Ensuring data accuracy poses a major hurdle for healthcare providers operating under value-based care models. In a recent discussion, Marlene McIntyre, assistant vice president of digital solutions at NCQA, outlined her organization’s initiatives aimed at assisting health systems in identifying key metrics and delivering data as close to the point of care as feasible.
McIntyre is set to appear on a panel at NCQA’s Health Innovation Summit in Atlanta, alongside executives from University of Massachusetts Memorial Health and Optum, to discuss building a scalable approach to quality initiatives that bridges claims, clinical, and payer data.
The presentation will explore how UMass combines Optum quality data with Epic clinical data and supplemental payer reports to create a more complete view of performance, validate results, and address common data gaps. In her role at NCQA, McIntyre leads digital products and initiatives focused on advancing trusted data, modernizing quality measurement, and accelerating the transition to digital quality.
McIntyre explained that clinicians working on quality initiatives often experience a lag time before claims data becomes available, resulting in reminders to close care gaps that have already been addressed. UMass and Optum are working to pull data together earlier in the process to ensure accuracy and provide meaningful insights.
Optum has built a platform to assess data quality and provide data to health systems in a way that demonstrates provider performance on specific measures. They are also using NCQA’s Quality Compass data from a prior year to show comparisons.
Building a Data Quality Framework
McIntyre noted that Optum is participating in an NCQA beta program building a data quality framework focused on establishing trust in data, particularly for HEDIS. The framework assesses data completeness, conformance, plausibility, and stability over time, as well as data integrity.
NCQA has developed metrics to help assess data quality more continuously and closer to the source, rather than relying on retrospective processes. McIntyre emphasized that data quality is a foundational cornerstone of good digital quality measurement, and the two work together to build a strong program.
McIntyre stressed that this is an evolutionary process for quality teams, starting with assessing current capabilities and finding the right partner organization to bring the right tools together to help solve data quality issues. NCQA’s data quality framework is designed to fit every payer type and portion of the ecosystem, providing a foundational element for digital quality measurement.
As the beta program progresses, NCQA will continue to refine its metrics and validation program, aiming to reduce the manual burden on payers, providers, and health systems related to primary source verification.
McIntyre previously worked at Optum and Datavant. Her experience has helped her understand the challenges of data quality in health systems.
Implementing the Data Quality Framework
Once the beta program goes live and earns trust, it is expected to reduce the mandatory requirement for primary source verification and empower providers to make better decisions with trusted data at their fingertips.
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