Can help payer organizations identify hot-spot zip codes and high-risk members by layering in multiple internal (Cost & Utilization, Conditions, SDOH) and external indicators (census, AHRQ, CDC, RWJF etc.) on an interactive map. ​

Will provide a dedicated health equity section that will enable payers to understand unconscious bias in their decisions and look at membership, clinical, utilizations and socio-economic factors by race, ethnicity, language spoken, disability, geographic location (Rural/Urban) and more.​

Will be powered by a unified data product that will be created entirely on cloud and will provide multi-dimensional view of the member. Our solution will not only help address Population health issues but can help drive other business analytics and AI/ML use cases. ​

With right interventions, there is potential for savings of ~3-4% in total cost of care, lift in PCP visits and improved chronic care management in select population cohorts. ​