Metabolic Monitoring Rates of Youth Treated with Second-Generation Antipsychotics in Usual Care: Results of a Large US National Commercial Health Plan.

Objectives

To examine metabolic monitoring rates in commercially insured children and adolescents treated with a second-generation antipsychotic (SGA) during calendar years (CYs) 2016 and 2017.

Methods

In this retrospective study, data were collected from a large national commercial health plan for the period covering January 1, 2016 to December 31, 2017. Commercially insured children and adolescents, aged 8-19 years with ≥2 SGA prescription claims during the CY, were identified for the CY2016 and CY2017 cohorts. The primary outcome of interest was the percentage of subjects with any glucose or lipid metabolism parameter monitoring. Other calculated metabolic testing rates included glucose, hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL-C), other cholesterol (including triglycerides), and combined glucose and lipid metabolism testing (≥1 test for blood glucose or HbA1c and ≥1 test for LDL-C or other cholesterol).

Results

In CY2016 and CY2017, 1502 and 1239 subjects, respectively, were identified for this study. The most common psychiatric diagnoses in CY2016 and CY2017 were major depressive disorder (57.1%, 56.5%, respectively), anxiety disorders (42.9%, 47.5%), attention-deficit/hyperactivity disorder (41.6%, 45.8%), and bipolar disorder (24.1%, 25.9%). The rate of any metabolic testing was 53.5% in CY2016 and 51.3% in CY2017. Glucose testing (50.3%, 46.9%, respectively) was most common in both CYs, followed by LDL-C testing (31.2%, 28.5%). Rates of combined glucose and lipid metabolism testing were 30.7% in CY2016 and 26.9% in CY2017.

Conclusions

Given the known potential for adverse cardiometabolic effects, rates of metabolic monitoring associated with SGA use in children and adolescents urgently need to be improved. There is a critical need for understanding barriers to routine monitoring, particularly of lipids, and developing interventions to enhance metabolic monitoring.