Our clients effectively prioritize their populations and get the highest return on investment and engagement because we go beyond risk analysis and risk score development.
We layer multiple risk scoring approaches with deep-learning algorithms, demographic factors, hundreds of clinical markers and custom data enrichments -- such as social determinants (SDoH) or calculated gaps in care -- to accurately classify everyone into one of four key risk groups:
- Rising risk
- Chronically unhealthy
- Catastrophically unhealthy
Within each risk group, we identify focus areas through enhanced and predictive data analytics. These include risk scores for poor COVID-19 outcomes, chronic disease complications, service utilization, and healthcare costs. Some of these models incorporate SDoH features as input variables.
By combining these layered approaches, we identify people and groups of people with disproportionately high costs and poor outcomes. We help our clients find and engage those most in need, those about to become most in need, and those for whom interventions drive the greatest impact.
Our data science models help healthcare organizations intervene earlier with patients whose risk is expected to rise and/or who are at risk for major, expensive conditions, enabling clients to improve patient health while mitigating future costs.