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Journal of Public Health

, Volume 27, Issue 1, pp 29–35 | Cite as

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

  • Lisanne WarmerdamEmail author
  • Edwin de Beurs
  • Marko Barendregt
  • Jos Twisk
Original Article
  • 52 Downloads

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.

Keywords

Risk adjustment Mental health care Multilevel analysis Outcomes 

Notes

Compliance with ethical standards

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

The Dutch Central Medical Ethical Committee (CCMO) has ruled that Dutch Law regarding research with humans does not apply to the collection of anonymized information and, consequently, providing SBG with this data and analyzing anonymized data for the present study does not require additional informed consent from participants.

Conflicts of interest

The authors declare that they have no conflicts of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Lisanne Warmerdam
    • 1
    Email author
  • Edwin de Beurs
    • 1
  • Marko Barendregt
    • 1
  • Jos Twisk
    • 2
    • 3
  1. 1.Stichting Benchmark GGZ (the Dutch Benchmark Foundation in Mental Health Care)Bilthoventhe Netherlands
  2. 2.Department of Epidemiology & BiostatisticsVU University Medical CenterAmsterdamthe Netherlands
  3. 3.Department of Health SciencesVU UniversityAmsterdamthe Netherlands

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