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Clin Epidemiol. 2017 Dec 14;9:689-698. doi: 10.2147/CLEP.S145353. eCollection 2017.

The use of random-effects models to identify health care center-related characteristics modifying the effect of antipsychotic drugs.

Author information

1
Epidemiological Research, Analytica LASER, Paris.
2
Population Health Research Center, Team Pharmaco-Epidemiology, UMR 1219, Bordeaux-2 University, INSERM, Bordeaux, France.
3
Parc Sanitari Sant Joan de Deu, CIBERSAM, University of Barcelona, Barcelona, Spain.
4
Eli Lilly and Company Limited, Erl Wood Manor, Windlesham.
5
Farr Institute, University of Manchester, Manchester, UK.

Abstract

Purpose:

A case study was conducted, exploring methods to identify drugs effects modifiers, at a health care center level.

Patients and methods:

Data were drawn from the Schizophrenia Outpatient Health Outcome cohort, including hierarchical information on 6641 patients, recruited from 899 health care centers from across ten European countries. Center-level characteristics included the following: psychiatrist's gender, age, length of practice experience, practice setting and type, countries' Healthcare System Efficiency score, and psychiatrist density in the country. Mixed multivariable linear regression models were used: 1) to estimate antipsychotic drugs' effectiveness (defined as the association between patients' outcome at 3 months - dependent variable, continuous - and antipsychotic drug initiation at baseline - drug A vs other antipsychotic drug); 2) to estimate the similarity between clustered data (using the intra-cluster correlation coefficient); and 3) to explore antipsychotic drug effects modification by center-related characteristics (using the addition of an interaction term).

Results:

About 23% of the variance found for patients' outcome was explained by unmeasured confounding at a center level. Psychiatrists' practice experience was found to be associated with patient outcomes (p=0.04) and modified the relative effect of "drug A" (p<0.001), independent of center- or patient-related characteristics.

Conclusion:

Mixed models may be useful to explore how center-related characteristics modify drugs' effect estimates, but require numerous assumptions.

KEYWORDS:

effect modification; effectiveness; health care system; hierarchical model; schizophrenia

Conflict of interest statement

Disclosure Lucien Abenhaim is the chairman of LASER Analytica, and Clementine Nordon has been employed by LASER Analytica, a research and consultancy company collaborating with virtually all pharmaceutical companies. LASER has no commercial interests in any of the products studied. Members of the LASER network have no interest in a drug or other factors studied. Josef Maria Haro works at the Sant Joan de Déu Health Park in Barcelona, Spain. Mark Belger is an employee of Eli Lilly and Company Limited. Helene Verdoux is a clinician at Bordeaux University Hospital. Constance Battin and Tjeerd van Staa report no conflicts of interest in this work.

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