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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 06.12.2017, 00:00 authored by T Lo, Lynne Parkinson, M Cunich, J Byles
Objective: 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

15

Issue

5

Start Page

833

End Page

841

Number of Pages

9

eISSN

1744-8379

ISSN

1473-7167

Location

USA

Publisher

Taylor & Francis

Language

en-aus

Peer Reviewed

Yes

Open Access

No

Era Eligible

Yes

Journal

Expert review of pharmacoeconomics & outcomes research.