As regional health systems prepare to transition patient panels into the new CMS ACCESS model, hospital executives are discovering a painful operational reality: you cannot execute a modern population health contract on an antiquated fee-for-service EHR chassis.
When health systems attempt to scale continuous remote physiologic monitoring across high-risk cardio-kidney-metabolic populations, the sheer volume of biometric telemetry creates catastrophic clinical alert fatigue. Attempting to force continuous data streams into legacy EHR inboxes forces highly compensated advanced practice providers to spend hours hunting for actionable data amid a sea of benign fluctuations.
You cannot cure a broken delivery model simply by digitizing it. To survive the margin compression of the next decade, hospital C-suites must abandon single-point digital solutions and adopt a unified, governed architectural strategy.
The imperative of responsibly-governed AI
To survive the transition to continuous care, health systems must establish strict physician governance over the deployment of artificial intelligence. In a value-based architecture, AI cannot function merely as an ambient scribe or an autonomous decision-maker. It must act as a strict clinical noise filter.
Health systems must deploy infrastructure that automatically suppresses benign biometric fluctuations and escalates only actionable, complex trends. By establishing a rigorous “Human-in-the-Loop” architecture, systems eliminate the manual data hunt, ensuring continuous monitoring scales safely without overwhelming the clinical staff or compromising patient safety.
Forcing collaboration: the economic engine of co-management
The CMS ACCESS model does not just change how we bill; it fundamentally changes who we work with. Engaging with these new value-based frameworks is a system-wide mandate.
Crucially, CMS designed the ACCESS model’s co-management G-codes with strict guardrails: these payments are generally not available for referrals within the exact same organization. This is a deliberate, structural mechanism designed to break down the competitive silos between massive health systems and independent community clinics — silos that should have come down long ago. It forces an economic partnership.
When a health system securely shares filtered data insights with an external community provider, it creates a powerful dual-engine:
- For the independent primary care providers: captures sustainable, recurring revenue through co-management G-codes.
- For the health system: actively mitigates downside risk by keeping the attributed patient stabilized upstream.
By breaking down these legacy silos, digital oversight transforms from a territorial dispute into a collaborative economic engine.
Stabilizing the clinical workforce: Ultimately, technology should never reduce a clinician to a cog in a data-processing machine. Ironically, this has happened over the past decade prior to AI. By utilizing governed AI to filter the noise, health systems instantly return hours of clinical capacity to their nursing staff and APPs.
This stabilization of the workforce is critical to addressing systemic burnout. Instead of spending their shifts drowning in administrative dashboards, our clinical teams are freed to practice the actual art of medicine. They can extend their reach, focusing entirely on the high-touch, complex interventions that keep vulnerable populations out of the emergency department.
The executive mandate: The transition to downside risk and outcome-aligned payments requires more than just new billing codes. It demands that health systems evolve their digital architecture. By deploying physician-governed AI, breaking down institutional silos through co-management, and prioritizing workforce stabilization, hospital executives can build a scalable engine that proactively restores health rather than passively managing its decline.
Dr. Kohler is the founder and CEO of US-LTN managed services organization and the medical director of Rappahannock Health Corp. in Washington, Va., and Litchfield Health. He also serves as the director of the lifestyle medicine distinction track at the Yale School of Medicine in New Haven, Conn. The views and opinions expressed in this article are solely his own and do not reflect the views, policies or positions of any affiliated hospitals, health systems or academic institutions.
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.
