Assuring the Integrity of the Data We Receive

Maintaining the highest data quality standards is integral to FAIR Health’s leadership in promoting healthcare cost transparency. Our healthcare data analysts, statisticians and clinical experts have applied extensive healthcare systems and claims experience to develop and implement healthcare data analytic processes and statistical quality review that assess the validity and integrity of the data.

FAIR Health performs rigorous validation processes and quality assurance tests at each stage of our data management process to support claims data collection, validation, mapping and aggregation. Claims data are subjected to intense scrutiny, including the standardization of data from multiple sources; identification of erroneous data elements; comparison to past contributions, contributions from other payors and industry norms; and detection of duplication and claim versioning.

Data Validation Process

Our data validation process includes tactical, methodological and business-based verification of the following:

• Data element formats and lengths;
• Population of required data elements;
• Location and procedure code validation;
• Data element values compared to expected values or thresholds;
• File content and volume, including analysis of utilization and field value frequency and comparison to contributor history;
• Utilization and cost comparisons against actuarial expectations and industry standards;
• Assessment of reverse and reprocessing within the submission compared to other submissions;
• Uniqueness of key fields;
• Distributions of key healthcare fields to prior submissions as well as to submissions provided in the same month/season in a prior year; and
• Remediation of identified issues in future data submissions in consultation with contributors.

FAIR Health staff experts work with contributors to understand their data so we can map the data to our data warehouse and facilitate the contribution process.