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Published in: Journal of Public Health 1/2019

01-02-2019 | Original Article

Comparing single-level and multilevel regression analysis for risk adjustment of treatment outcomes in common mental health disorders

Authors: Lisanne Warmerdam, Edwin de Beurs, Marko Barendregt, Jos Twisk

Published in: Journal of Public Health | Issue 1/2019

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Abstract

Aim

The aim of this paper is to compare single-level and multilevel regression analysis to obtain risk-adjusted outcomes from mental health care providers.

Subject and methods

The study population consisted of adult patients receiving treatment for common mental health disorders. The outcome was self-reported symptom level at post-test. Risk adjustment models were developed using single- and multilevel regression analysis. In the multilevel approach, a random intercept for each provider was included. The intraclass correlation coefficient was used to estimate the proportion of variability in treatment outcome between providers. Spearman correlation coefficient of ranks was used to compare results between the two approaches.

Results

The effects of most casemix variables on outcomes were similar for the two models. The ranking of providers in both methods was also quite similar (ρ = .99). The multilevel model estimated that 5.4% of total variability in adjusted post-test scores was explained by the provider factor.

Conclusions

The findings of risk adjustment of mental health outcomes are quite robust for the use of single-level or multilevel regression analysis in the current study. However, given the small but significant amount of variation in outcomes that is attributable to providers, the multilevel approach is recommended for dealing with outcomes when patients are clustered within providers.
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Metadata
Title
Comparing single-level and multilevel regression analysis for risk adjustment of treatment outcomes in common mental health disorders
Authors
Lisanne Warmerdam
Edwin de Beurs
Marko Barendregt
Jos Twisk
Publication date
01-02-2019
Publisher
Springer Berlin Heidelberg
Published in
Journal of Public Health / Issue 1/2019
Print ISSN: 2198-1833
Electronic ISSN: 1613-2238
DOI
https://doi.org/10.1007/s10389-018-0921-9

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