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Happy Thursday, Hospitalogists! Look out - HealthDataAtlas is making a hostile takeover bid for Epic! Gotta be the LinkedIn post of the week for sure. Should we make that a series? On to this week's Thursday roundup, full of takes on AI, contract labor, and more - enjoy! |
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An AI hot take with Rik Renard, PM at Sword Health | OpenEvidence vs. Doximity: Playing Dirty? |
This editorial was brought to you in collaboration with THE Rik Renard, Head of Strategy & Product at Sword Intelligence. Go connect with him so he can hit all of his content goals and dreams. The AI land grab - and subsequent spats - continue across verticals. OpenEvidence went from a $1B valuation to $3.5B in 5 months. So naturally, last week, Doximity bought out their much smaller competitor - and now they're all in a legal feud. OpenEvidence is positioning itself as the single source of truth for medical decisions. In essence, it's ChatGPT meets UpToDate. They've locked down partnerships with 13 major scientific journals (including JAMA) and claim that 40% of US doctors already use their platform. Doximity - once the "LinkedIn for doctors," but now much more (but still monetize exclusively through drug ads, one of the best business plans around) - acquired Pathway for $63M ($26M cash, $37M equity). Pathway is essentially an OpenEvidence clone, and according to the Health Tech Nerds rumor mill, they're generating maybe $1-2M ARR today. That's a 30x revenue multiple. Cheap in today's healthcare AI economy, right?? Doximity already has "Doximity GPT" (Jared at Healthcare Huddle has been breaking down some of Doximity's AI features) for summarizing charts and reports and has leaned into product distribution to keep physicians on-platform and monetize that engagement by providing direct value through AI tools. So Pathways fits this strategy very nicely. And the strategy seems to be working - Doximity noted 'record engagement' on platform during its most recent quarterly results. But what's amusing is that, as Brendan Keeler reported, OpenEvidence sued both Pathways AND Doximity for allegedly "stealing" their system prompt. |
So…the signal here is that Doximity realized it can't beat OpenEvidence given its head start and proprietary platform, so naturally they bought the company that also can't beat OpenEvidence (see example above). No, Doximity's bet is on something else entirely. They're betting that their distribution moat can overcome OpenEvidence's first-mover advantage in AI-enabled medical decision support. Now we have two distribution powerhouses on a collision course. OpenEvidence reportedly retains 40% of physicians through product/marketing superiority. Doximity owns massive reach through platform dominance. Both want to capture the critical moment when doctors need answers. In Belgium we say "a cat in trouble makes weird jumps," but maybe this cat knows exactly where it's landing. |
State of Hospital Labor in Q2: Hitting the Bottom? |
After wrapping up Q2 on Tuesday I thought it'd be interesting to look at the state of the labor market - most notably, contract labor expenses in 2025.
Back in 2020 and 2021, we had this whole thing called a pandemic which spiked travel nursing rates. Staffing companies had their time in the sun while hospitals, normally paying 2-5% of salaries in wages in premium pay, saw those sums spike significantly.
Since then, the public operators have been reporting steady, sequential drops in contract labor as a % of SWB as you can see in the chart below: |
Though in 2025, it appears as if the labor market has (finally) bottomed out and found its new normal. Tenet in particular has found a new LOWER baseline normal while the rest of the public operators seem to have reverted back to the mean. There wasn't much discussion around labor or labor market dynamics in Q2 given all of the hubbub around policy, but I do think it's one of the more noteworthy things happening in hospitals across the country. Here to chime in on broader labor dynamics is Jacob Laufer, COO at ShiftMed, who I've been having some good conversations with recently. His firm works with a number of large systems and he had a good perspective on the state of hospital labor in 2025 today: - If you zoom out, hospital labor is in a far more stable place than the chaos of 2020–2022, but the playbook for winning in 2025 looks nothing like it did then. Everyone talks about cutting contract labor, but across multiple health systems I'm seeing premium pay, overtime, bonuses, incentives, quietly becoming the bigger cost driver, with continued increases in average hourly wages, all while public policy is pushing for higher productivity in the face of upcoming Medicaid cuts.
- Underneath those numbers is a seismic shift in the clinical workforce profile. In 2020, 43% of nurses were over 55; today it's just 18%. Gen Z now accounts for 1 in 5 nurses, and they're not looking for 13-week travel contracts, or even full-time. They want flexible shifts and control over how and when they work. This generational change is redefining what workforce strategies need to look like.
- For health systems, the "new normal" is managing 20K–40K+ open shifts each month. Without automation, that's chaos. Forward-thinking organizations are moving beyond basic centralized scheduling and staffing to build workforce command centers: AI-augmented hubs that integrate with any WFM platform, route the right clinician to the right shift in real time, manage float pools, track credentialing and compliance automatically, and drive timeclock adherence to near 99%.
- The goal isn't to replace people, it's to replace manual, slow, and siloed processes with intelligent infrastructure that gives hospitals operational control and cost savings while giving clinicians autonomy and career growth.
- Imagine a nurse being presented with the 10 best shifts for their goals that week, or a CT tech being nudged toward their next certification based on demand, that's where we're headed.
Bottom Line: the future of hospital labor will be defined by flexibility, automation, and personalization, not just more bodies on the floor. And it's already paying off: our latest analysis of labor cost as a percentage of revenue shows early adopters of these strategies trending toward the low 40% range, with many expected to hit the mid-to-high 30s. Benchmarks that, until recently, most systems thought were out of reach. |
Adding to Jacob's commentary above, AI's time to drive additional operating leverage - both in providing more flexibility for Gen Z nurses or developing new infrastructure. Across the country, health systems are testing and piloting new novel use cases for AI and agentic AI, and they're about to have a material impact on labor productivity. Today, entry-level clinical labor presenting the biggest opportunity to drive productivity and efficiency. There's a key theme playing out: deploying the right solution enables that labor pool class to work at the 'top of their license' - simplifying the 80%, lower complexity stuff so that the physician, documentation specialist, or anyone in between can do the more complex stuff more often, and leave the low-hanging fruit, or aggregation, or documentation, or whatever repeatable workflows that can be taken care of by AI. - AI-enabled documentation → CDI team focuses on higher complexity codes or review
- Contact center → handles things like Epic MyChart password changes and hands off nuanced stuff to humans
- Systems of intelligence → data aggregation breaks down siloes and creates more enterprise-wide thinking.
Couple these pilots and existing use cases along with other expense and topline pressures and we may be creating a pressure cooker for leadership to lean on AI and adopt it into organizations even faster. With the current labor market, will we see hospitals push the needle even further on efficiency gains? What do you guys think? Where are you seeing AI having the biggest impact in hospital labor? |
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That's all for this week - hope you guys have a great weekend, relax, watch some golf or gear up for football season. One month til the Hospitalogy VBC retreat! |
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| Thanks for the read! Let me know what you thought by replying back to this email. Did we get too spicy, or just the right amount of heat? — Blake |
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