This year’s theme, Bridging the Gap: Digital Health and AI for Smarter Care, Stronger Teams, and Sustainable Healthcare, centers on the practical deployment of AI to close gaps in access, reduce administrative burden, and tackle the chronic disease crisis at scale.
With chronic conditions accounting for 90% of the $4.5 trillion in annual U.S. healthcare spending, the stakes couldn’t be higher—and the time for smart, actionable innovation is now. CTRC is leading the charge, equipping healthcare organizations with the knowledge, tools, and training to deploy AI responsibly, maximize digital investments, and ensure their teams are not just ready—but confident—navigating this new era.
You’ll hear from national thought leaders, technologists, and frontline staff who are turning today’s challenges into tomorrow’s breakthroughs including in rural California. Sessions will spotlight AI-driven efficiencies, workflow automation, specialty care access, and whole-person care models, all tailored to high-burden, high-cost conditions like diabetes, cardiovascular disease, and obesity. Whether you’re designing the future or adapting to it, this summit is your chance to:
We have secured sponsorship to ensure access for all provider and their team members. Registration is free. Transformation starts here.
To help you plan your summit experience, please note that registration is session‑based. Attendees must register individually for each session they plan to attend. Please use the registration links listed below to secure your spot.
Healthcare organizations are being asked to do more with less: expand access, protect workforce capacity, and sustain care delivery under mounting operational and financial pressure. This opening remark frames digital health and AI as part of a broader ecosystem transformation—not a collection of tools. The session connects strategy to practical leadership: how to prioritize initiatives that reduce friction, strengthen teams, and support long-term sustainability. Participants will hear how system-level trends (access constraints, workforce strain, and sustainability requirements) shape implementation choices and why governance, measurement, and partnership models matter as much as the technology itself.
Rural providers across California are facing persistent workforce shortages, rising operational pressures, and increasing expectations to deliver more care locally with limited resources. In response, California has launched the California Rural Health Transformation Program (CalRHT)—a statewide initiative supported by more than $233 million in federal funding for the initial budget period—to strengthen rural healthcare capacity through workforce development, technology modernization, and new care delivery models.
This opening keynote will outline what California has publicly announced about CalRHT and how the state is approaching telehealth, remote patient monitoring (RPM), and other technology‑enabled services as essential infrastructure for rural care delivery. The session will describe California’s emphasis on regional hub‑and‑spoke care networks, digital tools that extend workforce capacity, and technology investments designed to meet rural communities where they are—geographically, operationally, and digitally.
The keynote will also frame how state policy direction aligns with the CTRC Summit 2026 focus on digital health, emphasizing strategic sequencing, readiness, and sustainability. Participants will gain clarity on how California expects rural organizations to align digital health strategy, workforce planning, and funding decisions to move beyond short‑term initiatives toward durable, adaptable care delivery models.
Generative AI is moving rapidly from research settings into everyday clinical environments—but successful adoption depends far less on the technology itself than on how it is designed, integrated, evaluated, and governed within real care systems.
In this closing keynote, Dr. Chen draws on lessons from Stanford’s applied research and early deployments of generative AI in healthcare to examine what it takes to move from promising demonstrations to meaningful, safe, and sustainable use. Rather than focusing on speculative futures, the session centers on near-term realities: how care teams interact with AI tools, where generative systems reliably add value, where they introduce new risks or burdens, and how organizations can learn responsibly as they scale.
The talk frames generative AI as a sociotechnical capability, not a plug-and-play solution—requiring deliberate attention to workflow fit, workforce readiness, evaluation methods, and governance structures. Participants will leave with a clearer understanding of how to prioritize use cases, support clinicians, and establish guardrails that enable learning and improvement over the next 6–12 months.
Chronic disease care happens far beyond the exam room—particularly in Federally Qualified Health Centers, where patient outcomes are shaped as much by daily conditions as by clinical encounters. This session spotlights applied, real-world approaches to extending care between visits without increasing clinician burden.
Drawing on Dr. Magan’s hands-on experience implementing chronic care models in FQHC settings, the session explores how telehealth, remote monitoring, and AI-enabled workflows can support proactive, team-based care for complex populations.
The speaker focuses on practical system design: how to integrate digital modalities and supportive services into daily workflows; where automation adds value versus where human connection matters most; and how to coordinate across clinical, nutrition, and care management roles. The session emphasizes measurable impact—patient engagement, clinical outcomes, utilization, and staff workload—grounded in lessons learned from implementation, not theory.
Digital health has moved firmly into the mainstream—but long-term sustainability still hinges on how federal policy and Medicare payment pathways are evolving. This session offers a national, bigpicture view of where digital health policy is headed and what those shifts mean for organizations designing care models today.
Featuring national experts in telehealth, remote patient monitoring (RPM/RTM), Medicare payment, and AI policy, the discussion will cover the major federal forces shaping the next phase of scale: the stabilization of Medicare telehealth, ongoing refinement of RPM and RTM pathways, the emergence of outcomes aligned models such as CMS ACCESS, the FDA’s TEMPO pilot for technology enabled chronic care, and the growing integration of AI into federal health policy and reimbursement conversations.
Rather than focusing on code-by-code updates, the session emphasizes directional signals: how Medicare is moving from episodic, visit based reimbursement toward longitudinal, technology supported care; where accountability is shifting from federal oversight to provider led design and evaluation; and what payers increasingly expect from digital programs that aim to scale.
The goal is practical clarity. Participants will leave with a shared understanding of what is becoming durable, what remains in flux, and how to assess whether a digital service is positioned to survive beyond pilot funding—across fee-for-service, value-based, and hybrid payment environments.
As AI moves from experimentation into clinical and operational use, trust becomes the defining challenge—not just trust in the technology, but trust from clinicians, regulators, patients, and boards. This session focuses on how healthcare leaders earn that trust in practice.
Lydia Kotowski grounds the discussion in California’s evolving regulatory expectations, clarifying what state agencies are signaling around AI use, oversight, and accountability. Sylvia Trujillo situates those expectations within the broader health IT and compliance ecosystem, connecting AI governance to familiar structures such as quality, safety, privacy, security, and clinical operations.
Rather than treating regulation as a barrier, the session reframes it as a design constraint that, when handled well, enables scale. Speakers translate policy and trust principles into concrete actions CEOs and clinical leaders can take now: defining risk categories, setting minimum evidence thresholds, establishing ownership and escalation paths, and monitoring performance over time.
The emphasis is pragmatic and leadership focused. Attendees will leave with a clear sense of how to prepare their organizations—and their clinicians—for AI that is auditable, defensible, and usable in real clinical settings, without building a research lab or slowing innovation to a halt.
Rural hospitals and clinics are under pressure to modernize care delivery while navigating thin margins, workforce shortages, and limited implementation capacity. In this fireside chat, rural leaders share candid perspectives on what is driving sustainability in digital health—and what is not.
The conversation features Marshall’s digital health optimization journey, as Martin Entwistle discusses how Marshall is pursuing a rural led regional network that blends telehealth, remote monitoring, and hybrid care models in partnership with the State of California. They will reflect on early design choices, tradeoffs, and lessons learned as they move from concept to implementation—particularly around workforce readiness, governance, and keeping care (and revenue) local.
Jeff Dunbar brings a complementary statewide lens, sharing what he is hearing and learning from rural providers across California about adoption barriers, sustainability inflection points, and the conditions under which digital health becomes a stabilizing force rather than an added burden.
Together, the panel focuses on practical, experience-based insights: how rural organizations prioritize use cases, structure partnerships, align digital tools with real staffing models, and avoid one-off pilots in favor of durable, network-based approaches.
Why do some AI tools meaningfully improve clinical care—while others quietly fade into the background or increase burden? This panel brings together two leading physician researchers whose work has shaped how health systems understand clinical reasoning, decision support, and the real-world impact of AI at the point of care.
Drawing on rigorous research and hands-on experience, panelists will examine what determines whether clinical AI is trusted, adopted, and sustained. Topics include selecting use cases that align with clinical judgment, integrating AI into everyday workflows without increasing cognitive load, and designing systems that support—not replace—human decision-making. The discussion will also address where AI most often fails: unclear accountability, poor workflow fit, over automation, and insufficient monitoring after deployment.
Rather than focusing on specific tools, the session emphasizes transferable lessons from research and practice—how to evaluate claims, test AI safely in live environments, build feedback loops with clinicians, and measure both benefit and unintended burden. Attendees will leave with a clearer mental model for deciding when AI is likely to help, when it may harm, and how to design implementations that respect clinical work as it happens.

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