AI-Powered Diabetes Management Program

The Challenge

The health plan’s diabetes management program relied heavily on manual processes and static analytics. Member risk identification often lagged behind real-time data, meaning outreach and interventions were delayed or missed altogether. Teams across clinical, operational, and outreach functions worked from different datasets, creating inconsistent engagement and poor visibility into outcomes. To reach more members earlier, the organization needed a smarter, integrated approach to triage, engagement, and follow-up — one that could flex with evolving data and regulatory requirements.

The Solution

Productive Edge introduced the Healthcare AI Factory framework to help the health plan operationalize AI across its population health programs. The project began by aligning stakeholders on measurable goals: early identification, member engagement, and care coordination. The team integrated claims, clinical, and social determinants of health (SDOH) data into a unified environment. Through the Boost Foundry, Productive Edge developed reusable triage logic and AI models that could predict risk, prioritize outreach, and guide next best actions — all explainable and fully auditable. The solution also automated the delivery of personalized messages and scheduling prompts, enabling care teams to focus on higher-value interactions.

The Results

The new AI-enabled triage and outreach program improved early identification of at-risk members by 20% and increased engagement by 35%. Outreach workflows that previously required days of manual coordination were executed automatically, ensuring timely follow-up. All AI logic was transparent and compliant, supporting ongoing optimization and regulatory alignment. The Factory model now powers additional chronic disease programs, utilizing the same reusable intelligence that has proven successful in diabetes management.