Onyx Blog
From Interoperability to Intelligence: A Conversation with NCQA and Payer Leaders on Clinical Data, Quality, and Payer Performance
Onyx recently convened leaders from across Blue plans, commercial plans, DSNP organizations, and state Medicaid agencies for our inaugural Customer Advisory Forum focused on a question that is becoming more urgent across the payer market: now that more clinical data is finally accessible, what will separate organizations that simply have data from those that turn it into performance?
For years, the industry conversation has centered on interoperability, regulatory readiness, and the mechanics of data exchange. Those still matter. But for payer leaders, the more pressing question is now operational. The challenge is no longer just whether data can be exchanged. It is whether that data can be trusted, governed, and used well enough to improve quality, reduce friction, manage cost, and support stronger performance across the business.
Before the discussion, we asked participants which industry trends were likely to have the biggest impact on their organizations over the next 12 to 24 months. Two rose clearly to the top: AI and automation across the payer industry, and rising medical and administrative costs.
That response is telling. It reflects an environment in which payer organizations are trying to improve efficiency and decision-making at the same time that financial pressure is intensifying. It also suggests that plans increasingly view AI not as an isolated innovation topic, but as something that must be applied against real operational challenges — from workflow burden to data quality to prioritization.
Participants also rated themselves as relatively more advanced in prior authorization and risk adjustment, and earlier in their journey on digital quality measurement. The signal there is important: for many plans, the next maturity step is not simply more automation. It is building the clinical-data foundation and operational discipline needed to make digital quality real.
That is what made Digital HEDIS such an important focal point for the discussion.
NCQA Chief Technology Officer Ed Yurcisin framed NCQA’s role as helping push standardized data into the market through quality measurement. His formulation was especially useful:
“If your data is good enough for HEDIS, it’ll be good enough for prior auth. It’ll be good enough for public health.”
That is what makes Digital HEDIS bigger than a quality initiative. It is becoming one of the clearest early tests of whether clinical data is truly ready to support broader payer operations.
Ed shared that NCQA has now digitized 83 HEDIS measures using USCDI and CARIN Blue Button, expressed in Clinical Quality Language (CQL). HEDIS vendors can still certify today using either flat files or FHIR, but by 2030, FHIR ingestion will be required and paper specifications are being phased out in favor of digital delivery.
The direction is clear. The harder question is whether the data beneath it is ready.
The most important insight from Ed’s discussion was also the most practical: the limiting factor in digital quality measurement is increasingly data quality, not measure logic.
His comment that many EHRs still produce “FHIR data written in Klingon” captured the problem well. In the real world, technically compliant data is not always operationally usable. Proprietary value sets, inconsistent mappings, and basic disagreement over where common clinical events should live within FHIR resources all create friction downstream.
To address that, NCQA is building a data quality framework organized in three layers:
NCQA’s data quality framework is being operationalized through specifications that organizations can incorporate directly into their own validation and monitoring workflows.
That framework matters far beyond HEDIS. It points to a broader truth: the next phase of payer performance depends not just on acquiring more data, but on ensuring that the data is reliable enough to support confidence, automation, and action.
Two implications from Ed’s remarks stand out.
First, NCQA’s goal is to eliminate Primary Source Verification as a universal requirement for HEDIS health plan reporting, replacing it with continuous data quality rules and ongoing monitoring. More than 100 rules are already implemented. The move signals a larger shift from annual confidence checks to continuous confidence in the data itself. NCQA is already engaging health plans and software vendors through beta workstreams focused on Data Quality Specifications, software prevalidation, and roadmap development to help refine scalable validation approaches and inform the path to reducing PSV.
Second, bulk FHIR is coming for quality measurement. Ed pointed to emerging real-world examples showing that bulk FHIR extraction can reduce data acquisition cost and improve timeliness. In his view, the industry is moving steadily toward a world in which clinical data becomes more accessible, more current, and more useful for quality and adjacent workflows.
Together, those changes reinforce the same point: the organizations that invest in usable, trustworthy data now will be better positioned as the market evolves.
That broader transition was also reflected in the discussion with payer leaders.
When members were polled on where Onyx should focus product investment, data platform engineering and CDR/IDR capabilities ranked highest, with EHR completeness, risk adjustment, and intelligent prior authorization drawing additional support. The signal was clear: the market still sees the foundation as the most important work, because everything above it depends on it.
A related question on the biggest challenge that better data could solve surfaced governance and audit readiness as the leading concern. That is an important observation. It suggests that payer leaders are thinking beyond access and even beyond analytics. They are focused on whether they can trace data back to source, trust it in operational settings, and defend it when scrutiny increases.
That also explains the paradox many plans now face around AI. There is strong interest in deploying AI more aggressively, but there is also recognition that automation is only as strong as the data beneath it. Incomplete, delayed, or systematically miscoded data does not become more useful just because an AI layer is applied to it.
The thread running across the discussion was straightforward: the next phase of payer competitiveness will not be defined by access to data alone. It will be defined by the discipline organizations bring to making that data usable, governable, and operationally relevant.
Digital HEDIS is one proving ground for that shift. Bulk FHIR acquisition, longitudinal record building, and AI-assisted workflows are others. The common thread is the same — helping payer organizations move from connectivity to usability, and from interoperability to intelligence.
That is where the market is now headed. And for payer leaders, the organizations that make that transition best will be the ones most prepared to improve quality, reduce friction, and drive stronger performance across the business.
If these themes resonate with your organization, we’d welcome the opportunity to continue the conversation about how health plans are approaching clinical data, digital quality, and payer performance. Contact Us
