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Initial Antidepressant Choice by Non-Psychiatrists: Learning from Large-scale Electronic Health Records

By Yi-han Sheu, Colin Magdamo, Matthew Miller, Jordan W. Smoller, Deborah Blacker

Posted 04 Aug 2021
medRxiv DOI: 10.1101/2021.08.02.21260076

Introduction. Pharmacological treatment of depression mostly occurs in non-psychiatric settings, but factors that determine the initial choice of antidepressant treatment in these settings are not well-understood. This study models how non-psychiatrists choose among four antidepressant classes at first prescription (selective serotonin reuptake inhibitors [SSRI], bupropion, mirtazapine, or serotonin-norepinephrine reuptake inhibitors [SNRI]), by analyzing electronic health record (EHR) data. Methods. EHR data were from the Mass General Brigham Healthcare System (Boston, Massachusetts, USA) for the period from 1990 to 2018. From a literature search and expert consultation, we selected 64 variables that may be associated with antidepressant choice. Patients who participated in the study were aged 18 to 65 at the time of first antidepressant prescription with a co-occurring International Classification of Diseases (ICD) code for a depressive disorder. Multinomial logistic regression with main effect terms for all 64 variables was used to model the choice of antidepressant. Using SSRI as the reference class, odds ratios, 95% confidence intervals (CI), and likelihood ratio-based p-values for each variable were reported. We used a false discovery rate (FDR) with the Benjamini-Hochberg procedure to correct for multiple comparisons. Findings. A total of 47,107 patients were included after application of inclusion/exclusion criteria. We observed significant associations for 36 of 64 variables after multiple comparison corrections. Many of these associations suggested that antidepressants' known pharmacological properties/actions guided choice. For example, there was a decreased likelihood of bupropion prescription among patients with epilepsy (adjusted OR 0.41, 95% CI: 0.33-0.51, p < 0.001), an increased likelihood of mirtazapine prescription among patients with insomnia (adjusted OR 1.58, 95% CI: 1.39-1.80, p < 0.001), and an increased likelihood of SNRI prescription among patients with pain (adjusted OR 1.22, 95% CI: 1.11-1.34, p = 0.001). Interpretation. Non-psychiatrists' selection of antidepressant class appears to be guided by clinically relevant pharmacological properties, indications, and contraindications, suggesting that broadly speaking they choose antidepressants based on meaningful differences among medication classes.

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