Trends in central nervous system-active polypharmacy among people with multiple sclerosis.

BACKGROUND: People with multiple sclerosis (pwMS) are at risk of concurrently using multiple central nervous system (CNS)-active drugs, yet the prevalence of CNS-active polypharmacy remains unmeasured in pwMS. OBJECTIVE: The objective is to measure the prevalence of CNS-active polypharmacy in pwMS. METHODS: This serial, cross-sectional study measured CNS-active polypharmacy in people with MS in the United States from 2008 to 2021 using insurance claims data. CNS-active polypharmacy was defined as the concurrent prescription of ⩾3 CNS-active drugs for >30 continuous days. CNS-active drugs included antidepressants, antiepileptics, antipsychotics, benzodiazepines, nonbenzodiazepine benzodiazepine receptor agonist hypnotics, opioids, and skeletal muscle relaxants. RESULTS: The number of subjects included at each time point ranged from 23,917 subjects in 2008 to 55,797 subjects in 2021. In 2021, subjects with CNS-active polypharmacy were more likely to be 46-65 years of age and have CNS-related comorbidities compared to those without CNS-active polypharmacy. From 2008 to 2021, the age-adjusted prevalence of CNS-active polypharmacy among female subjects increased from 19.8% (95% confidence interval (CI) = 19.1-20.4) to 26.4% (95% CI = 25.9-26.8) versus 15.9% (95% CI = 14.8-17.0) to 18.6% (95% CI = 17.9-19.2) in male subjects. CONCLUSION: The prevalence of CNS-active polypharmacy has increased among people with MS with a growing disparity by sex.

COVID-19 severity scale for claims data research.

OBJECTIVE: To create and validate a methodology to assign a severity level to an episode of COVID-19 for retrospective analysis in claims data. DATA SOURCE: Secondary data obtained by license agreement from Optum provided claims records nationally for 19,761,754 persons, of which, 692,094 persons had COVID-19 in 2020. STUDY DESIGN: The World Health Organization (WHO) COVID-19 Progression Scale was used as a model to identify endpoints as measures of episode severity within claims data. Endpoints used included symptoms, respiratory status, progression to levels of treatment and mortality. DATA COLLECTION/EXTRACTION METHODS: The strategy for identification of cases relied upon the February 2020 guidance from the Centers for Disease Control and Prevention (CDC). PRINCIPAL FINDINGS: A total of 709,846 persons (3.6%) met the criteria for one of the nine severity levels based on diagnosis codes with 692,094 having confirmatory diagnoses. The rates for each level varied considerably by age groups, with the older age groups reaching higher severity levels at a higher rate. Mean and median costs increased as severity level increased. Statistical validation of the severity scales revealed that the rates for each level varied considerably by age group, with the older ages reaching higher severity levels (p < 0.001). Other demographic factors such as race and ethnicity, geographic region, and comorbidity count had statistically significant associations with severity level of COVID-19. CONCLUSION: A standardized severity scale for use with claims data will allow researchers to evaluate episodes so that analyses can be conducted on the processes of intervention, effectiveness, efficiencies, costs and outcomes related to COVID-19.

Incidence rate of psychiatric disorders in 2020: The pivotal role played by SARS-CoV-2 infection.

IMPORTANCE: The Coronavirus Disease (COVID-19) pandemic has significantly impacted mental health outcomes. While the frequency of anxiety and depressive symptoms has increased in the whole population, the relationship between COVID-19 and new psychiatric diagnoses remains unclear. OBJECTIVE: To compare the population incidence rate of emergence of de novo psychiatric disorders in 2020 compared to the previous years, and to compare the incidence rate of new psychiatric disorder diagnoses between people with vs without COVID-19. DESIGN, SETTING, AND PARTICIPANTS: This study utilized administrative claims data from the Clinformatics® Data Mart database, licensed from Optum®. The study is a cross-sectional analysis that compared the incidence rate of new psychiatric disorders in 2020 vs. 2018 and 2019 in the entire insured population database. Subsequently, the incidence of new psychiatric disorders in people with vs. without COVID-19 during 2020 was analyzed. EXPOSURE: The exposures included diagnosis and severity of COVID-19 infection. MAIN OUTCOMES MEASURES: The dependent variables of interest were the incidence rates of new psychiatric disorders, specifically schizophrenia spectrum disorders, mood disorders, anxiety disorders, and obsessive-compulsive disorder. RESULTS: The population studied included 10,463,672 US adults (mean age 52.83, 52% female) who were unique people for the year of 2020. Incidence of newly diagnosed psychiatric disorders per 1,000 individuals in the 2020 whole population were 28.81 (CI: 28.71, 28.92) for anxiety disorders, 1.04 (CI: 1.02, 1.06) for schizophrenia disorders, 0.42 (CI: 0.41, 0.43) for OCD and 28.85 (CI: 28.75, 28.95) for mood disorders. These rates were not significantly higher than 2018 or 2019. When comparing incidence rates between COVID-19 vs. non-COVID-19 populations in 2020, the rates were significantly higher in the COVID-19 population: 46.89 (CI: 46.24, 47.53) for anxiety, 49.31 (CI: 48.66, 49.97) for mood disorders, 0.57 (CI: 0.50, 0.65) for OCD, and 3.52 (CI: 3.34, 3.70) for schizophrenia. COVID-19 severity was significantly associated with new diagnoses of schizophrenia, anxiety and mood disorders in multivariate analyses. CONCLUSIONS: Compared to 2018 and 2019, in 2020 there was no increased incidence of new psychiatric disorders in the general population based on insurance claims data. Importantly, people with COVID-19 were more likely to be diagnosed with a new psychiatric disorder, most notably disorders with psychosis, indicating a potential association between COVID-19 and mental/brain health.