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

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.