New White Paper Provides Recommendations for Improving Transparency in Coverage Data

Analysis finds ghost rates, missing utilization data, inconsistent bundle reporting, and file structure risk undermining federal price transparency goals

WASHINGTON, DC, UNITED STATES, February 20, 2026 /EINPresswire.com/ -- A new white paper released today by Simple Healthcare outlines how key implementation decisions in the federal government’s proposed Transparency in Coverage (TiC) updates will determine whether healthcare price transparency data becomes truly usable for employers, researchers, and policymakers.
The paper, Improving Transparency in Coverage Data: Reducing Ghost Rates, Adding Utilization, and Standardizing File Structure, evaluates four technical design areas that will shape the effectiveness of the proposed December 2025 rule updates: ghost rate filtering, utilization reporting, bundled payment disclosure, and machine-readable file architecture.

While the proposed rule correctly focuses on improving data usability and reducing file size, the analysis finds that high-level policy goals alone are not enough—implementation details will determine whether the data supports real-world decision-making.

Key recommendations from the paper include:

Ghost Rate Filtering
• Replace taxonomy-only filtering with a hybrid approach combining TIN-level claims evidence and specialty-connection backstops
• Specify a standard lookback window: 12 months of claims data ending six months before the quarterly file posting date
• Use a one-or-more threshold: any claim appearance in the lookback window triggers inclusion; avoid arbitrary minimum volume thresholds
• Require method transparency: payers should publish inclusion logic and data quality checks so analysts can understand and replicate filtering decisions

Utilization Reporting
• Use TIN/group claim counts as the primary utilization metric in the in-network rates file
• Report utilization at the network level, not the plan level, consistent with network-based reporting direction
• Standardize reporting bins as: 0, 10 or fewer, and 11+, with exact values reported above 10 (aligned with CMS cell size suppression policy)
• Adopt a utilization file with NPI-level binary flags indicating whether each provider performed each service, rather than NPI-level claim counts
• Specify role attribution: attribute utilization based on performing provider role, not billing or referring roles

Bundle Reporting
• Require explicit bundle/component semantics in machine-readable outputs
• Require passthrough indicators distinguishing included components from separately billed items, with typical passthrough prices
• Require bundle-component linkage fields connecting individual service lines to bundle totals
• Include average paid amounts for bundled episodes to provide context on typical total costs

Data Architecture
• Require relational rectangular machine-readable standards rather than JSON-only or flattened CSV publication
• Publish versioned schemas with stable field names and data types
• Consider alternative file formats such as Apache Parquet, which provide compression and faster query performance while maintaining relational structure
• Provide mapping guidance for converting between formats

“Taken together, these recommendations address the core technical barriers that currently limit real-world use of Transparency in Coverage data. Implementing them would significantly improve data accuracy, interpretability, and decision-making value for employers, researchers, and policymakers,” said David Muhlestein, CEO of Simple Healthcare and author of the paper.

Why This Matters
Price transparency rules are intended to support employer purchasing, policy analysis, and market competition. However, if technical design choices introduce systematic distortions or usability barriers, stakeholders may be unable to rely on the data for real-world decisions.
The paper emphasizes that transparency policy outcomes will be determined less by regulatory intent and more by the technical standards used to implement that intent.

About the Paper
The recommendations are based on empirical evaluation of current Transparency in Coverage data and claims-based utilization patterns. It focuses on practical, implementable approaches that balance regulatory feasibility with real-world analytic utility.

About Simple Healthcare
Simple Healthcare is a research-driven data company dedicated to making healthcare pricing clear, accurate, and decision-grade. We transform decision-making by turning complex transparency files into validated datasets—filtering out duplicates, ghost rates, and other noise while enriching with comprehensive provider data—and pairing them with intuitive analytics tools and APIs for fast benchmarking, contract analysis, and market monitoring. Led by experts in health economics, data engineering, and operations, we collaborate with payers, providers, employers, life sciences, and investors to advance the field through peer-reviewed publications, policy work, and practical guidance. Through our platform, data licensing, and publications, we accelerate the adoption of high-quality pricing insights at scale.

David Muhlestein
Simple Healthcare
+1 407-464-4444
email us here

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