Secure, Accurate Medicare Data Starts with Governance

Think of your organization’s data like your neighborhood library. If no one maintained the shelves, the books would become disorganized, outdated, or go missing.

Now imagine the stakes are much higher. In the world of Medicare provider data, even a single inaccurate or misplaced record can trigger inefficiencies and regulatory non-compliance or open the door to fraud. Without a clear system for managing data, organizations face serious risks—from compromised data quality to a loss of trust and accountability.

That’s where data governance comes in.

Data governance is the framework of rules, roles, and processes that foster robust data management, ensuring that data is reliable, secure, and used properly. 

Returning to the library analogy, where books represent data, effective data governance makes certain that: 

• The right people can access the books when they need to. 

• The books are in good condition, and the information inside is accurate and up to date. 

• Everyone follows the same rules for organizing, storing, and handling the books—so nothing gets lost, misfiled, or overlooked. 

This is why implementing data governance for the Centers for Medicare & Medicaid Services (CMS) provider enrollment—delivered through Tria Federal’s key data asset, the provider vetting API—was so crucial.  

The API enables real-time Medicare provider and supplier enrollment checks against the Provider Enrollment, Chain, and Ownership System (PECOS), delivering the highest level of compliance with CMS provider enrollment policies. The API also helps to maintain program integrity, reduce provider burden and improve operational efficiency across Medicare programs and models.  

So how can an organization build strong data governance? Here are some best practices, based on Tria’s experience successfully applying policies, processes, and technology to manage CMS provider data with integrity and compliance.

Our Data Governance Framework

Policies: Defining the “What” and “Why” 

Access Control: Tria established policies around access controls for different teams (e.g. Data Ops, Prod Ops and Dev Ops) to ensure only authorized users handle sensitive data. 

Provider Enrollment Compliance: We enforced provider credential validation during the initial provider onboarding and periodic revalidation, in alignment with CMS policies. 

Provider Data Integrity: We implemented policies around maintaining data integrity, including regular audits to verify provider credentials and status. 

Data Stewardship and Accountability: We designated data stewards who are responsible for data accuracy, completeness, and security throughout its lifecycle. 

Processes: Turning Policy into Action

Provider Enrollment Lifecycle Management: Tria defined end-to-end processes for provider applications, revalidations, updates, and terminations, including: 

• Initial credentialing and verification of provider identity and qualifications 

• Ongoing monitoring for changes in licensure, sanctions, and exclusions 

• Scheduled CMS-compliant revalidation 

Data Quality Assurance: We implemented workflows to: 

• Clean outdated or duplicate records 

• Cross-reference data with external sources (e.g., PECOS and the National Plan & Provider Enumeration System) 

• Conduct regular audits to avoid enrolling ineligible or sanctioned providers 

Exception Handling and Remediation: We created structured processes for addressing data discrepancies (e.g., incomplete applications, credential mismatches) with built-in escalation paths.  

Change Management and Version Control: We managed data updates (e.g., address updates, National Provider Identifier (NPI) changes) with full version control and history tracking.  

Technology: Scaling with Automation and Transparency 

Data Quality and Validation: We used tools built with Python, JSON and SQL to automate data profiling, cleansing, and validation tasks.  

Metadata Management and Data Lineage: We designed custom solutions to track provider metadata about each provider, including enrollment status, NPI, specialty, licensing status, and credentialing history, making provider data traceable and transparent. 

Looking Ahead: Governance for AI at Tria Federal

At Tria, vigorous governance of our provider vetting API ensures secure, compliant, and efficient provider data management.  

As we expand into AI-driven solutions, we are applying the same governance principle to future AI products. We are committed to pursuing:  

• Ethical AI design 

• Transparency in algorithms and outcomes 

• Accountability in decision-making 

• Compliance with evolving healthcare regulations 

Through strong AI governance, we aim to build AI systems that are not only innovative and intelligent—but also secure, fair, and impactful for the federal government.  

To learn more about how Tria Federal can help your agency manage your data and AI products, contact us today. 

Nikita Patel is a Senior Data Quality Analyst with over a decade of experience in public and private healthcare sectors. Patel is a Certified Data Management Professional (CDMP) and Certified in Allscripts Sunrise Clinical Manager (SCM) – Enterprise EMR. An earlier version of this article was published by Softrams, a Tria Federal Company.