National Trends in Mental Health-Related Emergency Department Visits Among Youth, 2011-2020.

Importance: There has been increasing concern about the burden of mental health problems among youth, especially since the COVID-19 pandemic. Trends in mental health-related emergency department (ED) visits are an important indicator of unmet outpatient mental health needs. Objective: To estimate annual trends in mental health-related ED visits among US children, adolescents, and young adults between 2011 and 2020. Design, Setting, and Participants: Data from 2011 to 2020 in the National Hospital Ambulatory Medical Care Survey, an annual cross-sectional national probability sample survey of EDs, was used to examine mental health-related visits for youths aged 6 to 24 years (unweighted = 49 515). Main Outcomes and Measures: Mental health-related ED visits included visits associated with psychiatric or substance use disorders and were identified by International Classification of Diseases-Ninth Revision, Clinical Modification (ICD-9-CM; 2011-2015) and ICD-10-CM (2016-2020) discharge diagnosis codes or by reason-for-visit (RFV) codes. We estimated the annual proportion of mental health-related pediatric ED visits from 2011 to 2020. Subgroup analyses were performed by demographics and broad psychiatric diagnoses. Multivariable-adjusted logistic regression analyses estimated factors independently associated with mental health-related ED visits controlling for period effects. Results: From 2011 to 2020, the weighted number of pediatric mental health-related visits increased from 4.8 million (7.7% of all pediatric ED visits) to 7.5 million (13.1% of all ED visits) with an average annual percent change of 8.0% (95% CI, 6.1%-10.1%; P < .001). Significant linearly increasing trends were seen among children, adolescents, and young adults, with the greatest increase among adolescents and across sex and race and ethnicity. While all types of mental health-related visits significantly increased, suicide-related visits demonstrated the greatest increase from 0.9% to 4.2% of all pediatric ED visits (average annual percent change, 23.1% [95% CI, 19.0%-27.5%]; P < .001). Conclusions and Relevance: Over the last 10 years, the proportion of pediatric ED visits for mental health reasons has approximately doubled, including a 5-fold increase in suicide-related visits. These findings underscore an urgent need to improve crisis and emergency mental health service capacity for young people, especially for children experiencing suicidal symptoms.

Comparing mental and physical health of U.S. veterans by VA healthcare use: implications for generalizability of research in the VA electronic health records.

OBJECTIVE: The Department of Veterans Affairs' (VA) electronic health records (EHR) offer a rich source of big data to study medical and health care questions, but patient eligibility and preferences may limit generalizability of findings. We therefore examined the representativeness of VA veterans by comparing veterans using VA healthcare services to those who do not. METHODS: We analyzed data on 3051 veteran participants age ≥ 18 years in the 2019 National Health Interview Survey. Weighted logistic regression was used to model participant characteristics, health conditions, pain, and self-reported health by past year VA healthcare use and generate predicted marginal prevalences, which were used to calculate Cohen's d of group differences in absolute risk by past-year VA healthcare use. RESULTS: Among veterans, 30.4% had past-year VA healthcare use. Veterans with lower income and members of racial/ethnic minority groups were more likely to report past-year VA healthcare use. Health conditions overrepresented in past-year VA healthcare users included chronic medical conditions (80.6% vs. 69.4%, d = 0.36), pain (78.9% vs. 65.9%; d = 0.35), mental distress (11.6% vs. 5.9%; d = 0.47), anxiety (10.8% vs. 4.1%; d = 0.67), and fair/poor self-reported health (27.9% vs. 18.0%; d = 0.40). CONCLUSIONS: Heterogeneity in veteran sociodemographic and health characteristics was observed by past-year VA healthcare use. Researchers working with VA EHR data should consider how the patient selection process may relate to the exposures and outcomes under study. Statistical reweighting may be needed to generalize risk estimates from the VA EHR data to the overall veteran population.

Implications of Telepsychiatry for Cost, Quality, and Equity of Mental Health Care.

This Viewpoint discusses overlapping challenges to multiple stakeholders as telepsychiatry continues to expand.

Trends in psychiatric diagnoses by COVID-19 infection and hospitalization among patients with and without recent clinical psychiatric diagnoses in New York city from March 2020 to August 2021.

Determining emerging trends of clinical psychiatric diagnoses among patients infected with the SARS-CoV-2 virus is important to understand post-acute sequelae of SARS-CoV-2 infection or long COVID. However, published reports accounting for pre-COVID psychiatric diagnoses have usually relied on self-report rather than clinical diagnoses. Using electronic health records (EHRs) among 2,358,318 patients from the New York City (NYC) metropolitan region, this time series study examined changes in clinical psychiatric diagnoses between March 2020 and August 2021 with month as the unit of analysis. We compared trends in patients with and without recent pre-COVID clinical psychiatric diagnoses noted in the EHRs up to 3 years before the first COVID-19 test. Patients with recent clinical psychiatric diagnoses, as compared to those without, had more subsequent anxiety disorders, mood disorders, and psychosis throughout the study period. Substance use disorders were greater between March and August 2020 among patients without any recent clinical psychiatric diagnoses than those with. COVID-19 positive patients (both hospitalized and non-hospitalized) had greater post-COVID psychiatric diagnoses than COVID-19 negative patients. Among patients with recent clinical psychiatric diagnoses, psychiatric diagnoses have decreased since January 2021, regardless of COVID-19 infection/hospitalization. However, among patients without recent clinical psychiatric diagnoses, new anxiety disorders, mood disorders, and psychosis diagnoses increased between February and August 2021 among all patients (COVID-19 positive and negative). The greatest increases were anxiety disorders (378.7%) and mood disorders (269.0%) among COVID-19 positive non-hospitalized patients. New clinical psychosis diagnoses increased by 242.5% among COVID-19 negative patients. This study is the first to delineate the impact of COVID-19 on different clinical psychiatric diagnoses by pre-COVID psychiatric diagnoses and COVID-19 infections and hospitalizations across NYC, one of the hardest-hit US cities in the early pandemic. Our findings suggest the need for tailoring treatment and policies to meet the needs of individuals with pre-COVID psychiatric diagnoses.

Association Between the Use of Psychotropic Medications and the Risk of COVID-19 Infection Among Long-term Inpatients With Serious Mental Illness in a New York State-wide Psychiatric Hospital System.

Importance: Individuals with serious mental illness are at increased risk of severe COVID-19 infection. Several psychotropic medications have been identified as potential therapeutic agents to prevent or treat COVID-19 but have not been systematically examined in this population. Objective: To evaluate the associations between the use of psychotropic medications and the risk of COVID-19 infection among adults with serious mental illness receiving long-term inpatient psychiatric treatment. Design, Setting, and Participants: This retrospective cohort study assessed adults with serious mental illness hospitalized in a statewide psychiatric hospital system in New York between March 8 and July 1, 2020. The final date of follow-up was December 1, 2020. The study included 1958 consecutive adult inpatients with serious mental illness (affective or nonaffective psychoses) who received testing for SARS-CoV-2 by reverse transcriptase-polymerase chain reaction or antinucleocapsid antibodies and were continuously hospitalized from March 8 until medical discharge or July 1, 2020. Exposures: Psychotropic medications prescribed prior to COVID-19 testing. Main Outcomes and Measures: COVID-19 infection was the primary outcome, defined by a positive SARS-CoV-2 reverse transcriptase-polymerase chain reaction or antibody test result. The secondary outcome was COVID-19-related death among patients with laboratory-confirmed infection. Results: Of the 2087 adult inpatients with serious mental illness continuously hospitalized during the study period, 1958 (93.8%) underwent testing and were included in the study; 1442 (73.6%) were men, and the mean (SD) age was 51.4 (14.3) years. A total of 969 patients (49.5%) had laboratory-confirmed COVID-19 infection that occurred while they were hospitalized; of those, 38 (3.9%) died. The use of second-generation antipsychotic medications, as a class, was associated with decreased odds of infection (odds ratio [OR], 0.62; 95% CI, 0.45-0.86), whereas the use of mood stabilizers was associated with increased odds of infection (OR, 1.23; 95% CI, 1.03-1.47). In a multivariable model of individual medications, the use of paliperidone was associated with decreased odds of infection (OR, 0.59; 95% CI, 0.41-0.84), and the use of valproic acid was associated with increased odds of infection (OR, 1.39; 95% CI, 1.10-1.76). Clozapine use was associated with reduced odds of mortality in unadjusted analyses (unadjusted OR, 0.25; 95% CI, 0.10-0.62; fully adjusted OR, 0.43; 95% CI, 0.17-1.12). Conclusions and Relevance: In this cohort study of adults hospitalized with serious mental illness, the use of second-generation antipsychotic medications was associated with decreased risk of COVID-19 infection, whereas the use of valproic acid was associated with increased risk. Further research is needed to assess the mechanisms that underlie these findings.

Substance use disorders and COVID-19: An analysis of nation-wide Veterans Health Administration electronic health records.

BACKGROUND: Substance use disorders (SUD) elevate the risk for COVID-19 hospitalization, but studies are inconsistent on the relationship of SUD to COVID-19 mortality. METHODS: Veterans Health Administration (VHA) patients treated in 2019 and evaluated in 2020 for COVID-19 (n=5,556,315), of whom 62,303 (1.1%) tested positive for COVID-19 (COVID-19+). Outcomes were COVID-19+ by 11/01/20, hospitalization, ICU admission, or death within 60 days of a positive test. Main predictors were any ICD-10-CM SUDs, with substance-specific SUDs (cannabis, cocaine, opioid, stimulant, sedative) explored individually. Logistic regression produced unadjusted and covariate-adjusted odds ratios (OR; aOR). RESULTS: Among COVID-19+ patients, 19.25% were hospitalized, 7.71% admitted to ICU, and 5.84% died. In unadjusted models, any SUD and all substance-specific SUDs except cannabis use disorder were associated with COVID-19+(ORs=1.06-1.85); adjusted models produced similar results. Any SUD and all substance-specific SUDs were associated with hospitalization (aORs: 1.24-1.91). Any SUD, cocaine and opioid disorder were associated with ICU admission in unadjusted but not adjusted models. Any SUD, cannabis, cocaine, and stimulant disorders were inversely associated with mortality in unadjusted models (OR=0.27-0.46). After adjustment, associations with mortality were no longer significant. In ad hoc analyses, adjusted odds of mortality were lower among the 49.9% of COVID-19+ patients with SUD who had SUD treatment in 2019, but not among those without such treatment. CONCLUSIONS: In VHA patients, SUDs are associated with COVID-19 hospitalization but not COVID-19 mortality. SUD treatment may provide closer monitoring of care, ensuring that these patients received needed medical attention, enabling them to ultimately survive serious illness.

Hepatitis C Screening Among Medicaid Patients With Schizophrenia, 2002-2012.

OBJECTIVE: Although people with schizophrenia are disproportionately affected by Hepatitis C virus (HCV) compared to the general population, HCV screening among US Medicaid recipients with schizophrenia has not been characterized. Following 1998 CDC recommendations for screening in high-risk populations, we estimated the proportion of Medicaid recipients with and without schizophrenia screened for HCV across states and over time. Examining patterns of screening will inform the current public health imperative to test all adults for HCV now that safer and more effective treatments are available. METHODS: Data are drawn from 1 353 424 Medicaid recipients aged 15-64 years with schizophrenia and frequency-matched controls from 2002 to 2012. Participants with known HCV infection one year prior and those dual-eligible for Medicare were excluded. Multivariable logistic regression estimated associations between predictor variables and HCV screening. RESULTS: HCV screening was low (<4%) but increased over time. Individuals with schizophrenia consistently showed higher screening compared to controls across years and states. Several demographic and clinical characteristics predicted higher screening, especially comorbid HIV (OR = 6.5; 95% CI = 6.0-7.0). Outpatient medical care utilization increased screening by nearly double in 2002 (OR = 1.8; CI = 1.7-1.9) and almost triple in 2012 (OR = 2.7; CI = 2.6-2.9). CONCLUSIONS: Low screening was a missed opportunity to improve HCV prevention efforts and reduce liver-related mortality among people with schizophrenia. Greater COVID-19 disease severity in HCV patients and the availability of effective HCV treatments increase the urgency to improve HCV screening. Eliminating Medicaid restrictions and expanding statewide HIV policies to include HCV would have multiple public health benefits, particularly for people with schizophrenia.

Associations between COVID-19 mobility restrictions and economic, mental health, and suicide-related concerns in the US using cellular phone GPS and Google search volume data.

During the COVID-19 pandemic, US populations have experienced elevated rates of financial and psychological distress that could lead to increases in suicide rates. Rapid ongoing mental health monitoring is critical for early intervention, especially in regions most affected by the pandemic, yet traditional surveillance data are available only after long lags. Novel information on real-time population isolation and concerns stemming from the pandemic's social and economic impacts, via cellular mobility tracking and online search data, are potentially important interim surveillance resources. Using these measures, we employed transfer function model time-series analyses to estimate associations between daily mobility indicators (proportion of cellular devices completely at home and time spent at home) and Google Health Trends search volumes for terms pertaining to economic stress, mental health, and suicide during 2020 and 2021 both nationally and in New York City. During the first pandemic wave in early-spring 2020, over 50% of devices remained completely at home and searches for economic stressors exceeded 60,000 per 10 million. We found large concurrent associations across analyses between declining mobility and increasing searches for economic stressor terms (national proportion of devices at home: cross-correlation coefficient (CC) = 0.6 (p-value <0.001)). Nationally, we also found strong associations between declining mobility and increasing mental health and suicide-related searches (time at home: mood/anxiety CC = 0.53 (<0.001), social stressor CC = 0.51 (<0.001), suicide seeking CC = 0.37 (0.006)). Our findings suggest that pandemic-related isolation coincided with acute economic distress and may be a risk factor for poor mental health and suicidal behavior. These emergent relationships warrant ongoing attention and causal assessment given the potential for long-term psychological impact and suicide death. As US populations continue to face stress, Google search data can be used to identify possible warning signs from real-time changes in distributions of population thought patterns.

Hydroxyzine Use and Mortality in Patients Hospitalized for COVID-19: A Multicenter Observational Study.

(1) Background: Based on its antiviral activity, anti-inflammatory properties, and functional inhibition effects on the acid sphingomyelinase/ceramide system (FIASMA), we sought to examine the potential usefulness of the H1 antihistamine hydroxyzine in patients hospitalized for COVID-19. (2) Methods: In a multicenter observational study, we included 15,103 adults hospitalized for COVID-19, of which 164 (1.1%) received hydroxyzine within the first 48 h of hospitalization, administered orally at a median daily dose of 25.0 mg (SD = 29.5). We compared mortality rates between patients who received hydroxyzine at hospital admission and those who did not, using a multivariable logistic regression model adjusting for patients' characteristics, medical conditions, and use of other medications. (3) Results: This analysis showed a significant association between hydroxyzine use and reduced mortality (AOR, 0.51; 95%CI, 0.29-0.88, p = 0.016). This association was similar in multiple sensitivity analyses. (4) Conclusions: In this retrospective observational multicenter study, the use of the FIASMA hydroxyzine was associated with reduced mortality in patients hospitalized for COVID-19. Double-blind placebo-controlled randomized clinical trials of hydroxyzine for COVID-19 are needed to confirm these results, as are studies to examine the potential usefulness of this medication for outpatients and as post-exposure prophylaxis for individuals at high risk for severe COVID-19.

Psychotropic medication prescribing during the COVID-19 pandemic.

ABSTRACT: This study examined changes in psychotropic medication use associated with the early months of the coronavirus disease 2019 (COVID-19) pandemic. Using Kaiser Permanente Northern California electronic health records, the authors identified adult patients with fills for psychotropic medications and a non-psychotropic comparator (statins) in the 13 weeks before and after the first-known COVID-19-related death in California (March 4, 2020). Generalized estimating equations were used to derive relative risk ratios (RRR) for medication fills compared with the prior year. Analyses were stratified by new and continued fills and patient characteristics. Among 2,405,824 patients, the mean (SD) age was 49.8 (17.9) years; 52.9% were female; 47.9% identified as White; 8.0% and 7.9% had anxiety and depression disorder diagnoses, respectively. Accounting for secular trends, in the 13 weeks following March 4, 2020, there were increased fills for trazodone (RRR = 1.03, 95% CI = 1.02, 1.04), decreased fills for benzodiazepines (RRR = 0.95, 95% CI = 0.94, 0.96) and hypnotics (RRR = 0.97, 95% CI = 0.96, 0.99), and stable fills for antidepressants (RRR = 1.00, 95% CI = 0.99, 1.00). Relative rates of new fills decreased across most medication classes and continued fills either remained stable or demonstrated non-clinically significant decreases. Patients aged ≥65 years demonstrated decreased fills for most medication classes. In the first 13 weeks of the COVID-19 pandemic, fills for most psychotropic medications remained constant or showed small changes relative to the previous year. Continued (compared with new) fills accounted for observed increases in some medication classes. Older adults demonstrated decreased fills of most medications.

COVID-19 Case Rates After Surveillance and Vaccinations in a Statewide Psychiatric Hospital System.

Individuals with serious mental illness are particularly vulnerable to COVID-19. The New York State (NYS) Office of Mental Health implemented patient and staff rapid testing, quarantining, and vaccination to limit COVID-19 spread in 23 state-operated psychiatric hospitals between November 2020 and February 2021. COVID-19 infection rates in inpatients and staff decreased by 96% and 71%, respectively, and the NYS population case rate decreased by 6%. Repeated COVID-19 testing and vaccination should be priority interventions for state-operated psychiatric hospitals. (Am J Public Health. 2021;111(10):1780-1783. https://doi.org/10.2105/AJPH.2021.306444).

Author Correction: A stochastic agent-based model of the SARS-CoV-2 epidemic in France.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Suicide and the agent-host-environment triad: leveraging surveillance sources to inform prevention.

Suicide in the US has increased in the last decade, across virtually every age and demographic group. Parallel increases have occurred in non-fatal self-harm as well. Research on suicide across the world has consistently demonstrated that suicide shares many properties with a communicable disease, including person-to-person transmission and point-source outbreaks. This essay illustrates the communicable nature of suicide through analogy to basic infectious disease principles, including evidence for transmission and vulnerability through the agent-host-environment triad. We describe how mathematical modeling, a suite of epidemiological methods, which the COVID-19 pandemic has brought into renewed focus, can and should be applied to suicide in order to understand the dynamics of transmission and to forecast emerging risk areas. We describe how new and innovative sources of data, including social media and search engine data, can be used to augment traditional suicide surveillance, as well as the opportunities and challenges for modeling suicide as a communicable disease process in an effort to guide clinical and public health suicide prevention efforts.

Association of Psychiatric Disorders With Mortality Among Patients With COVID-19.

Importance: To date, the association of psychiatric diagnoses with mortality in patients infected with coronavirus disease 2019 (COVID-19) has not been evaluated. Objective: To assess whether a diagnosis of a schizophrenia spectrum disorder, mood disorder, or anxiety disorder is associated with mortality in patients with COVID-19. Design, Setting, and Participants: This retrospective cohort study assessed 7348 consecutive adult patients for 45 days following laboratory-confirmed COVID-19 between March 3 and May 31, 2020, in a large academic medical system in New York. The final date of follow-up was July 15, 2020. Patients without available medical records before testing were excluded. Exposures: Patients were categorized based on the following International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnoses before their testing date: (1) schizophrenia spectrum disorders, (2) mood disorders, and (3) anxiety disorders. Patients with these diagnoses were compared with a reference group without psychiatric disorders. Main Outcomes and Measures: Mortality, defined as death or discharge to hospice within 45 days following a positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) test result. Results: Of the 26 540 patients tested, 7348 tested positive for SARS-CoV-2 (mean [SD] age, 54 [18.6] years; 3891 [53.0%] women). Of eligible patients with positive test results, 75 patients (1.0%) had a history of a schizophrenia spectrum illness, 564 (7.7%) had a history of a mood disorder, and 360 (4.9%) had a history of an anxiety disorder. After adjusting for demographic and medical risk factors, a premorbid diagnosis of a schizophrenia spectrum disorder was significantly associated with mortality (odds ratio [OR], 2.67; 95% CI, 1.48-4.80). Diagnoses of mood disorders (OR, 1.14; 95% CI, 0.87-1.49) and anxiety disorders (OR, 0.96; 95% CI, 0.65-1.41) were not associated with mortality after adjustment. In comparison with other risk factors, a diagnosis of schizophrenia ranked behind only age in strength of an association with mortality. Conclusions and Relevance: In this cohort study of adults with SARS-CoV-2-positive test results in a large New York medical system, adults with a schizophrenia spectrum disorder diagnosis were associated with an increased risk for mortality, but those with mood and anxiety disorders were not associated with a risk of mortality. These results suggest that schizophrenia spectrum disorders may be a risk factor for mortality in patients with COVID-19.

A stochastic agent-based model of the SARS-CoV-2 epidemic in France.

Many European countries have responded to the COVID-19 pandemic by implementing nationwide protection measures and lockdowns1. However, the epidemic could rebound when such measures are relaxed, possibly leading to a requirement for a second or more, repeated lockdowns2. Here, we present results of a stochastic agent-based microsimulation model of the COVID-19 epidemic in France. We examined the potential impact of post-lockdown measures, including physical distancing, mask-wearing and shielding individuals who are the most vulnerable to severe COVID-19 infection, on cumulative disease incidence and mortality, and on intensive care unit (ICU)-bed occupancy. While lockdown is effective in containing the viral spread, once lifted, regardless of duration, it would be unlikely to prevent a rebound. Both physical distancing and mask-wearing, although effective in slowing the epidemic and in reducing mortality, would also be ineffective in ultimately preventing ICUs from becoming overwhelmed and a subsequent second lockdown. However, these measures coupled with the shielding of vulnerable people would be associated with better outcomes, including lower mortality and maintaining an adequate ICU capacity to prevent a second lockdown. Benefits would nonetheless be markedly reduced if most people do not adhere to these measures, or if they are not maintained for a sufficiently long period.