23 Jun Health IT Answers: Why Delaying dQM Readiness Could Cost More Than Preparing Top Takeaways

Top Takeaways

• The costs associated with fragmented data environments and manual reporting workflows are already affecting healthcare organizations today. 
• dQM readiness is not just about future compliance requirements. It is about improving operational efficiency, data quality, and decision making now.
• Investments in interoperability, data standardization, and reporting infrastructure can support multiple strategic initiatives beyond quality reporting.
• Delaying data modernization efforts may increase administrative burden and make future transitions more disruptive. 
• Organizations that strengthen their data foundations today will be better positioned for digital quality measurement, analytics, value-based care, and AI initiatives.

In his latest guest article for Health IT Answers, Mark Coetzer, VP of Business Development at IMAT Solutions, explores why healthcare organizations should look beyond the implementation costs of digital quality measures (dQMs) and consider the hidden costs of maintaining current reporting processes.

Read the full article here: Why Delaying dQM Readiness Could Cost More Than Preparing

As healthcare organizations prepare for HEDIS 2030 and the broader shift toward digital quality measurement, much of the industry conversation has focused on the investments required to support dQMs. However, as Mark explains, the status quo carries costs of its own.

Many healthcare organizations continue to rely on fragmented data environments, disconnected reporting processes, and manual workflows that require significant time and resources to maintain. While these processes may feel familiar, they often create administrative burdens, limit visibility into performance, and make it harder to generate value from healthcare data.

Why Data Readiness Is More Than a Future Requirement

One of the key themes in the article is that dQM readiness is not simply about preparing for future reporting requirements.

Many of the challenges organizations are trying to solve for tomorrow are already affecting them today. Incomplete clinical data, inconsistent documentation, disconnected systems, and limited interoperability can impact:

• Quality reporting performance
• Care coordination initiatives
• Provider engagement efforts
• Population health programs
• Value-based care strategies
• Healthcare analytics and reporting

 

As digital quality measurement continues to evolve, organizations are increasingly recognizing that stronger data foundations can deliver benefits long before future compliance deadlines arrive

The Opportunity Cost of Waiting

The article also highlights the opportunity cost associated with delaying data modernization efforts.

Every year organizations spend managing fragmented data environments and manual reporting processes is another year spent dealing with operational inefficiencies, reporting complexity, and administrative burden.

Investments that support dQM readiness often help organizations:

• Improve data quality and completeness.
• Strengthen interoperability.
• Reduce manual reporting efforts.
• Improve visibility into quality performance.
• Support more informed decision making.
• Generate greater value from healthcare data investments.

 

Rather than viewing dQM readiness solely as a compliance project, many healthcare leaders are beginning to see it as an opportunity to strengthen broader organizational capabilities.

How IMAT Supports dQM Readiness

At IMAT Solutions, we help healthcare organizations build the trusted data foundations required for digital quality measurement and long-term operational success.

With IMAT Intelligence, organizations can:

• Aggregate clinical and claims data from multiple sources.
• Normalize and validate data for reporting and analytics.
• Improve interoperability and data consistency.
• Reduce manual reporting and reconciliation efforts.
• Support HEDIS, dQMs, and future digital quality reporting requirements.
• Create a trusted data foundation for population health, value-based care, and AI initiatives.

 

Read the Full Article

The conversation around dQMs often focuses on implementation costs. In his latest Health IT Answers article, Mark explains why healthcare organizations should also consider the operational and strategic costs of waiting.

Read the full article here: Why Delaying dQM Readiness Could Cost More Than Preparing

Contact IMAT Solutions to learn how IMAT Intelligence can help your organization strengthen data readiness, support digital quality measurement, and maximize the value of healthcare data investments.

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About the Author
Mark Coetzer is VP of Business Development at IMAT Solutions, with more than 30 years of technology experience and a decade dedicated to healthcare. He brings deep expertise in clinical data integration, interoperability, and population health, and is passionate about helping organizations build trusted data foundations for better care and smarter outcomes.

Additional Insights from Mark Coetzer

• Why Health Plans Are Shifting Focus from Data Exchange to Data Intelligence
• Why AI Ready Data Drives Sustainable Quality Performance for Health Plans
• What Senior Quality Leaders Must Do Now to Prepare for Digital HEDIS
• Why Health Plan Data Infrastructure Is Becoming a Competitive Advantage