Since July 2025, CMS and its Innovation Center have announced a run of new value-based models, and the direction is consistent: more financial accountability, with payment tied to measurable outcomes.
A few examples:
- In its first year, ACCESS pays in full only when at least half of a practice's patients meet every required target.
- The Ambulatory Specialty Model makes participation mandatory for specialists treating conditions such as heart failure and low back pain.
- LEAD, the successor to ACO REACH, offers a global risk track that can put 100% of losses against a benchmark on the organization.
In my recent article in The American Journal of Managed Care, VBC Risk Is Outpacing Provider Readiness, CMS Must Act, I argue that this is happening faster than many organizations can build the infrastructure to meet it.
Readiness has to exist where care is delivered
Readiness usually gets discussed at the enterprise level: budgets, vendors, reporting teams. But it must also exist in the exam room, in the conversation between the clinician and her patient, because that is where a quality gap closes or stays open.
Earlier models gave organizations room to practice care management, attribution, and measurement with limited downside. The newer ones expect them to identify who needs attention, coordinate care across settings, and show measurable gains in cost and quality. Specialty groups pulled into the ASM, many with little population management experience, face the steepest adjustment. CMS is driving this now, and I expect commercial payers and Medicaid agencies to follow.
Data has to arrive as insight
On paper, organizations have access to plenty of data: claims, labs, medications, specialist notes, imaging, risk scores. Timely, high-quality clinical data is the most critical element of the transition, and the shortfall is in completeness and usability. A digital quality measure built on incomplete records returns an incomplete result, and so do predictive models. I recommend mapping internal and external data sources and favoring those that follow USCDI and FHIR.
A population dashboard can flag a care gap across thousands of patients, but closing it still often depends on someone recognizing what matters for the patient in front of them. Thus, a risk model whose output never reaches the clinical workflow does little for that patient. AI tools can provide clinicians with a longitudinal view before and during the encounter: what has happened, what may have been missed, what needs attention now, and why. Context-sensitive, patient-specific information about conditions, preferences, social needs, and risks is what lets them personalize a plan. Once this becomes part of daily workflows across an organization, population health can be impacted at scale.
Sequencing matters here. If digital measurement moves faster than operations can absorb new data flows, clinicians get buried in reporting requirements. AI earns its place when it pulls scattered clinical information together and surfaces the relevant signals without adding an administrative layer. Care between visits belongs in the picture too. Research shows patients immediately forget 40% to 80% of what clinicians tell them, so reinforcement that fits the individual, and escalates to the care team when something urgent comes up, should be part of the clinical model.
What CMS can do
Providers cannot close this gap alone. My article makes two requests from CMS.
First, fund a new generation of digital quality measures. Digitizing today's portfolio would carry over the limits of retrospective, accountability-based measurement, which cannot separate higher performers from lower ones well enough to support differential payment.
Second, pair payment models with technology and operational support. The Regional Extension Centers did this for small, rural, and underserved practices during the EHR transition, and nothing comparable has existed since. LEAD's Tech Enabler Initiative and learning forums help, though I expect them to serve practices already ahead on technology adoption more than those just starting.
Payment models, digital quality measurement, interoperability, and clinical technology have to evolve together. Asking clinicians and organizations to carry more risk comes with an obligation to give them a way to act on it.
Read the full article in AJMC: VBC Risk Is Outpacing Provider Readiness, CMS Must Act
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