ABSTRACT
PURPOSE: Access to research programs and increased diversity in research enrollment may be key to improving diverse populations' health and healthcare outcomes. To facilitate research recruitment, a Research Registry ("Registry"), a pre-recruitment database, was developed at an urban tertiary Autism Center ("Autism Center"). In this study, we examined whether disparities in research participation occur in the pre-research recruitment (pre-recruitment) stage. METHODS: We compared demographic factors of patients seen at the Autism Center (but not enrolled in the Registry) vs. patients enrolled in the Registry. We also examined whether demographic factors differ among the Registry participants who were enrolled in the Registry by signing an informed consent form (ICF) vs. by returning a research interest form (RIF). RESULTS: A total of 18,522 patients (including 1092 patients in the Registry with 403 patients via ICF and 689 patients via RIF) were included in this study. English as the primary language, White race, Non-Hispanic ethnicity, and younger age at their first clinic encounter were associated with the Registry. In the Registry sample, the RIF group had a higher proportion of non-English as a primary language, Medicaid insurance, longer distance from the Autism Center, and lower median household income (based on their ZIP code) than the ICF group. CONCLUSIONS: This study suggests that disparities may have existed in the pre-research recruitment stage. To achieve equity in both clinical and research advancements in autism and related developmental disorders, further efforts are needed to equitably disseminate research opportunities to patients of diverse backgrounds.
ABSTRACT
High but variable rates of psychotropic polypharmacy (PP) in youth with autism spectrum disorder (ASD) have been reported in previous studies. The effect of the COVID-19 pandemic on prescribing patterns has not been well described. This study aims to examine the factors associated with psychotropic prescribing patterns, including rates of PP and multiclass polypharmacy (MPP) in youth with ASD during the COVID-19 pandemic. We examined the prescription records and clinical characteristics of youth aged between 3−21 years with a clinical diagnosis of ASD who were followed at an urban tertiary autism center psychiatry clinic between 1 January 2019, and 31 December 2020. For study purposes, we treated 2019 as the pre-pandemic year and 2020 as the pandemic year and compared the clinical characteristics of the "total clinic cohort (n = 898)" across two years. We examined the clinical characteristics of patients seen in both years ("paired-sample," n = 473) and those seen only in 219 ("not-paired sample," n = 378) to identify factors associated with the likelihood of patients' return to clinic in 2020. As the total clinic cohort was a naturalistic sample containing duplicate patients, we created a separate data set by randomly assigning duplicate patients to one of the years ("random unique sample," n = 898) and examined the clinical characteristics across two years. We defined PP and MPP broadly as the use of ≥2 unique medications (PP) and ≥2 unique medication classes (MPP) within a calendar year in this study. In the total clinic cohort, increased rates of PP (71.6% to 75.6%), MPP (61.9% to 67.8%, p = 0.027), and antidepressant prescriptions (56.9% to 62.9%, p = 0.028) were noted, although only the latter two were nominally significant. The paired-sample had a higher proportion of teens (31.0% vs. 39.7%, p < 0.001 and persons who self-identified as non-Hispanic (77.8% vs. 85.4%, p = 0.016)), higher rates of anxiety (78.9% vs. 48.7%, p < 0.001), ADHD (71.0% vs. 44.4%, p < 0.001), depression (23.9% vs. 13.0%, p < 0.001) and disruptive behavior (63.3% vs. 33.3%, p < 0.001) diagnoses, higher rates of antidepressants (63.4% vs. 48.7%, p < 0.001), ADHD medications (72.5% vs. 59.8%, p < 0.001), and antipsychotics (36.8% vs. 26.2%, p < 0.001) prescribed, and higher rates of PP (81.6% vs. 59.0%, p < 0.001) and MPP (71.0% vs. 50.5%, p < 0.001) than the not-paired sample. In the random unique sample, the patient group assigned to 2020 had higher rates of anxiety (75.0% vs. 60.2%, p < 0.001), ADHD (69.9% vs. 54.6%, p < 0.001), and disruptive behavior (57.9% vs. 45.4%, p < 0.001) diagnoses but the PP and MPP rates did not differ across years. Overall, we found high rates of PP and MPP, likely due to the broader definition of PP and MPP used in this study than those in other studies as well as the study site being a tertiary clinic. While our study suggests a possible impact of the COVID-19 pandemic on comorbidity rates and prescribing patterns, a replication study is needed to confirm how pandemic-related factors impact prescribing patterns and polypharmacy rates in youth with ASD.
ABSTRACT
Objectives: The Seattle Children's Autism Center (SCAC) serves youth throughout Washington state (WA). The authors examined (1) whether the ethnicity and race of patients seen at the SCAC aligned with the demographics reported in the WA census, and (2) whether psychotropic medication prescriptions were associated with patient factors, including age, sex, ethnicity, race, insurance, visit number, and diagnoses. Methods: The authors extracted demographic and prescription data from electronic medical records for all patients (3-21 years) seen at the SCAC in 2018 for psychiatric medication evaluation in the context of autism spectrum disorder (ASD) and/or other related neurodevelopmental disorder (n = 1112), and used binary logistic regression to ascertain the effects of patient factors on psychotropic prescriptions. Results: The SCAC study sample appeared to align well with the WA census. Older age and higher visit number were among the most significant factors associated with psychotropic prescriptions. Psychotropic prescriptions increased with age, across all categories, except attention-deficit/hyperactivity disorder medications. There were no sex differences in prescribing rates. There were differences in prescribing rates by ethnicity and race. There were also increased prescription rates among those with Medicaid insurance. Conclusion: These demographic differences in prescribing for youth with ASD provide more specificity than prior studies about sex, ethnic, racial, and insurance-related differences, and can serve as an impetus to examine the reasons for variance.
