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 Happy Thursday, Hospitalogists. Today’s piece is a great guest post! I’m handing the proverbial mic over to two leaders who see healthcare AI from the health system and the technology side:
Everyone has an opinion on healthcare AI right now, but few are making the case that the real bottleneck is neither the models nor the vendors. It’s whether the person at the top treats AI as their own job. Governance is top of mind for every exec thinking about AI deployment these days. Steve and Justin argue the organizations that pull ahead won’t be the ones with the fanciest tools, since most systems will have access to similar tech anyway. They’ll be the ones whose leaders actually lead. Own it. I love the perspective. They lay out 4 leadership commitments and 4 things CEOs can do this week, so I’ll get out of the way and let them cook. Enjoy the guest post below. Was this email forwarded to you? Sponsored by Prosper AI It’s a tough time for practice leaders. 84% of medical groups report higher operating costs than a year ago, with an average increase of 11%. Add stagnant or declining reimbursements and Medicare’s temporary 2.5% boost expiring at the end of 2026, and practices are staring down serious margin pressure. I read a new report from Prosper AI that proves timely. It quantifies how AI can help specialty practices capture demand and revenue and ensure they’re paid for the care they deliver by pulling 4 levers: converting missed calls to appointments, re-engaging existing patients, preventing avoidable denials, and recovering unpaid patient balances. CEOs: AI is Your Job, Not Your CIO’sBy Steve Mackin, MBA, CEO of Mercy; Justin Norden, MD, MBA, MPhil, CEO of Qualified Health As the CEO of a major healthcare system, and the CEO and founder of Qualified Health, we are deeply invested in the principled application of AI in healthcare delivery. Our country’s healthcare system is quickly approaching a crossroads. Over the next three to five years, organizations that adopt AI in a thoughtful, organization-wide way will pull ahead of the pack, improving efficiency and advancing how care is delivered to those who need it. Those organizations that can’t or don’t adopt will face growing financial strain as reimbursement pressure, staffing shortages and rising operating costs continue to mount. The deciding factor won’t be technology itself, as most health systems will have access to similar tools. What will set organizations apart is something far more familiar: leadership. Why Delegation FailsMany CEOs have approached AI as a technology project they can hand off to others to implement. But AI is more than an IT rollout: it’s a people issue in disguise. Success requires frontline caregivers to abandon old workflows, change familiar routines, learn new systems and, at times, trust AI-generated insights instead of long-standing habits. Add to this the chronic worry that AI will threaten job security, and it becomes clear why caregivers may struggle to embrace this sea change. That’s why AI can’t simply be delegated: CEOs and senior leaders must take an active role in creating a culture where people feel safe to adapt and learn. Four Leadership Commitments that Make a DifferenceAI transformation only works when senior leaders stay directly involved and focus on people as much as technology. We believe there are four mandatory commitments: 1. Align the Entire OrganizationOrganizations that treat AI as a series of department-level projects end up with disconnected tools that don’t work well together. Executives must champion enterprise integration, with all leaders agreeing on shared goals and measuring success in the same way. At Mercy, we’ve learned that scaling only works when the platform is shared and consistent across care locations. 2. Lead Cultural Change in Plain SightThe real barrier to getting value from AI isn’t technology, it’s skepticism. Leaders need to use the tools themselves and articulate the “why.” When teams see real benefits, like reduced documentation through tools like ambient listening, they’re more likely to engage. 3. Hold the Organization AccountableWhen AI is treated like a side project, results fall flat. Leaders must set expectations, track progress and make course corrections quickly based on what the data shows, not internal politics. At Mercy, if something isn’t delivering, we shut it down. When something shows value, we invest more and expand it. And once we can prove value, we scale it quickly across the organization. 4. Choose and Manage the Right PartnersMost healthcare organizations are unable to build comprehensive AI solutions on their own. Choosing the right partners is critical. These decisions must be made at the executive level as they can shape long-term capability, culture and results. Four Actions CEOs Can Take This Week
The Real Opportunity: Leading People, Not Implementing TechnologyHealth system leaders face a defining moment: lead the transformation needed to improve how your organizations operate or risk falling behind as others move ahead decisively. This is not a technology decision: it's a leadership one. The organizations that succeed will be those that best lead their people, regardless of who has the most advanced tools. Blake’s quick take: As noted, governance and leadership and the human component of AI and technology is paramount to future organizational success. Part of this process is understanding how multi-disciplinary, cross-function teams will work together in the future. How involved should your CFO be in other domains, and vice versa? Successful cross-domain engagement will result in better enterprise-wide thinking and those health systems will lead on consumer-centric strategies. About the AuthorsSteve Mackin Steve Mackin, president and CEO of Mercy, leads one of the 15 largest U.S. health systems, with 55 acute care hospitals, more than 1,000 physician practices and more than 50,000 caregivers. Mercy invested early in technology and innovation to transform the model of care and is continually demonstrating improved quality, safety and patient experience as it builds a platform of care with trusted partners. The health system is a national leader in AI and is working with Mayo Clinic to create a global healthcare database that helps identify and treat diseases earlier. Mercy's collaboration with Microsoft focuses on integrating AI into patient care environments, enabling more predictive and personalized care. As Mercy prepares for its third century of care, recent successes include a 30-year affiliation agreement with the Alice L. Walton Foundation, partnerships advancing precision medicine and large-scale implementation of AI tools that reduce clinician burden and expand patient access. Mercy’s ACO ranks among the top three in the country for patients served and total taxpayer savings. Justin Norden, MD, MBA, MPhil Justin Norden is the co-Founder and CEO of Qualified Health, a health technology company helping health systems deliver safe and scalable AI by combining workflow automation, clinical safeguards and agent development tools with real-time monitoring and end-to-end governance. He is also an adjunct professor at Stanford University School of Medicine, where his work focuses on artificial intelligence in healthcare and digital health. Previously, Dr. Norden was a partner at GSR Ventures, a venture capital firm with $4 billion in assets under management, where he invested in healthcare AI companies. Prior to that, he founded and served as CEO of Trustworthy AI, which was acquired by Waymo, Google’s self-driving technology division. Dr. Norden earned his MD from Stanford University School of Medicine, his MBA from Stanford Graduate School of Business, an MPhil in Computational Biology from the University of Cambridge, and a BA in Computer Science from Carleton College. Sponsored by Capacity Health Every patient's next step shapes the entire hospital's capacity. Capacity Health continuously updates a model of every patient, connecting history, labs, imaging, treatments, and notes across the entire care team's decisions and handoffs. It forecasts operational needs hours to days ahead and recommends next steps for clinician review. Every clinical decision and patient outcome informs the operational model, continuously refining predictions of hospital-wide needs. The same architecture models patients alongside shared resources, from CT queues to beds and staffing, helping teams prioritize care, match needs to resources, and improve throughput. See your ED through the Capacity Health model. MISCELLANEOUS MADDENINGS Florida this week! If we don’t beat Florida, we don’t deserve to be in the playoff picture. Simple as that. We’re not as good as we thought. Let’s see how we bounce back after an emotional loss with a lot of psychological baggage and questions to answer. Horns by 10! I also wanted to sincerely thank the kind, wonderful folks at Saint Francis Health System for hosting me during their executive leadership retreat this week. I felt right at home and really enjoyed the engaging dialogue. Thanks for the read! Let me know what you thought by replying back to this email. — Blake | ||||||
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