Attributing medical spending to conditions: A comparison of methods

Area of Science:

• Health Economics
• Medical Cost Analysis
• Biostatistics

Background:

• Accurate partitioning of medical spending by condition is crucial for understanding healthcare costs.
• Existing methods include claims-based attribution and regression analysis, each with limitations.

Purpose of the Study:

• To develop and evaluate a novel propensity score analysis method for attributing medical spending to specific health conditions.
• To compare the performance of the propensity score approach against traditional claims-based and regression methods.

Main Methods:

• Development of a propensity score-based cost attribution model.
• Application of the propensity score, claims-based, and regression methods to Medicare beneficiaries aged 65+ (2009 data).
• Comparative analysis of spending allocation across the three methodologies.

Main Results:

• Significant differences in disease-specific spending allocation were observed among the three methods.
• The propensity score approach demonstrated a theoretically and empirically superior combination for cost attribution.
• The study highlights the impact of methodology on understanding the cost burden of medical care.

Conclusions:

• The propensity score method provides a more flexible and potentially accurate approach to disease-specific cost attribution.
• Healthcare economic research should consider advanced statistical methods like propensity score analysis for more precise spending allocation.
• Findings have implications for healthcare policy, resource allocation, and understanding the true cost burden of various medical conditions.