Determinants of U.S. Prescription Drug Utilization using County Level Data

Area of Science:

• Health Economics
• Econometrics
• Public Health

Background:

• Prescription drugs represent a major U.S. healthcare expenditure.
• Medicare Part D and the Affordable Care Act have increased prescription drug utilization.
• Understanding prescription drug utilization determinants is crucial for policy and cost management.

Purpose of the Study:

• To investigate the determinants of prescription drug utilization at the county level in the U.S.A.
• To analyze how factors like health status, access to care, socioeconomic, and demographic variables correlate with prescription drug use.
• To examine these correlations separately for states categorized as low, medium, and high prescription drug users.

Main Methods:

• Utilized 2011 county-level data from the U.S.A.
• Employed variance-stabilizing Box-Cox power transformation regression models due to skewed prescription data.
• Partitioned states into low, medium, and high prescription drug utilization groups for separate model fitting.

Main Results:

• Optimal Box-Cox transformation parameters (λ) varied across utilization groups: high (λ=0.214), medium (λ=0.942), and low (λ=0.302).
• Estimated income elasticities differed significantly: -0.634 (high), 0.031 (medium), and -0.532 (low) utilization models.
• Economic behavior related to prescription drugs is not uniform across different utilization levels.

Conclusions:

• Prescription drug utilization determinants are heterogeneous across U.S. states based on usage levels.
• Policy interventions targeting prescription drug use should consider state-specific utilization patterns and economic factors.
• The findings highlight the need for nuanced approaches to managing prescription drug expenditures.