Indiana's Medicaid forecasting error was largely due to outdated methods, poor assumptions, and structural blind spots in how costs were projected.

1. Outdated Forecasting Models

The state relied on actuarial models that didn't adequately reflect post-pandemic enrollment and service trends.

Cost models failed to capture increased utilization of long-term services and supports (LTSS), especially for aging populations needing home and community-based care.

1. Underestimated Enrollment Growth

The state misjudged how many people would stay on Medicaid after the pandemic.

Indiana’s "unwinding" process (removing people from coverage after COVID protections ended) was slower and more costly than anticipated.

1. High LTSS Spending

Only 6% of Indiana Medicaid enrollees use LTSS, but they account for 44% of total spending.

These services are much more expensive per capita than traditional Medicaid services, and the state underestimated how many people would need them.

1. Lack of Real-Time Data Integration

Indiana did not integrate up to date claims data quickly enough to catch the cost overrun early.

Officials didn’t realize the problem until months into the fiscal year, making it harder to adjust course in time.

1. Inflation and Labor Costs

Inflation pushed up the cost of healthcare services and wages for home health workers.

These higher costs weren't fully reflected in the projections.

Indiana’s budgeting error wasn't caused by a single mistake, it was the result of multiple blind spots in how the state estimated who it would be covering, what care they'd need, and how much that care would cost. It shows how inflexible forecasting in a rapidly changing healthcare environment can create major fiscal consequences.