Why The CMS Access Model Is A Blueprint For The Next Decade Of Healthcare

A Ten-Year Signal, Not a Ten-Month Pilot

When the CMS Innovation Center announced the ACCESS Model on July 5, 2026, many viewed it as another Medicare payment model for chronic disease management. In reality, it represents something much larger.

ACCESS is one of the clearest signals yet that healthcare is entering a new phase of value-based care. The challenge is no longer getting patient data from one system to another. It is ensuring that every new data point, from remote monitoring devices and patient-reported outcomes to social needs assessments, leads to the right clinical action at the right time.

Organizations that recognize this shift will build capabilities that extend far beyond ACCESS. Those that treat it as another compliance initiative may find themselves rebuilding the same infrastructure for every future value-based care program.

What ACCESS Actually Requires

At its core, the ACCESS Model changes what healthcare organizations are paid for. Instead of rewarding the volume of services delivered, it rewards measurable improvements in patient outcomes.

Participating Medicare Part B organizations must manage patients across one of four care tracks: early cardio-kidney-metabolic (eCKM), cardio-kidney-metabolic (CKM), musculoskeletal (MSK), and behavioral health (BH). Success is no longer defined by completing visits or delivering interventions. It is defined by whether patients actually get better.

CMS has published fixed annual payment rates for the 2026-2027 performance period, with payments varying by care track and distributed monthly. But those payments are only part of the story. Organizations receive only a portion of the reimbursement upfront. The remaining amount depends on whether they can demonstrate measurable clinical improvement and lower unnecessary healthcare spending over a 12-month period.

That changes the financial risk. Providers are no longer being reimbursed simply for delivering care. They are being asked to prove that the care produced better outcomes.

For healthcare leaders, especially CFOs, this raises an important question. Can your organization continuously measure patient outcomes, connect those outcomes to the care delivered, and report them with confidence? If the answer is no, the challenge is no longer financial. It is operational.

This is why ACCESS should not be viewed as just another CMS payment model. It is a test of an organization’s ability to turn patient data into measurable action. The providers that succeed will not necessarily have more data. They will have the systems, workflows, and operational infrastructure needed to act on that data and demonstrate its impact.

Two Organizations, One Model

Picture two organizations enrolling in the same ACCESS track on the same day.

The first builds exactly enough to pass. It stands up a narrow connection to satisfy the model’s reporting fields, hires additional care coordinators to manually track patient-reported outcome measures, and treats the reconciliation deadline as a recurring fire drill. It will likely qualify for its withheld payment in year one, at real administrative cost.

The second organization uses ACCESS as the forcing function to modernize its entire interoperability layer: normalized FHIR resources, a queryable clinical data repository, and automated pipelines that route biomarker and PROM data into the workflows that actually act on it. It spends more up front. It also owns infrastructure that plugs into the next CMS model, and the one after that, without a second integration project.

Only the second organization compounds its investment. The first will be having this exact conversation again the next time CMS opens a value-based model, because nothing it built for ACCESS survives past ACCESS.

FHIR Support Is No Longer Enough

Ask most healthcare organizations whether they support FHIR, and the answer will be yes. Technically, they are right. However, operationally, the picture is far more complicated.

The 2025 State of FHIR Survey from Firely and HL7 International found that more than 70% of organizations now use FHIR in operational workflows, showing that adoption continues to grow. But the same survey also revealed a different reality. While 79% of countries have a national FHIR implementation guide, only 20% report that it is widely used in practice.

That gap matters. Supporting FHIR and using FHIR effectively are not the same thing.

Many organizations have a certified FHIR endpoint in place, but the data behind it is incomplete or inconsistently standardized. In other cases, downstream systems rarely query the API, and clinicians continue to rely on manual processes such as PDFs, fax, email, or phone calls to move information between teams.

This is where many ACCESS implementations run into problems. The technology needed to exchange data exists, but the workflows needed to act on that data do not.

Interoperability delivers value only when it enables action. A FHIR endpoint that exists solely to meet compliance requirements is not operational capability. It becomes one only when applications, care teams, and AI systems use it to automate decisions and improve patient care.

ACCESS Demands More Than Data Exchange

One of the biggest misconceptions about ACCESS is that it is simply another data-sharing requirement. It is not. The model expects healthcare organizations to exchange structured data at the right time and ensure it can be used to support clinical decisions.

Participants are required to share structured clinical information at three key points in the patient’s care journey. The first is care initiation, when the baseline care plan, biomarkers, and other clinical information are established. The second is care escalation, when a patient’s condition worsens and timely intervention is needed. The third is care completion, at the end of the 12-month care period.

Meeting these milestones is only the starting point.

CMS allows organizations to use Direct Secure Messaging and similar technologies during the initial rollout. However, by July 2027, every ACCESS participant must connect to a CMS Aligned Network or a Health Information Exchange (HIE). More importantly, structured clinical data, including blood pressure, HbA1c, LDL-C, weight, and patient-reported outcome measures (PROMs), must be available directly within the referring clinician’s EHR workflow.

That is a much higher standard than simply sending a clinical summary. It requires data that is standardized, queryable, and trusted across organizations. The receiving system must be able to retrieve the information when it is needed and use it as part of routine clinical care.

The industry’s direction is already clear. By mid-2026, more than 71,000 healthcare organizations were connected to TEFCA through 11 Qualified Health Information Networks (QHINs), and that number continues to grow. ACCESS aligns with the same vision. It moves healthcare beyond exchanging information toward creating a connected ecosystem where structured data can be accessed, shared, and acted on across organizations.

For healthcare leaders, the takeaway is straightforward. The goal is no longer to prove that data can move between systems. The goal is to ensure that data reaches the right workflow, at the right time, in a format that enables better clinical decisions.

HRSN Is Operational Data, Not a Demographic Field

Health-related social needs are the part of ACCESS most organizations are least prepared for, because most EHR workflows still treat social risk as a checkbox rather than a tracked clinical variable. ACCESS requires universal, standardized screening and evaluates participants on documented resolution of the needs that screening identifies, not just their identification.

The technical path here already exists. The Accountable Health Communities HRSN Screening Tool covers five domains, housing instability, food insecurity, transportation, utilities, and interpersonal safety, and HL7’s Gravity Project has spent several years building the standards to make screening responses machine-readable: mapping to ICD-10-CM Z-codes in the Z55 to Z65 range and to the SDOH Clinical Care FHIR Implementation Guide, so a housing-instability finding can move between a screening app, an EHR problem list, and a community-based organization’s referral system without manual re-entry. What ACCESS adds is the requirement to prove the loop closed, not just that a referral was made, but that it reached a community organization and was resolved or documented as attempted. That is a fundamentally different capability than a screening form bolted onto an intake workflow.

From Interoperability to Automation

Interoperability moves data. It does not, by itself, change what a care team does differently on a Tuesday afternoon. The organizations that will actually hit ACCESS’s outcome targets are the ones that convert clean, queryable data into automated action: proactive outreach triggered when a patient’s remote blood pressure readings trend upward for a week rather than waiting for the next scheduled visit, automated reconciliation of PROM scores against a care plan without a coordinator manually re-entering results, and escalation workflows that route a deteriorating biomarker to a clinician the moment it crosses a threshold rather than at the next data review.

This is the actual translation of the model’s core mechanic. CMS is not paying for data exchange. It is paying for a measurable change in a patient’s condition, and the only way to produce that consistently across a population, at the payment rates CMS has set, is through automation layered on top of interoperable data, not headcount layered on top of manual review.

Where the Model Rewards Precision

ACCESS pays for outcomes, not activity, and independent evaluations of the technology participants are likely to deploy are already showing why that distinction matters. The Peterson Health Technology Institute’s assessment of digital hypertension tools found that solutions built around active medication management produced rapid, clinically meaningful blood pressure reductions that outperformed usual care, while solutions that only transmitted home monitoring data to a clinician, without the authority or workflow to act on it, did not produce meaningful clinical improvement. Monitoring without a mechanism to change the treatment plan is not the same intervention as monitoring paired with one, even though both would look identical on an adoption dashboard.

That distinction maps directly onto the eCKM and CKM tracks, where an ACCESS participant’s revenue depends on documented blood pressure and HbA1c improvement, not on how many readings a device transmitted. The same logic extends to the MSK and BH tracks: a digital physical-therapy program or a PHQ-9-tracking behavioral health platform only earns its outcome payment if the data it collects triggers an actual change in the care plan, a modified exercise regimen, an escalated referral, a medication adjustment, rather than sitting in a dashboard a care coordinator reviews once a month.

The Infrastructure That Also Makes You AI-Ready

One of the biggest advantages of preparing for ACCESS is that the infrastructure it requires is the same infrastructure needed for enterprise AI.

ACCESS is not an AI program. Yet the capabilities it demands, standardized FHIR data, longitudinal patient records, integrated patient-reported outcome measures (PROMs), health-related social needs (HRSNs), and continuous data from remote monitoring devices, are exactly what modern AI systems depend on.

Whether an organization is building an AI care coordinator, a predictive risk model, a clinical documentation assistant, or an intelligent outreach solution, the foundation is the same: clean, standardized, and continuously updated data that can be accessed across clinical workflows.

This is why ACCESS should be viewed as more than a value-based care initiative. It is an opportunity to build a data architecture that supports both today’s reimbursement requirements and tomorrow’s AI strategy.

Organizations that invest in normalized, queryable, longitudinal data for ACCESS will also create the foundation needed to deploy AI safely and at scale. Those that rely on manual workarounds to meet ACCESS requirements may succeed in the short term, but they will have to rebuild the same capabilities when they begin expanding their AI initiatives.

In other words, the organizations preparing for ACCESS are also preparing for enterprise AI. The question is whether they are building infrastructure that can support both, or solving today’s problem in a way that creates tomorrow’s technical debt.

The Hidden Cost of Minimum Compliance

This is where the compliance-versus-infrastructure divide becomes a financial argument rather than a philosophical one. CMS-0057-F, the interoperability and prior authorization final rule, already previewed this pattern for payers. Organizations that built genuine FHIR-based Provider Access and Prior Authorization APIs ahead of their 2027 deadlines are positioned to extend that same infrastructure into other CMS reporting obligations. Organizations that built the narrowest possible interpretation of the rule are now rebuilding for ACCESS, TEFCA connectivity, and whatever CMMI announces next, each time treating the work as a fresh compliance project instead of an extension of the last one.

An organization that builds only enough FHIR infrastructure to satisfy ACCESS reconciliation will face this same choice again the next time CMS launches a model with similar requirements, and there is no realistic scenario in which CMS launches fewer of them over the next decade. The cost of minimum compliance is not the integration work itself. It is paying for that integration work repeatedly, once per model, indefinitely, rather than once, well, with reuse built in.

Three Strategic Shifts ACCESS Demands

• From reporting to operations. Structured data exchange stops being an annual attestation and becomes a continuous, queryable capability other organizations depend on.
• From screening to resolution. Social-needs data has to close the loop, from a documented screening result to a tracked, resolved community referral, not stop at capture.
• From interoperability to automation. Moving data between systems is necessary but not sufficient. Value comes from the workflows that act on that data without waiting for a person to notice it.

Building for Compliance VS. Building for Scale

Don’t Build a Regulatory Band-Aid. Build an Automation Engine.

The ACCESS Model is about far more than meeting another CMS requirement. It signals a broader shift in healthcare, where success will increasingly depend on an organization’s ability to transform data into timely, measurable clinical action.

For years, healthcare has invested heavily in interoperability. ACCESS raises the bar by asking organizations to prove that interoperable data leads to better outcomes. That requires more than connected systems. It requires standardized data, automated workflows, and the ability to measure the impact of every intervention across the patient journey.

Organizations that approach ACCESS as a short-term compliance initiative may meet today’s reporting requirements, but they will likely repeat the same work as new value-based care models emerge. Those that use it to modernize their data and workflow architecture will create capabilities that extend well beyond ACCESS. The same infrastructure that supports continuous outcome measurement also enables AI-driven care coordination, predictive analytics, and intelligent clinical automation.

In many ways, ACCESS is a preview of where healthcare is heading. The organizations that invest in operational interoperability today will be better prepared for the next generation of value-based care and enterprise AI.

At Pegasus One, we help healthcare organizations build that foundation. From FHIR-native data platforms and interoperable integration layers to workflow automation and AI-ready architectures, we enable providers to turn fragmented healthcare data into coordinated, measurable action. The goal is not simply to succeed under ACCESS. It is to build an infrastructure that continues to create value as healthcare delivery, reimbursement, and AI continue to evolve.

Prepare for ACCESS, and for What Comes After It

The organizations that treat ACCESS as an infrastructure decision, not a reporting exercise, will be ready for the next wave of value-based care and enterprise AI. Pegasus One helps healthcare organizations assess their interoperability and workflow maturity, close the gaps that affect outcomes, and build a FHIR-native, AI-ready foundation that keeps creating value long after the first reporting cycle.

Talk to the Pegasus One team to understand what ACCESS will require of your data and workflows, and where the gaps are today. We help healthcare organizations build the FHIR-native, AI-ready foundation ACCESS rewards, so the work carries into the value-based care models that follow.