Situation

A regional Medicaid managed care plan was losing high-acuity members during the post-COVID redetermination period but didn’t know why. Termination reason codes in 834 files contradicted what the state portal showed. Members were disappearing at rates that didn’t match any internal data source. No one inside the plan could reconcile the gap.

This wasn’t anyone’s fault. Everyone from leadership to field outreach was working with the data they had. The people closest to members often sensed something was wrong before anyone could prove it. Their intuition was right. The evidence sat buried in sources no one inside the plan was positioned to cross-reference.

The plan’s IT organization wasn’t the problem either. Solving an eligibility data problem at the intersection of 834 files, state portals, and supplemental notification files is a specialized capability. The plan needed a specialist. They called Agilian.

Solution

Rather than routing the problem through conventional IT channels, Agilian identified a non-IT stakeholder within the plan who had direct state portal access and could use that access to surface what the data actually showed. Within weeks, Agilian confirmed the root cause: structural gaps in how state eligibility data flowed, reconciled, and triggered action.

In six months, Agilian decoded the state’s eligibility data file by file. By January 2025, Agilian completed analysis of the full member universe and projected exposure for 2025. By February 2025, the roadmap for a full MVP build was in place.

The pilot focused exclusively on MLTSS and ABD populations, the highest-acuity, highest-value members in the plan. Outreach targeted members genuinely at risk, using the plan’s own portal data and 834 files, so care managers weren’t chasing members the state had already resolved. This prioritized targeting — later formalized as Agilian’s Smart List process — became the foundation for everything that followed.

Results

Working from accurate lists, the plan’s outreach team reinstated 128 high-acuity members during the pilot.

The pilot proved the model. A targeting methodology built from scratch that no internal team had been positioned to build. That foundation is what made everything that followed possible.

See what happened when the program scaled. →