04 Mar Health IT Answers: Why Data Quality Will Decide Who Is Ready for HEDIS 2030

In a recent Health IT Answers guest article, Mark Coetzer, VP of Business Development at IMAT Solutions, explains why data quality is becoming the deciding factor in HEDIS 2030 readiness. As hybrid chart review is phased out and digital reporting becomes mandatory, health plans must strengthen data completeness, normalization, interoperability, and audit defensibility to protect performance outcomes and regulatory compliance.

For decades, HEDIS has anchored health plan quality measurement. What is now changing is how it will be reported and audited. As such, NCQA has proposed a full transition to digital HEDIS by Measurement Year 2030, eliminating hybrid chart review and replacing it with standards based digital reporting built on interoperable clinical data.

Plans will be required to demonstrate readiness through parallel reporting, and audits will shift from reviewing chart abstraction workflows to examining data pipelines, normalization rules, and traceability.

In his recent Health IT Answers guest article, HEDIS 2030 Is a Countdown and Data Quality Will Decide Who Is Ready, Mark explains why this shift fundamentally changes the nature of performance risk. In a fully digital environment, what exists in the data is what gets measured.

Missing data cannot be manually reconciled, inconsistencies cannot be smoothed over late in the cycle, and audit scrutiny moves upstream into the data lifecycle itself. As a result, data quality becomes the determining factor in digital HEDIS readiness.

Why Digital HEDIS Changes the Standard
For years, hybrid reporting gave quality teams flexibility, and documentation gaps could be addressed through manual chart abstraction. In addition, inconsistencies could be reconciled late in the reporting cycle.

When reporting is driven entirely by structured clinical data and automated logic, what exists in the dataset is what gets measured. Missing data remains missing. Inconsistent mappings affect results. Delayed feeds impact performance visibility. Digital systems apply logic consistently and precisely, which means the underlying data must meet that same standard.

As Mark writes in the article, data quality is no longer a secondary issue and that it directly affects reporting accuracy, audit defensibility, and performance outcomes.

Why Preparation Cannot Wait
The article also emphasizes that readiness cannot be achieved in a single measurement year. Digital reporting requires sustained testing, validation, and operational experience. As such, payers must understand how their clinical and claims data align, how normalization rules are applied, and where gaps may exist before hybrid options are retired. Waiting increases pressure. It reduces time for correction. It compresses remediation into a smaller window with higher stakes. Quality leaders who begin evaluating their data foundations now will be positioned to move confidently into a fully digital reporting environment.

Questions Every Health Plan Should Be Asking
Mark encourages health plans to assess their readiness by asking practical questions:

• Can clinical data be ingested electronically across providers and systems at scale?
• Is the data complete, normalized, and current enough to support digital measures?
• Do clinical and claims datasets align consistently?
• Can results be traced clearly during audit review?
• Is the data infrastructure built for ongoing digital measurement, not just annual submission?

Answering these questions today helps avoid uncertainty tomorrow. For quality leaders, analytics teams, and payer executives navigating the shift to digital measurement, this guest article provides practical guidance on where to focus now.

Contact IMAT Solutions today to learn how IMAT Intelligence and the Health Data Quality Assessment can help you prepare for HEDIS 2030 with confidence.