Utilization Pattern Analysis
Our analytics assess dominant utilization patterns and how they relate to clinical characteristics. The analytics flag unexpected cases for further investigation.
- Identification of dominant utilization groups through customized patient segmentation algorithm
- Construction of predictive models linking clinical characteristics to expected utilization
- Identification of unexpected cases via comparison between expected and actual utilization groups for each patient
- Provider: enable management by exception by allowing focused investigations into significant unexpected practice variations
- Payer: insight to help guide disease management program design and fraud detection