an active agent versus we're going to be a recipient and be a victim of the change.”
Wanna listen when it drops? Subscribe to the pod here. |
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*This read is brought to you by one of my brand partners who help make this newsletter possible! |
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Bristol Myers Squibb has announced a strategic collaboration with Microsoft to accelerate the early detection of lung cancer using advanced artificial intelligence. Under the partnership, FDA-cleared radiology AI algorithms will be deployed through Microsoft’s Precision Imaging Network, already used by more than 80% of U.S. hospitals, to analyze X-ray and CT images for hard-to-detect lung nodules and support clinicians in identifying potential early-stage disease more quickly. The initiative aims to improve diagnostic accuracy, reduce radiology workload, and expand access to early detection—especially in medically underserved communities such as rural hospitals and community clinics—helping guide patients into appropriate care pathways sooner.
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BrightInsight announced a new investment round of $13M from existing and new investors including Eclipse, General Catalyst, Insight Partners, Mayo Clinic, and New Leaf Venture Partners. The company says this new capital will accelerate development of BrightInsight’s AI-enabled medication persistence and adherence solutions and enable rapid scalability of high-impact programs.
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Three large health systems achieved measurable efficiency, financial, and clinician satisfaction gains after deploying Suki’s AI-powered ambient clinical documentation platform in ambulatory settings. Across all three organizations (FMOL Health, McLeod Health, and Rush University System for Health), clinicians reduced time spent on documentation and after-hours work, improved evaluation and management coding accuracy, and generated incremental revenue. Request the full January 2026 KLAS “ROI Validations” report here.
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Thanks for the read! As always, I’d love to hear your thoughts. And if you’d like to be featured in a future newsletter, asking or responding to Qs in the Hospitalogy Membership is the quickest way to do it. – Blake |
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