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NCQA Receives KLAS Points of Light Award for Demonstrating Feasibility of Bulk FHIR Exchange

NCQA Receives KLAS Points of Light Award for Demonstrating the Feasibility of Bulk FHIR Exchange

May 21, 2026NCQA

Summary

NCQA, with partners including eHealth Exchange, received the 2026 KLAS Points of Light Award. This initiative demonstrated that large-scale data exchange using Bulk FHIR is possible, improving upon traditional challenges such as fragmented data collection and manual processes.

Details

NCQA announced receiving a 2026 KLAS Points of Light Award for a Payer/Provider Initiative, in collaboration with partners like eHealth Exchange, Cambia Health Solutions, and MultiCare Health System. This award highlights the advancement of digital quality measurement through Bulk FHIR. Historically, quality measurement (such as HEDIS reporting) relied on manual chart reviews or point-to-point interfaces, leading to administrative burden and inconsistent data. Furthermore, while FHIR is the industry standard, EHR infrastructure often optimizes for single-patient retrieval, making scaling to thousands of members difficult. Many HEDIS vendors also do not accept native FHIR inputs. To address this, NCQA convened the Bulk FHIR Quality Coalition. They conducted real-world testing using a TEFCAβ„’-aligned network and a single connection model. eHealth Exchange served as the interoperability intermediary, eliminating the need for bespoke point-to-point integrations. MultiCare implemented a production-grade Bulk FHIR endpoint, while Cambria generated member rosters and built pipelines to ingest and validate data. The collaboration successfully exchanged HEDIS-relevant clinical data for over 5,000 attributed members, validating data completeness. Key results included reducing chart-chasing costs by approximately $50 per chart and accelerating bulk export timelines from days or weeks to minutes. This case validates that regulated APIs and shared FHIR profiles can operate consistently at scale when supported by governance and attribution standards.

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