Prospective HEDIS Analysis

Business Challenges

  • 20% of patient records lack essential information required for HEDIS measures.
  • Use of reactive approach as issues are generally tracked back after problem is surfaced.
  • Inconsistent data quality across multiple systems results in data discrepancies.

Solution Approach

  • Performed data quality analysis on data pertaining to 6 HEDIS measures, identified data gaps, enhanced data visibility & provided recommendations.
  • Incorporated shift left approach with early data quality checks and validations.
  • Created a funnel view to provide recommendations for analyzing the definition of each measure.
  • Analyzed data with advanced classification and time-series forecasting models.

Outcomes

  • Data quality dashboards
  • Defined 267 rules on 11 datasets
  • Created 23 data quality checks in SQL.
  • Actionable insights, ensuring high-quality data from source