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

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

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.