02 Jul Healthcare Has Achieved Interoperability. Now Comes the Hard Part: Data Standardization
Top Takeaways
• Healthcare interoperability has reached an important milestone, but exchanging data is only the first step toward improving care and operational performance.
• TEFCA and the CMS Health Tech Ecosystem are accelerating secure health information exchange across the industry.
• Health plans are moving from experimentation to operationalization as AI becomes embedded into workflows such as risk adjustment, claims, and utilization management.
• The next challenge is ensuring exchanged data is standardized, trusted, and ready to support quality reporting, analytics, and clinical decision making.
• Data standardization will play a critical role in the success of HEDIS 2030, digital quality measures (dQMs), AI, value-based care, and population health.
• Healthcare organizations that invest in trusted data foundations today will be better positioned to maximize the value of interoperability tomorrow.
By Mark Coetzer, VP of Business Development at IMAT Solutions
For years, healthcare’s biggest interoperability challenge was moving data between organizations. Today, that challenge is rapidly changing.
Federal initiatives such as TEFCA and the CMS Health Tech Ecosystem are making it easier than ever for healthcare organizations to securely exchange clinical information. More than 500 million records have already been exchanged through TEFCA, while hundreds of healthcare organizations have committed to advancing interoperability through the CMS Health Tech Ecosystem.
That represents tremendous progress, but it also raises a different question.
Now that healthcare data can move more freely, how do organizations ensure that the information arriving on the other end is complete, accurate, consistent, and ready to support better decisions?
The conversation is beginning to shift from interoperability to data standardization.
Healthcare has spent years building the infrastructure to exchange information. The next phase of digital transformation will focus on making that information usable.
Interoperability Has Reached an Important Milestone
The alignment between TEFCA and the CMS Health Tech Ecosystem represents one of the most significant interoperability advances the industry has seen in years.
Together, these initiatives are helping healthcare organizations improve data exchange while supporting broader goals around patient access, care coordination, electronic prior authorization, and healthcare innovation.
Rather than competing approaches, they complement one another. TEFCA provides the governance framework needed to enable secure nationwide exchange, while the CMS Health Tech Ecosystem encourages faster innovation through voluntary collaboration among providers, payers, technology vendors, and health information networks.
Healthcare organizations finally have the infrastructure to move healthcare data at scale.
The next challenge is making sure that data can actually be used.
Exchanging Data Doesn’t Guarantee Trusted Data
Interoperability allows healthcare organizations to share information. However, It does not automatically ensure that information is standardized.
Healthcare data continues to be generated across multiple EHRs, claims systems, laboratories, pharmacies, imaging platforms, and countless clinical workflows. Differences in documentation practices, coding, terminology, and data formats often create inconsistencies that persist long after information has been exchanged.
Organizations frequently encounter:
- Duplicate patient records
- Incomplete clinical documentation
- Inconsistent coding
- Missing data elements
- Varying data formats
- Disconnected clinical and claims information
As more organizations begin exchanging larger volumes of healthcare data through TEFCA and other interoperability initiatives, these inconsistencies become even more visible. Healthcare is discovering that exchanging fragmented data simply creates fragmented interoperability.
The true value of interoperability depends on the quality of the data being exchanged.
Why Data Standardization Matters More Than Ever
The importance of standardized data extends far beyond interoperability itself. Healthcare organizations are increasingly relying on trusted data to support quality reporting, value-based care, analytics, care management, AI, and operational decision making.
These initiatives all depend on data that is complete, accurate, normalized, and trusted.
If healthcare leaders cannot rely on the information flowing through their systems, they cannot confidently measure quality, identify care gaps, evaluate performance, or automate workflows.
This is why data standardization is becoming one of healthcare’s most important strategic priorities.
The conversation is no longer simply about moving healthcare data, but it is about creating healthcare data that organizations can confidently use.
HEDIS 2030 Raises the Stakes
The growing emphasis on standardized data comes at an important time. As healthcare moves toward digital quality measurement, organizations will increasingly rely on electronic clinical data rather than manual chart abstraction to measure quality performance.
That transition makes trusted data more important than ever. Digital quality measures depend on standardized clinical information that can be consistently extracted, validated, and reported across organizations.
Healthcare organizations that continue to rely on fragmented data environments and manual reporting workflows may find it increasingly difficult to keep pace as reporting requirements evolve.
This is one reason IMAT has consistently emphasized that HEDIS 2030 is not simply a future milestone. It is a data readiness challenge that organizations should be addressing today.
Our recent resources explore this transition in greater detail, including:
- Meeting the HEDIS 2030 Moment: Why Data Readiness Can No Longer Wait
- HEDIS 2030 Is a Countdown, and Data Quality Will Decide Who Is Ready
- Why HEDIS 2030 Is a Now Problem for Payers
- Why Delaying dQM Readiness Could Cost More Than Preparing
Together, these industry changes reinforce a common message: trusted data is becoming the foundation for modern healthcare performance.
Standardized Data Creates Enterprise Value
The benefits of data standardization extend well beyond compliance. Organizations with stronger data foundations are better positioned to:
- Improve digital quality measurement
- Strengthen population health initiatives
- Support value-based care programs
- Enhance care management
- Streamline prior authorization workflows
- Improve healthcare analytics
- Reduce administrative burden
- Support responsible AI adoption
- Improve operational decision making
These initiatives may appear unrelated, but they all rely on the same underlying capability.
Trusted, standardized healthcare data. Healthcare organizations that establish this foundation once can leverage it across multiple strategic priorities instead of solving the same data challenges repeatedly within individual programs.
How IMAT Intelligence Helps Organizations Move Beyond Interoperability
As interoperability continues to mature, healthcare organizations need more than the ability to exchange information. They need the ability to transform exchanged data into trusted intelligence.
IMAT Intelligence helps healthcare organizations aggregate, normalize, validate, and operationalize clinical and claims data across the enterprise, creating a standardized data foundation that supports today’s reporting requirements while preparing organizations for tomorrow’s digital healthcare ecosystem.
By transforming fragmented healthcare data into trusted, actionable intelligence, IMAT Intelligence helps organizations:
- Improve data quality and consistency
- Support HEDIS 2030 and digital quality measures
- Strengthen interoperability initiatives
- Reduce manual reporting and reconciliation
- Improve population health and care management
- Enable more effective analytics
- Support responsible AI initiatives
- Generate greater value from healthcare data investments
Interoperability creates access to data, and IMAT Intelligence helps organizations create confidence in that data.
Looking Ahead
Healthcare has made enormous progress in interoperability. The industry now has the infrastructure to move healthcare data farther and faster than ever before.
The next challenge is ensuring that data is trusted. Organizations that invest in data standardization today will be better positioned to improve quality reporting, strengthen interoperability, support AI, reduce administrative burden, and deliver better patient outcomes tomorrow. Healthcare has achieved interoperability, and now comes the hard part.
Contact IMAT Solutions to learn how IMAT Intelligence can help you move from data exchange to data impact.
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 Delaying dQM Readiness Could Cost More Than Preparing
• Why AI Ready Data Drives Sustainable Quality Performance for Health Plans
• Interoperability in 2026: Progress, Gaps, and What It Means for Closing Care Gaps
• Why Health Plan Data Infrastructure Is Becoming a Competitive Advantage
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