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Exploring the variation in state-level prescription utilization using a triangulation of analytic methods
Mustafa Hussein1, Lawrence M Brown2
1Health Outcomes and Policy Research (HOPR) Graduate Program, The University of Tennessee Health Science Center, Memphis, TN, USA.
State prescription drug use varies widely. Higher utilization is linked to more Medicaid/private insurance and nurse practitioners, but less physical activity. Chronic conditions also play a role.
Area of Science:
- Health Services Research
- Pharmaceutical Policy
- Public Health
Background:
- State-level prescription drug utilization shows significant variation, with rates differing substantially across the US.
- Empirical investigations into the drivers of this wide variation in prescription fills have been limited.
Purpose of the Study:
- To identify factors contributing to the observed disparities in prescription drug utilization across different US states.
- To explore the relationship between sociodemographic, health, insurance, and provider characteristics and prescription fill rates.
Main Methods:
- Utilized pooled cross-sectional data from 2008-2010 for all 50 states and DC.
- Employed multivariable regression models (linear, negative binomial, ordered logit) to analyze prescription utilization.
- Incorporated principal components analysis to manage multicollinearity among explanatory variables.
Main Results:
- Higher prescription utilization correlated with increased employer-sponsored insurance and Medicaid coverage.
- Greater density of nurse practitioners was associated with higher utilization; higher physician density showed an inverse relationship.
- Increased physical activity was linked to lower prescription use, while chronic conditions affected utilization levels but not high-utilization likelihood.
Conclusions:
- Variations in provider types, insurance coverage (Medicaid/private), and chronic disease prevalence appear to influence state prescription drug utilization.
- Further research is recommended to elucidate the specific mechanisms through which these factors impact state-level prescription patterns.
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