Ensuring 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 mathematicians, statisticians and clinical experts have applied extensive healthcare systems and claims experience to develop and implement statistical quality review and analytic processes 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 verification of the following elements and criteria:

  • 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;
  • Identification of duplicate or conflicting records; 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.

Extensive validation and quality assurance tests are conducted at each stage of the data management.