Patient Cohort Analytics

Sector

Engagement Type

Longitudinal patient cohort modeling

Scope

Diabetes, hypertension & cardiovascular comorbidity care

Geography

U.S.

Project overview

Patient Cohort Analytics Longitudinal Outcomes Monitoring for Chronic Care

Challenges

  • Patient risk stratification was based on visit-level data rather than population trend insights.

  • No unified view existed across labs, vitals, medication adherence, and social determinants of health.

  • Care managers lacked a data-driven framework to prioritize follow-ups.

Our Approach

Built a canonical patient record combining EHR, lab feeds, wearable data & care management notes.

Implemented cohort progression algorithms to identify deterioration patterns.

Delivered care-pathway recommendations based on risk, comorbidity patterns & past response.

Provided dashboards for clinical, operational & population-health teams.

Impact Delivered

  • Avoidable readmissions dropped by 14% in high-risk patient cohorts.

  • Care-manager workload efficiency improved by 1.9× through intelligent prioritization.

  • Enabled early intervention for 28% of patients exhibiting silent deterioration signals.