Risk Stratification Agent

The work it takes off your plate

Care management teams struggle to identify which patients will benefit most from intensive outreach when risk is assessed inconsistently across claims, EHR, and utilization silos. Manual stratification is slow, opaque, and often lags months behind real utilization spikes, so high-risk patients are missed while lower-risk members consume scarce care-manager capacity. The Risk Stratification Agent continuously scores populations using clinical, utilization, and social signals, segments members into actionable risk tiers, and routes prioritized worklists to care management so resources focus on the patients most likely to escalate.

How it works

The Risk Stratification Agent aggregates multi-source member data, applies configurable clinical and utilization models, and produces tiered risk cohorts with explainable drivers. It refreshes scores on a scheduled and event-driven cadence, aligns output to care-management program criteria, and pushes prioritized assignments into care management workflows with audit-ready rationale.

1. Step 1: Ingest Multi-Source Population Data

   • Pull claims, encounters, labs, medications, admissions, ED visits, and demographic attributes for the attributed population
   • Normalize identifiers, resolve member duplicates, and align episodes to a common attribution period
   • Flag incomplete records and quarantine members missing critical clinical or utilization fields for remediation

   Result: A clean, de-duplicated population dataset ready for risk scoring with data-quality flags attached.

2. Step 2: Score Clinical and Utilization Risk

   • Compute composite risk using chronic condition burden, polypharmacy, recent acute utilization, and rising-risk trajectory signals
   • Apply configurable weights for HCC-like clinical complexity, cost trends, and avoidable utilization patterns
   • Generate explainable risk drivers for each member (e.g., multiple ED visits, uncontrolled A1c, recent CHF admission)

   Result: Each member receives a transparent risk score and ranked driver list supporting clinical review.

3. Step 3: Segment Cohorts and Prioritize Outreach

   • Bucket members into high, rising, moderate, and low risk tiers using organization-defined thresholds
   • Map tiers to care management programs, panel capacity, and outreach SLAs
   • Produce prioritized worklists excluding recently engaged or hospice/palliative exclusions

   Result: Actionable cohort worklists sized to care management capacity with clear prioritization.

4. Step 4: Publish Scores and Continuous Feedback

   • Push risk tiers, drivers, and recommended programs into care management platforms and population dashboards
   • Track engagement outcomes and re-stratify after admissions, care plan changes, or new claims
   • Capture care manager feedback on false positives to refine model thresholds over time

   Result: Live risk intelligence continuously refined by outcomes and care team feedback.

Why use it

• Targeted Resource Allocation. Focus scarce care management capacity on the highest-yield patients.
• Explainable Scores. Risk drivers support clinical trust and audit readiness.
• Rising-Risk Detection. Surface patients before high-cost acute events.
• Operational Worklists. Direct integration into care management assignment queues.
• Continuous Refresh. Scores update with new utilization rather than annual lag.