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Factors associated with higher healthcare costs in individuals living with arthritis : evidence from the quantile regression approach
journal contribution
posted on 2017-12-06, 00:00 authored by T Lo, Lynne Parkinson, M Cunich, J BylesObjective: To examine the factors associated with higher healthcare cost in women with arthritis, using generalized linear models (GLMs) and quantile regression (QR). Methods: This is a cross-sectional healthcare cost study of individuals with arthritis that focused on older Australian women. Cost data were drawn from the Medicare Australia datasets. Results: GLM results show that healthcare cost was significantly associated with various socio-demographic and health factors. Although QR analysis results show the same direction of association between these factors and healthcare cost as in the GLMs, they indicate progressively increased effect sizes at the 50th, 75th, 90th and 95th percentiles. Conclusion: Findings suggest traditional regression models such as GLMs that assume a single rate of change to accurately describe the relationships between explanatory variables and healthcare costs across the entire distribution of cost can produce biased results. QR should be considered in future healthcare cost research.
History
Volume
15Issue
5Start Page
833End Page
841Number of Pages
9eISSN
1744-8379ISSN
1473-7167Location
USAPublisher
Taylor & FrancisPublisher DOI
Full Text URL
Language
en-ausPeer Reviewed
- Yes
Open Access
- No
Era Eligible
- Yes