Data Quality That Happens Before It Matters Most

Clinical data powers quality measurement, analytics, interoperability and care improvement, but data quality issues are often discovered too late to easily correct.

NCQA Data Quality Solutions provide a shared, standards-based framework for evaluating clinical data quality earlier in the data lifecycle, helping organizations build confidence in the data they use for quality measurement.

Built on nationally recognized standards, these solutions enable automated, upstream data quality checks that reduce manual effort, preserve trusted rigor and support scalable digital measurement across interoperable data ecosystems.

THE CHALLENGE

Six Ways Data Quality Fails Healthcare Organizations

When data quality is inconsistent, undefined or has issues discovered too late, the result is rework, operational burden and reduced confidence in reporting and analytics.

  • 1. No Shared Definition of Quality

    Without a common standard, organizations define "good data" differently, creating inconsistency and rework.

  • 2. Problems Surface Too Late

    Data issues are often discovered during reporting or audit, when remediation is most costly and disruptive.

  • 3. No Continuous Monitoring

    Data quality isn't monitored throughout the workflow, allowing issues to grow over time.

  • 4. Manual, Inefficient Processes Don't Scale

    Manual reviews and custom checks create burden and struggle to keep pace with growing data volumes.

  • 5. Limited Trust in Data

    Uncertainty about data quality undermines confidence in reporting, analytics and decisions.

  • 6. Acting on False Signals

    Poor data quality can lead teams to focus on the wrong gaps, priorities and opportunities.

The cost isn't just technical. It's clinical, operational and financial.

THE SOLUTION

Standards‑Based Confidence for Digital Quality Measurement

NCQA Data Quality Solutions help organizations move from reactive data quality processes to proactive data quality management. By establishing a shared framework for evaluating clinical data quality and supporting automated, upstream assessment, organizations can identify issues earlier, reduce manual effort and build confidence in the data used for quality measurement.

With NCQA Data Quality Solutions, you can:

  • Move data confidence upstream with standardized, automated checks.
  • Preserve the rigor and trust built on decades of HEDIS® quality measurement.
  • Support digital quality measurement across modern, interoperable data pipelines.

NCQA Data Quality Solutions help establish confidence in clinical data earlier in the lifecycle, supporting more automated, scalable validation while preserving the rigor of Primary Source Verification (PSV).

Three Components of NCQA Data Quality Solutions

NCQA Data Quality Solutions are designed as a modular, forward looking framework that strengthens data confidence across the ecosystem.

  • HEDIS Data Quality Specifications

    Delivers standardized rules and standards that define whether data is fit for quality use, enabling organizations to embed them directly into technology solutions or use as a reference framework.

  • Prevalidation for HEDIS Data Quality Specifications

    A validation program that assesses that the data quality rules embedded in technology solutions are implemented correctly, giving organizations confidence that automated data quality checks are functioning as intended.

  • Validation for Data Streams (Coming in 2027)

    A validation program that evaluates aggregated clinical data streams so organizations can assess their level of data quality and know it is fit for use in HEDIS reporting.

Why Organizations Use NCQA Data Quality Solutions

  • Improve Data Integrity Upstream

    Catch errors before they reach reporting or analytic systems.

  • Reduce Manual Effort

    Standardized rules help automate QA processes and decrease time‑consuming rework.

  • Accelerate Digital Transformation

    Support FHIR®, digital measures and interoperability initiatives with authoritative guidance.

  • Build Trust & Readiness

    Strengthen confidence across partners and stakeholders with a transparent, repeatable approach to data validation.

HOW IT WORKS

Evaluate Data Quality Across Multiple Dimensions

The HEDIS Data Quality Specifications are the foundation of the Data Quality Solutions portfolio. Organizations use these specifications to assess clinical data quality within and across data sources, identify issues that need attention and monitor ongoing data exchange.

  • Usability

    Evaluates whether data is complete, conformant, accurate and timely, helping organizations determine whether data is properly structured and suitable for quality measurement.

  • Plausibility New for October 2026

    Evaluates whether data reflects expected clinical patterns through metrics such as prevalence rates, prevalence distributions and contextual measures.

  • Stability New for October 2026

    Evaluates the degree of variation across repeated assessments of the same data source to help organizations understand consistency over time.

Together, these dimensions help organizations assess clinical data quality across sources and better understand whether data is fit for quality measurement.

Built with Industry Feedback

Developed and refined with input from health plans, HIEs, data aggregators and technology organizations, the HEDIS Data Quality Specifications reflect real-world implementation experience and evolving industry needs.

What's Included

  • More than 100 standardized data quality checks spanning usability, plausibility, and stability dimensions.
  • Alignment with HEDIS Volume 2 value sets for consistency across clinical concepts.
  • Patient-level test data and a scoring key to support implementation, validation and real-world scenario testing.
  • Support for both in-flight and at-rest data, enabling use across pipelines and at scale.
  • FHIR®-based implementation guidance.
  • Annual updates to maintain consistency with HEDIS and digital quality standards.

GET STARTED

  • See the Specifications in Action

    Schedule a demo and discuss your organization's data quality challenges.

    Speak with an Expert

  • Get Started with the Specifications

    Purchase the HEDIS Data Quality Specifications and begin implementing standardized data quality checks.

    Visit NCQA Store

Part of a Trusted Data Quality Ecosystem

NCQA Data Quality Solutions are designed to complement—not replace—the HEDIS Compliance Audit and Data Aggregator Validation program. The audit remains a critical safeguard to ensure HEDIS results are reliable, comparable and suitable for benchmarking across organizations.

As standardized FHIR® data and digital quality measurement continue to mature, NCQA will incorporate more automation into audit processes over time, helping reduce manual burden while preserving the rigor and consistency the industry depends on.

HEDIS® is a registered trademark of the National Committee for Quality Assurance (NCQA).

NCQA HEDIS Compliance Audit™ is a trademark of the National Committee for Quality Assurance (NCQA).

FHIR® is a registered trademark of Health Level Seven International; use does not constitute endorsement by HL7.