Estimating True Patient Cost-Sharing Burden: Multi-Payer Claim Reconciliation in an All-Payer Claims Database

Area of Science:

• Health Services Research
• Health Economics
• Data Science in Healthcare

Background:

• All-payer claims databases (APCDs) aggregate data from multiple insurance providers for patient-level analysis.
• Accurate estimation of patient cost-sharing is crucial for healthcare research and policy.
• Existing methods may overestimate patient costs by not accounting for secondary and tertiary payer reimbursements.

Purpose of the Study:

• To develop and validate an algorithm for reconciling payments across multiple payers to accurately estimate patient cost-sharing.
• To assess the impact of payment reconciliation on cost-sharing estimates within an APCD cohort.

Main Methods:

• Developed a novel algorithm to reconcile payments from secondary and tertiary payers with primary insurance claims.
• Applied the reconciliation algorithm to a cancer cohort (n=70,100) within a Colorado APCD.
• Compared estimated cost-sharing before and after reconciliation for patients with multiple insurance sources.

Main Results:

• Reconciliation markedly lowered estimated patient cost-sharing, from $5,544 (no reconciliation) to $1,580 for patients with multiple payers.
• Significant cost-sharing reductions were observed for specific insurance combinations: Traditional Medicare with Medigap (-$5,326), dual Medicare-Medicaid (-$2,099), and Medicaid-commercial (-$699).
• Excluding secondary payments systematically inflates cost-sharing estimates.

Conclusions:

• A transparent reconciliation algorithm is essential for accurately estimating patient cost-sharing using APCD data.
• The developed algorithm provides a more precise measure of out-of-pocket expenses for individuals with complex insurance coverage.
• Researchers and policymakers should adopt such reconciliation methods for reliable cost estimation and informed decision-making.