Transparency in Coverage Schema 2.0 Is Here: What Changed and What It Means in Practice
Last October, we outlined CMS’s planned updates to the Transparency in Coverage (TiC) schema and anticipated how a redesigned structure might improve the usability of commercial reimbursement data. Schema 2.0 has now officially rolled out, and payers have begun publishing files in the updated format.
With the latest files now deployed and enforcement policies in effect, the trend is clear: Transparency in Coverage data is becoming more standardized and reliable, but it also requires stronger data engineering capabilities to interpret accurately.
While the policy itself has not changed, the mechanics of working with TiC data have.
What’s different now
The updated schema delivers several practical improvements:
- Consolidation of redundant fields, reducing overall file size
- Clearer payer identifiers (business names + EINs)
- Standardized severity-related attributes
- Streamlined location structures
- Separation of payer and plan sponsor fields
- Shared provider references instead of repeated inline lists
The result is less duplication and greater consistency across files.
However, these efficiencies come with a tradeoff: rather than flat structures, Schema 2.0 relies more heavily on internal referencing and relational links. In other words, files are lighter but require more sophisticated mapping during ingestion.
What this means operationally
For teams analyzing TiC data, this change is less about policy and more about infrastructure.
Pipelines built around earlier formats often assume repeated inline provider groups and simpler joins. Under Schema 2.0, those assumptions no longer hold. Without updated ingestion logic, rates may be misattributed, incomplete, or difficult to reconcile across entities.
In short:
- Files are smaller
- Structure is cleaner
- Processing is more complex
The quality of downstream insights now depends even more on how well data are normalized and linked.
How Trek approaches it
At Trek, we’ve been preparing for Schema 2.0 since its announcement, updating ingestion workflows to handle shared provider lists, relational references, and evolving identifiers. Our focus remains the same: transforming raw TiC files into consistent, organization-level reimbursement intelligence that teams can actually use. Schema 2.0 is a step toward better standardization, but meaningful insights still depend on the infrastructure behind the scenes.

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Published on
February 2, 2026
Written by
Jordan Kassab
Last October, we outlined CMS’s planned updates to the Transparency in Coverage (TiC) schema and anticipated how a redesigned structure might improve the usability of commercial reimbursement data. Schema 2.0 has now officially rolled out, and payers have begun publishing files in the updated format.
With the latest files now deployed and enforcement policies in effect, the trend is clear: Transparency in Coverage data is becoming more standardized and reliable, but it also requires stronger data engineering capabilities to interpret accurately.
While the policy itself has not changed, the mechanics of working with TiC data have.
What’s different now
The updated schema delivers several practical improvements:
- Consolidation of redundant fields, reducing overall file size
- Clearer payer identifiers (business names + EINs)
- Standardized severity-related attributes
- Streamlined location structures
- Separation of payer and plan sponsor fields
- Shared provider references instead of repeated inline lists
The result is less duplication and greater consistency across files.
However, these efficiencies come with a tradeoff: rather than flat structures, Schema 2.0 relies more heavily on internal referencing and relational links. In other words, files are lighter but require more sophisticated mapping during ingestion.
What this means operationally
For teams analyzing TiC data, this change is less about policy and more about infrastructure.
Pipelines built around earlier formats often assume repeated inline provider groups and simpler joins. Under Schema 2.0, those assumptions no longer hold. Without updated ingestion logic, rates may be misattributed, incomplete, or difficult to reconcile across entities.
In short:
- Files are smaller
- Structure is cleaner
- Processing is more complex
The quality of downstream insights now depends even more on how well data are normalized and linked.
How Trek approaches it
At Trek, we’ve been preparing for Schema 2.0 since its announcement, updating ingestion workflows to handle shared provider lists, relational references, and evolving identifiers. Our focus remains the same: transforming raw TiC files into consistent, organization-level reimbursement intelligence that teams can actually use. Schema 2.0 is a step toward better standardization, but meaningful insights still depend on the infrastructure behind the scenes.