The opt-out solution for payer-provider data exchange

Why the opt-out model is the key to scaling real-time payer-provider data exchange

For years, healthcare interoperability has been treated as a technical problem. Build the right APIs, adopt the right standards, and eventually the data will flow. But as anyone who has tried to onboard a health system one provider practice at a time knows, the technical challenge is only half the battle. The harder problem is scale.

That was the insight at the center of a conversation at HIMSS26 between Greg LeGrow, Executive Director, Payer Marketing Strategy at athenahealth, and two leaders from Aetna: Sonal Jain, Executive Director of Software Engineering, and Kristen Monk, Senior Manager of Program Management. Together, they made the case that real-time, standards-based data exchange between payers and providers isn't a future state — it's happening now, and one design decision is making it possible faster than many expected: the opt-out model.

The problem with practice-by-practice onboarding

Anyone who has built payer-provider integrations at scale has lived through the same painful cycle. You identify a health system, negotiate access, complete implementation, train staff, and move on to the next practice — only to repeat the process hundreds of times over. The result is slow value realization, high implementation costs, and change management challenges that erode adoption before the integration even goes live.

Sonal Jain described the problem directly:

When you onboard health systems one provider at a time, it's inefficient, slow, and complex. Change management is harder, and it's costly because implementation windows are so long.

— Sonal Jain, Executive Director, Software Engineering, Aetna

The athenahealth opt-out model inverts this dynamic. Rather than requiring each provider to actively enroll, connected systems within the athenahealth network are included by default. This “opt-out” approach refers to provider participation in the athenahealth network, as governed by athenahealth participation terms, and does not alter patient rights under applicable privacy laws. For Aetna, this meant reaching a broad portion of athenahealth’s connected network in a single integration effort — compressing what might have taken years into a fraction of the time.*

Opt-out isn't just efficient. It's strategic.

The implications of the opt-out approach extend well beyond implementation speed. For Kristen Monk and the Aetna team, it fundamentally changes what's possible from a population health standpoint.

The opt-out model makes it a lot easier for us to expand to the full population. I'm super excited and very eager to start working on additional features because of that strategy.

— Kristen Monk, Senior Manager, Program Management, Aetna

When you can achieve network-level participation at scale rather than a patchwork of opted-in practices, the economics of interoperability change. Care gap notifications, diagnosis gap alerts, and clinical data exchange stop being targeted interventions for a subset of patients and start being foundational infrastructure for members across athenahealth’s participating providers.

That shift — from selective to systemic — is what makes the opt-out model so consequential for payers thinking about value-based care performance, accurate and compliant risk adjustment, and administrative efficiency at scale.

Workflow is where adoption lives or dies

Technology that lives outside the clinical workflow doesn't get used. It's a truth that has derailed more healthcare IT initiatives than almost any other factor. The HIMSS26 conversation made clear that Aetna has internalized this lesson deeply. 

If we can get the right data to the right place in front of our end users when they need it — sometimes even before they know they need it — that's what creates the efficiencies that drive adoption.

 — Kristen Monk, Senior Manager, Program Management, Aetna

For athenahealth, this means building payer data natively into the EHR rather than layering it on top. Diagnosis gaps, care gaps, and clinical summaries surface inside the provider's existing workflow — no new training, no new login, no new tab, while maintaining appropriate access controls, auditability, and use limitations. The result is that providers interact with payer data the same way they interact with any other clinical information: as a natural part of the encounter.

The downstream effect on administrative burden is measurable. Aetna reported a meaningful reduction in manual medical record requests — a historically expensive and time-consuming process — as electronic clinical data began flowing in near real time through the integrated connection. Providers that once dedicated staff hours to fax management and record scanning are recapturing that time without diminishing privacy or security safeguards.

Early results are validating the model

The proof, of course, is in the outcomes. And the early indicators from the Aetna-athenahealth exchange are encouraging. The partnership has facilitated the exchange of millions of clinical documents and hundreds of thousands of diagnosis gap notifications.*

Jain framed the significance of real-time data availability in terms that will resonate with any payer leader thinking about care management:

"When we have clinical data in real time, it's sitting and waiting before a process even needs to kick off within a care event. We already have the data. We ingest it once and can use it many times — it's there before the event even happens."

 — Sonal Jain, Executive Director, Software Engineering, Aetna

This isn't just an efficiency story. It's a care quality story. Proactive, pre-event data availability means care managers, utilization reviewers, and clinical programs can operate from a complete picture rather than chasing records after the fact.

The takeaway for payer leaders

The conversation at HIMSS26 offers a clear message for payers evaluating their interoperability investments: the technical infrastructure for real-time payer-provider data exchange is mature through private, standards-based interoperability frameworks. FHIR standards are proven. EHR-native integrations are deployable. The remaining question is whether you're choosing partners and architectures that can scale while aligning with regulatory, contractual, and governance requirements.

The opt-out model is one of the clearest examples of a design decision that looks simple on the surface but has profound implications for how quickly a payer can move from pilot to population-scale exchange. For Aetna, it was a differentiator that compressed implementation timelines, expanded population reach, and created a foundation for expanding to new use cases — prior authorization, utilization management, and beyond.*

Healthcare interoperability has been a promise for a long time. The organizations doing the work to make it real aren't waiting for the industry to catch up. They're building the infrastructure now — and the opt-out model is one reason they're winning.