healthsystemCIO Weekly Roundup: Guerra on Propagation, CMS on Rural Health, Podesta on Career Moves, and More

Letter from the Editor

The Power of Propagation

Healthcare is well acquainted with learning from mistakes. To advance that idea, improvement efforts have extended beyond actual errors to those narrowly averted.

This is known as a “near miss” (also referred to as a “close call” or “good catch”). Many health systems encourage staff to file near-miss reports—often anonymously or confidentially—through internal incident-reporting tools and, in the U.S., via federally recognized Patient Safety Organizations.

Operationally, frontline clinicians document what happened, contributing factors, and how the miss was caught. The payoff includes earlier hazard detection, learning at scale, and a stronger “just culture” in which people speak up before harm occurs.. In short, anonymous or protected reporting turns close calls into actionable intelligence that improves reliability across the system.

The propagation of knowledge from mistakes, near misses, and discovered flaws is crucial.

Well before April 26, 1986, Soviet specialists had evidence that the RBMK design used at Chernobyl possessed hazardous traits—most notably a strongly positive void coefficient at low power and a control rod design that could momentarily add reactivity at the start of insertion. Earlier incidents at Leningrad (1975) and Chernobyl Unit 1 (1982) had already revealed significant weaknesses, yet the remedies amounted to limited or piecemeal changes. Even proposals to modify the control rods to eliminate the water column under their graphite displacers—measures that might have prevented the Chernobyl surge—were not implemented across the fleet of Soviet reactors.

The deeper problem was organizational. Post-mortem studies concluded that the Soviet nuclear system suffered from poor feedback from operating experience and inadequate communication among designers, manufacturers, operators, and regulators, with unclear lines of responsibility. As a result, lessons from prior RBMK events were not disseminated effectively, and operating procedures left critical issues which were confusing for crews under pressure to meet production targets. Those systemic communication failures, layered atop the RBMK’s design sensitivities, created the conditions in which Chernobyl’s late-night test turned into a disaster of historic proportions.

It is clear that, when it comes to mistakes and flaws, disseminating information is key to systemwide improvement. History also shows that the same dynamic applies on the other side of the ledger.

In “Guns, Germs & Steel,” Jared Diamond argues that innovation spread faster across Europe and Asia largely because of geography. Eurasia’s broad east-west axis links regions with similar latitudes—meaning comparable climates, day lengths, and seasons. Crops, livestock, and the know-how to use them could move along this belt with relatively modest adaptation. Steppe corridors and contiguous temperate zones helped writing, metallurgy, and other technologies radiate from early centers such as the Fertile Crescent to the Mediterranean, India, and China, creating dense exchange networks that reinforced further innovation.

By contrast, Africa and the Americas are oriented north-south, forcing ideas and domesticated species to cross sharply different ecological zones. The Sahara Desert, Congo rainforest, and Kalahari formed formidable barriers within Africa, while the Americas were segmented by the narrow Isthmus of Panama, the Andes, the Amazon, and vast deserts. Each transition demanded new adaptations to distinct climates and diseases, fragmenting trade routes and slowing diffusion. Diamond’s core claim is not that societies outside Eurasia were less inventive, but that their continents’ geography hindered the spread of successful ideas, whereas Eurasia’s geography, on balance, did not.

And that brings us to today’s AI-powered healthcare environment. In my interviews for our Special Report on the topic, a major theme resonated: put these tools in the hands of your brilliant co-workers; add guardrails so they can’t break too much; let them develop clever solutions to the problems that are bogging them down; surface the best of those ideas and disseminate them across the organization.

In a yet-to-be-published interview, Peter Pronovost, MD, PhD, Chief Clinical Transformation Officer at University Hospitals, described how he is applying properties found in fractals to organizational design so that good ideas don’t depend on chance to spread. Pronovost argued for governance that actively moves what works across settings.

His “fractal” rule is simple: at every higher level of the enterprise, there must be a table at which every lower level has a seat; if that table becomes crowded, create another branch. “We don’t have dissemination of best practices by chance—we build a structure or the scaffolding to allow it to flow,” he said, emphasizing a culture where anyone can contribute regardless of pedigree.

Operationally, this creates repeating units of decision-making—identical in shape but different in scale—so that innovations proven on a unit or in a rural hospital can surface, be vetted, and propagate systemwide. It complements tool rollouts and guardrails (for example, prompt libraries or AI use policies) by ensuring there is a standing pathway for bottom-up ideas to meet top-down oversight. In Pronovost’s model, the fractal pattern supplies both the mechanism (who sits where, when, and with whom) and the mindset (safety to speak up) needed for rapid, reliable diffusion of best practices.

It follows that your job today is not only to be the trusted adviser guiding the infusion of AI into every aspect of your organization, but also to manage the dissemination and propagation of effective uses of those technologies. First, create the groundwork to let a thousand flowers bloom; then manage the harvesting of the most hardy and beautiful for planting elsewhere. Do this assiduously, because allowing something remarkable to wither in darkness is a near miss just the same.

Midnight in Chernobyl; by Adam Higginbotham

Find this column online

Thoughts on this piece? Drop me a line aguerra@healthsystemCIO.com

Special Report – AI

Health System Leaders Developing the Frameworks to Let AI Flourish

Health systems are moving beyond AI pilots to an operating model centered on measurable outcomes, fit-for-purpose governance, and disciplined change management. In this special report, healthsystemCIO Editor-in-Chief Anthony Guerra spoke with leaders from UCI Health, Duke, Mercy, Mayo Clinic Platform, John Muir Health, Cedars-Sinai, and Mount Sinai who described single-front-door intake, risk tiering, time-boxed pilots, and human-in-the-loop oversight. Early value concentrates in administrative work and call-center automation, while clinical uses advance carefully. Data quality, workforce activation, and swap-ready architectures enable sustained enterprise scale.

Experts Behind the Report -

News, Articles & Columns

CMS Opens $50B Rural Health Transformation Funding With Tech Modernization in the Spotlight

CMS opened a $50 billion Rural Health Transformation Program directing $10 billion annually from FY 2026–2030 to modernize rural care with technology. Half of funds are evenly allocated to approved states; the rest awarded based on impact. Applications due Nov. 5, 2025; awards Dec. 31, 2025. For CIOs, priorities include cybersecurity, HIPAA-aligned identity, EHR/EMR interoperability via FHIR APIs, broadband and telehealth expansion, cloud resilience, zero-trust architectures, and analytics/AI-enabled care coordination, via coordinated state-led implementation plans.

The CIO’s Playbook for Career Transitions

healthsystemCIO’s webinar “Strategic Transitions: The Do’s and Don’ts of Executive Career Moves” offers guidance for IT leaders on timing a move, engaging recruiters, reading culture, and evaluating turnaround realities. Panelists Chuck Christian, VP of Technology/CTO, Franciscan Health and Chuck Podesta, CIO, Renown Health; stress clear mandates, candid conversations, and governance clarity—reporting lines, budgets, and appetite for AI. Advice centers on sequencing early wins, building successors, and avoiding brittle leadership dynamics.

Partner Perspective: Artera’s de Zwirek Says IT Leaders Must Commit to Becoming AI Experts; Outlines Three Paths to Deploying Agents

Guillaume de Zwirek, CEO, Artera, says that health-system IT leaders must become fluent in AI to remain trusted advisors as adoption accelerates. In a wide-ranging interview, he outlines three paths—build, buy, or partner—while pointing to call-center automation as a near-term win with measurable ROI. de Zwirek emphasizes rigorous governance, including SOC 2/HITRUST, MCP-guarded integrations, and “LLM-as-judge” testing, plus executive dashboards tracking accuracy, handoffs, and latency. Starting with appointment verification, he says, builds muscle to scale responsibly, enterprise-wide.

The SANDBOX Act: A Turning Point for Responsible AI Innovation?

Taylor Rhoades, Program Director, Responsible AI at Mercy, argues that regulatory uncertainty stalls AI adoption in healthcare and highlights the proposed SANDBOX Act as a path forward. The bill would enable time-limited, renewable waivers to test AI under guardrails, coordinated by the Office of Science and Technology Policy with transparency requirements. Rhoades weighs benefits and trade-offs—equitable access, monitoring rigor, and federal–state alignment—and defines success as safer innovation, case studies, and inclusive participation that builds trust.

Physician Informaticists/Builders: The EHR Optimization Secret Weapon

Physician informaticists/builders bridge bedside care and EHR design, writes Tiffany Kuebler, Medical Director of Clinical Informatics, University of Maryland Medical Center. A resident bypassing medication reconciliation stalled discharges; clinician-builders traced the issue and taught the fix. Because they practice and build, they translate nuance, collaborate with analysts, and, in Epic, can configure tools. As AI proliferates, Kuebler urges clinician-led evaluation and implementation to improve safety, efficiency, and adoption—citing evidence that clinician champions drive higher uptake.

AI in Healthcare: Revolution or Evolution? Why Clinicians Don't Care

Muhammad Siddiqui, Chief Digital & Information Officer, Reid Health, argues clinicians judge AI by workflow relief, not vendor theatrics. Reflecting on Oracle Health’s “built-in” pitch—semantic models and evergreen data—he notes Epic has long embedded similar capabilities, citing Comet’s 100-billion-event corpus and 2024 growth. He casts the choice as evolution versus revolution, urging partnerships that prioritize integration, reliability, and outcomes. Success is measured by reduced administrative burden, faster charting, seamless EHR fit, and frontline trust—not slogans.

Leveraging Native Integration, Epic Gets High Marks in Patient Messaging, KLAS Finds

KLAS’ 2025 patient-communications brief places Epic Hello World in the lead, with customers crediting tight Epic integration, stronger MyChart preference control, and fewer no-shows. Outside Epic, organizations report EHR-integration gaps that force manual workarounds. Artera, Luma Health, and Upfront are praised for flexible workflows and mature texting, though pricing and usability concerns persist. Market signals include platform consolidation, patient-centric design, and interest in agentic AI and contact-center solutions, with KLAS planning a patient-engagement platform segment.

Will Slowing Down Make You More Productive?

The Mayo Clinic Platform's Dr. John Halamka & Paul Cerrato write that slowing down can improve productivity. They cite evidence favoring Type 2 reasoning over fast heuristics, fewer errors with shorter intern hours, and daytime naps boosting cognition. The “speed-accuracy trade-off” and the “art of noticing” underpin their case, echoing Ellen Langer’s mindfulness research.

Brilliant Bites