OBJECTIVES

To describe the proportion of pediatric mental health emergency department (MH-ED) visits across 5 COVID-19 waves in New York City (NYC) and to examine the relationship between MH-ED visits, COVID-19 prevalence, and societal restrictions.

METHODS

We conducted a time-series analysis of MH-ED visits among patients ages 5 to 17 years using the INSIGHT Clinical Research Network, a database from 5 medical centers in NYC from January 1, 2016, to June 12, 2022. We estimated seasonally adjusted changes in MH-ED visit rates during the COVID-19 pandemic, compared with predicted prepandemic levels, specific to each COVID-19 wave and stratified by mental health diagnoses and sociodemographic characteristics. We estimated associations between MH-ED visit rates, COVID-19 prevalence, and societal restrictions measured by the Stringency Index.

RESULTS

Of 686 500 ED visits in the cohort, 27 168 (4.0%) were MH-ED visits. The proportion of MH-ED visits was higher during each COVID-19 wave compared with predicted prepandemic trends. Increased MH-ED visits were seen for eating disorders across all waves; anxiety disorders in all except wave 3; depressive disorders and suicidality/self-harm in wave 2; and substance use disorders in waves 2, 4, and 5. MH-ED visits were increased from expected among female, adolescent, Asian race, high Child Opportunity Index patients. There was no association between MH-ED visits and NYC COVID-19 prevalence or NY State Stringency Index.

CONCLUSIONS

The proportion of pediatric MH-ED visits during the COVID-19 pandemic was higher during each wave compared with the predicted prepandemic period, with varied increases among diagnostic and sociodemographic subgroups. Enhanced pediatric mental health resources are essential to address these findings.

What’s Known on This Subject:

Pediatric mental health emergencies have increased throughout the COVID-19 pandemic and continues to rise.

What This Study Adds:

This time-series analysis of 5 waves of COVID-19 in New York City demonstrated higher rates of mental health emergency department visits compared with a predicted prepandemic period, adjusting for seasonal variation. Changes in mental health emergencies were not associated with COVID-19 prevalence or societal restrictions.

The COVID-19 pandemic had a profound impact on youth mental health (MH).16  Nationally, comparative rates of MH-related emergency department (ED) visits increased during the pandemic while overall pediatric ED visits decreased through 2022.714  The Centers for Disease Control and Prevention’s National Syndromic Surveillance Program data demonstrated the proportion of ED visits for mental health emergencies (MHE) rose 36% during the first 42 weeks of the pandemic compared with 2019.15  National pediatric organizations issued a state of emergency in October 2021 and the US Surgeon General issued a public health advisory in December 2021 regarding the pediatric mental health crisis.16,17 

Although evidence has reported an overall rise in MH-ED visits nationally, early studies were based on single-center experiences,7,13,18  or did not control for seasonal variation.1,19  Furthermore, the direct relationship between the COVID-19 pandemic and MHE is unclear. Studies implicate the disruption of school and social interactions as primary drivers of pediatric MHE, although some countries with more stringent societal restrictions reported lower rates of MHE in youth.2023  More than 3 years after the pandemic began, children have returned to school and most societal restrictions have been lifted, yet the youth MH crisis continues.24  We investigated the impact of the COVID-19 pandemic on pediatric MH over time in a large multisite cohort in New York City (NYC), a major epicenter of the pandemic.25 

We sought to (1) describe seasonally adjusted changes in the proportion of MH-ED visits across the first 5 waves of the COVID-19 pandemic by patient demographic, socioeconomic, and clinical characteristics; and (2) explore the association between pediatric MHE and pandemic intensity as measured by the prevalence of COVID-19 and pandemic-related societal restrictions.

Study Design and Data Source

We conducted a cross-sectional time-series analysis using the INSIGHT Clinical Research Network, a large database consisting of electronic health records from 5 large academic medical centers in the NYC metropolitan area.26,27  We included all visits for patients ages 5 to 17 years from January 1, 2016, to June 12, 2022, and analyzed ED visit data during each of the first 5 COVID-19 waves. This study was approved by the Weill Cornell Medicine Institutional Review Board, with informed consent waived.

Outcome Variable

Our primary outcome was the number of pediatric MH-ED visits per 10 000 total pediatric ED visits. We defined an MH-ED visit as when the primary discharge International Classification of Diseases, Ninth Revision or Tenth Revision, code was included in the Child and Adolescent Mental Health Disorders Classification System, and further classified these by diagnostic subcategories.28  We included primary diagnoses of highest prevalence in the database and from prior studies:, anxiety disorders,1  depressive disorders,1  suicidality or self-injury,13,29  eating disorders,30  schizophrenia spectrum and other psychotic disorders,31  and substance-related and addictive disorders.13,29 We performed a manual chart review on a subset of 70 visits in 42 patients to corroborate patient diagnostic coding.

Explanatory Variables

We defined 5 COVID-19 waves based on data from the NYC Department of Health, corresponding to factors such as COVID-19 variants and/or distinct periods of increased COVID-19 prevalence32  as follows: wave 1 (March 1, 2020–July 31, 2020), wave 2 (August 1, 2020–June 18, 2021), wave 3 (June 19, 2021–November 30, 2021), wave 4 (December 1, 2021–March 5, 2022), and wave 5 (March 6, 2022–June 12, 2022). We collected sociodemographic data including sex, race and ethnicity, age, and the ZIP code–level Child Opportunity Index (COI) 2.0. We reported race and ethnicity based on US Census categories as American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, White, multiple races, Hispanic or Latino, and Other. We collapsed the race and ethnicity categories with stratified cell counts of less than 10 or insufficient data for regression models into the Other group. We included race and ethnicity, within a health equity structure, to understand the impact of race and ethnicity as social constructs and markers of racism and bias on our outcome because prior literature demonstrates inequities in mental health outcomes based on race.33  Consistent with prior literature, we categorized subjects based on age: children (5–11 years) and adolescents (12–17 years), excluding those younger than age 5 years based on rarity of MHE in this age group.15,34  The COI is a composite index that measures neighborhood resources and conditions that matter for children’s healthy development, with categories for child opportunity of “very low,” “low,” “moderate,” “high,” and “very high” determined by ZIP code of residence.35 

We analyzed 2 additional variables to measure COVID-19 pandemic intensity over time: (1) NYC COVID-19 prevalence (COVID-19 cases per 10 000 NYC residents), abstracted from NYC Department of Health data32  and (2) state-level societal restrictions, measured using the New York State Stringency Index. The Stringency Index, developed by the Oxford University Coronavirus Government Response Tracker Project, is a composite of 9 metrics, including school and workplace closures, public event cancellation, public gathering restrictions, public transportation closures, stay-at-home requirements, and international travel controls.36,37  The Stringency Index was not available for NYC specifically at time of publication.

Primary Analysis

Our primary analysis compared predicted and actual NYC MH-ED visit rates during the first 5 COVID-19 waves. First, we reported baseline sociodemographics of pediatric patients with MH-ED visits during each COVID-19 wave. Using seasonally adjusted time series and interrupted time series models, we estimated changes in MH-ED visit rates from a predicted baseline level. We fit these models in our overall pediatric sample and subpopulations stratified by diagnosis and sociodemographic characteristics.

Using the pre-COVID period (January 1, 2016–February 29, 2020) as a baseline, we forecasted MH-ED visit rates that would have been expected from March 1, 2020, to June 12, 2022, had the COVID-19 pandemic not occurred. Using observed data during this period, we estimated the difference between observed and forecasted (ie, predicted) MH-ED visit rates for each of the 5 COVID-19 waves, and calculated a COVID-19 wave-specific coefficient based on the average difference between the observed and predicted MH-ED visits per 10 000 ED visits.38,39  We describe visit rate increases above predicted baseline as “excess” visit rates. We described estimate uncertainty using 95% confidence intervals (CIs).

We used multivariable linear regression models with autoregressive moving average error processes (ARIMA) to include covariates in our time series models while accounting for complex seasonal patterns and the potential for autocorrelation across sequential observations.4042  We aggregated daily visit data to weekly counts and truncated data within each year at 52 weeks, appending data from week 53 to week 52. We determined nonseasonal and seasonal components of ARIMA models using a variation of the Hyndman-Khandakar algorithm, a semiautomated ARIMA model selection process.43  Although the length of COVID-19 waves differed, our time series models accounted for differences in the length of COVID-19 waves using an estimation of wave-specific effects.

To examine changes in MH-ED visit rates by diagnoses and sociodemographic characteristics, we repeated our primary time-series analysis stratified by subpopulations based on these characteristics. We reported subpopulation-specific values for mean percent change in MH-ED visit rates from the subpopulation’s predicted baseline, estimated for each wave. This relative measure was derived by dividing each subpopulation’s ARIMA regression coefficient estimate by the mean of its predicted baseline MH-ED visit rate (Supplemental Formula 1 ). This relative percent change measure is useful in that it allows comparisons across distinct clinical and sociodemographic categories with varying baseline MH-ED levels. We derived 95% CIs for percent change estimates using regression coefficient error estimates (Supplemental Tables 1 and 2).

Secondary Analysis

Our secondary analysis examined the association between MH-ED visit rates and 2 variables that describe COVID-19 pandemic intensity more specifically: (1) NYC COVID-19 prevalence and (2) the New York State Stringency Index. Whereas our primary analyses observed excess MH-ED visit rates broadly during the COVID-19 pandemic, our secondary analyses observed 2 specific aspects of the COVID-19 pandemic. We constructed 2 additional time-series models, including COVID-19 prevalence and the Stringency Index as primary exposures.44  Because these exposures were limited to the COVID-19 period, we were unable to use seasonal ARIMA components based on baseline, prepandemic data. Therefore, we adjusted each model for the baseline MH-ED rate predicted from our overall primary model. We adjusted models for each COVID-19 wave using indicator variables to account for distinct characteristics of each period that may have affected both exposure and outcome.44  COVID-19 cases per 10 000 were log2-transformed to lessen the effect of outlier prevalence values, especially those during wave 4.

All analyses were performed using R version 4.2.1. ARIMA models were implemented using the forecast and zoo packages.45,46  This study followed the Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines.47 

Using the INSIGHT Clinical Research Network database, our total study sample consisted of 349 495 patients comprising 686 500 ED visits from January 1, 2016, to June 12, 2022. For all pediatric ED visits, the census decreased during wave 1, increased during waves 2 and 3, and returned to the pre-COVID baseline during waves 4 and 5 (Supplemental Figure 5). We classified 27 168 (4.0%) of the total ED visits as MH-ED visits based on having an MHE-associated discharge diagnosis. The sociodemographic composition of patients with a MH-ED visit included a median age of 14 years (interquartile range, 11–16), with 46% male, 37% Hispanic, 16% Black, and 41% very low COI quintile. Our analyses consisted of 17 943 (66%) MH-ED visits during the prepandemic period and 9225 (34%) during the pandemic (wave 1: 825 [3.0%]; wave 2: 3132 [11.5%]; wave 3: 2099 [7.7%]; wave 4: 1435 [5.3%]; and wave 5: 1734 [6.4%] (Table 1). A manual review of charts for a subset of 42 patients found 98% demonstrated narrative evidence supporting the MHE diagnosis code.

TABLE 1

Characteristics of Mental Health–Related Pediatric Emergency Department Visits in New York City, January 2016–June 2022

Patient Visit CharacteristicsOverall,
N = 27 168
Pre-COVID,
N = 17 943
COVID Wave 1,
N = 825
COVID Wave 2,
N = 3132
COVID Wave 3,
N = 2099
COVID Wave 4,
N = 1435
COVID Wave 5,
N = 1734
Sex 
 Female 14 687 (54%) 9279 (52%) 459 (56%) 1919 (61%) 1220 (58%) 825 (57%) 985 (57%) 
 Male 12 465 (46%) 8653 (48%) 366 (44%) 1209 (39%) 878 (42%) 610 (43%) 749 (43%) 
 Unknown 16 (<0.1%) 11 (<0.1%) 0 (0%) 4 (0.1%) 1 (<0.1%) 0 (0%) 0 (0%) 
Race and ethnicity 
 Hispanic 10 019 (37%) 6668 (37%) 302 (37%) 1151 (37%) 724 (34%) 530 (37%) 644 (37%) 
 Black or African American 4227 (16%) 2943 (16%) 118 (14%) 449 (14%) 286 (14%) 191 (13%) 240 (14%) 
 White 4071 (15%) 2410 (13%) 145 (18%) 574 (18%) 390 (19%) 256 (18%) 296 (17%) 
 Asian 559 (2.1%) 348 (1.9%) 18 (2.2%) 80 (2.6%) 48 (2.3%) 34 (2.4%) 31 (1.8%) 
 American Indian or Alaska Native 25 (<0.1%) 12 (<0.1%) 1 (0.1%) 4 (0.1%) 0 (0%) 2 (0.1%) 6 (0.3%) 
 Native Hawaiian or Other Pacific Islander 17 (<0.1%) 13 (<0.1%) 0 (0%) 1 (<0.1%) 2 (<0.1%) 0 (0%) 1 (<0.1%) 
 Multiple race 52 (0.2%) 27 (0.2%) 4 (0.5%) 7 (0.2%) 3 (0.1%) 9 (0.6%) 2 (0.1%) 
 Other 2163 (8.0%) 1460 (8.1%) 49 (5.9%) 215 (6.9%) 183 (8.7%) 109 (7.6%) 147 (8.5%) 
 Unknown 6035 (22%) 4062 (23%) 188 (23%) 651 (21%) 463 (22%) 304 (21%) 367 (21%) 
Age at ED visit 
 5–11 7328 (27%) 5359 (30%) 190 (23%) 650 (21%) 426 (20%) 325 (23%) 378 (22%) 
 12–17 19 840 (73%) 12 584 (70%) 635 (77%) 2482 (79%) 1673 (80%) 1110 (77%) 1356 (78%) 
Child Opportunity Index 
 Very high 2894 (11%) 1683 (9.4%) 91 (11%) 423 (14%) 286 (14%) 186 (13%) 225 (13%) 
 High 1736 (6.4%) 828 (4.6%) 56 (6.8%) 312 (10.0%) 241 (11%) 134 (9.3%) 165 (9.5%) 
 Moderate 3069 (11%) 1887 (11%) 111 (13%) 370 (12%) 273 (13%) 204 (14%) 224 (13%) 
 Low 8062 (30%) 5379 (30%) 257 (31%) 891 (28%) 586 (28%) 430 (30%) 519 (30%) 
 Very low 11 045 (41%) 7899 (44%) 300 (36%) 1105 (35%) 696 (33%) 471 (33%) 574 (33%) 
 Unknown 362 (1.3%) 267 (1.5%) 10 (1.2%) 31 (1.0%) 17 (0.8%) 10 (0.7%) 27 (1.6%) 
Primary mental health diagnosis category associated with visita 
 Anxiety disorders 3015 (11%) 1906 (11%) 122 (15%) 390 (12%) 251 (12%) 145 (10%) 201 (12%) 
 Depressive disorders 5452 (20%) 3848 (21%) 151 (18%) 626 (20%) 351 (17%) 245 (17%) 231 (13%) 
 Suicide, self-injury, or suicidal ideation 5629 (21%) 3422 (19%) 149 (18%) 799 (26%) 488 (23%) 342 (24%) 429 (25%) 
 Feeding and eating disorders 232 (0.9%) 115 (0.6%) 17 (2.1%) 40 (1.3%) 20 (1.0%) 19 (1.3%) 21 (1.2%) 
 Schizophrenia spectrum and other psychotic disorders 469 (1.7%) 307 (1.7%) 16 (1.9%) 53 (1.7%) 35 (1.7%) 31 (2.2%) 27 (1.6%) 
 Substance abuse and addictive disorders 1969 (7.2%) 1256 (7.0%) 72 (8.7%) 228 (7.3%) 149 (7.1%) 97 (6.8%) 167 (9.6%) 
Patient Visit CharacteristicsOverall,
N = 27 168
Pre-COVID,
N = 17 943
COVID Wave 1,
N = 825
COVID Wave 2,
N = 3132
COVID Wave 3,
N = 2099
COVID Wave 4,
N = 1435
COVID Wave 5,
N = 1734
Sex 
 Female 14 687 (54%) 9279 (52%) 459 (56%) 1919 (61%) 1220 (58%) 825 (57%) 985 (57%) 
 Male 12 465 (46%) 8653 (48%) 366 (44%) 1209 (39%) 878 (42%) 610 (43%) 749 (43%) 
 Unknown 16 (<0.1%) 11 (<0.1%) 0 (0%) 4 (0.1%) 1 (<0.1%) 0 (0%) 0 (0%) 
Race and ethnicity 
 Hispanic 10 019 (37%) 6668 (37%) 302 (37%) 1151 (37%) 724 (34%) 530 (37%) 644 (37%) 
 Black or African American 4227 (16%) 2943 (16%) 118 (14%) 449 (14%) 286 (14%) 191 (13%) 240 (14%) 
 White 4071 (15%) 2410 (13%) 145 (18%) 574 (18%) 390 (19%) 256 (18%) 296 (17%) 
 Asian 559 (2.1%) 348 (1.9%) 18 (2.2%) 80 (2.6%) 48 (2.3%) 34 (2.4%) 31 (1.8%) 
 American Indian or Alaska Native 25 (<0.1%) 12 (<0.1%) 1 (0.1%) 4 (0.1%) 0 (0%) 2 (0.1%) 6 (0.3%) 
 Native Hawaiian or Other Pacific Islander 17 (<0.1%) 13 (<0.1%) 0 (0%) 1 (<0.1%) 2 (<0.1%) 0 (0%) 1 (<0.1%) 
 Multiple race 52 (0.2%) 27 (0.2%) 4 (0.5%) 7 (0.2%) 3 (0.1%) 9 (0.6%) 2 (0.1%) 
 Other 2163 (8.0%) 1460 (8.1%) 49 (5.9%) 215 (6.9%) 183 (8.7%) 109 (7.6%) 147 (8.5%) 
 Unknown 6035 (22%) 4062 (23%) 188 (23%) 651 (21%) 463 (22%) 304 (21%) 367 (21%) 
Age at ED visit 
 5–11 7328 (27%) 5359 (30%) 190 (23%) 650 (21%) 426 (20%) 325 (23%) 378 (22%) 
 12–17 19 840 (73%) 12 584 (70%) 635 (77%) 2482 (79%) 1673 (80%) 1110 (77%) 1356 (78%) 
Child Opportunity Index 
 Very high 2894 (11%) 1683 (9.4%) 91 (11%) 423 (14%) 286 (14%) 186 (13%) 225 (13%) 
 High 1736 (6.4%) 828 (4.6%) 56 (6.8%) 312 (10.0%) 241 (11%) 134 (9.3%) 165 (9.5%) 
 Moderate 3069 (11%) 1887 (11%) 111 (13%) 370 (12%) 273 (13%) 204 (14%) 224 (13%) 
 Low 8062 (30%) 5379 (30%) 257 (31%) 891 (28%) 586 (28%) 430 (30%) 519 (30%) 
 Very low 11 045 (41%) 7899 (44%) 300 (36%) 1105 (35%) 696 (33%) 471 (33%) 574 (33%) 
 Unknown 362 (1.3%) 267 (1.5%) 10 (1.2%) 31 (1.0%) 17 (0.8%) 10 (0.7%) 27 (1.6%) 
Primary mental health diagnosis category associated with visita 
 Anxiety disorders 3015 (11%) 1906 (11%) 122 (15%) 390 (12%) 251 (12%) 145 (10%) 201 (12%) 
 Depressive disorders 5452 (20%) 3848 (21%) 151 (18%) 626 (20%) 351 (17%) 245 (17%) 231 (13%) 
 Suicide, self-injury, or suicidal ideation 5629 (21%) 3422 (19%) 149 (18%) 799 (26%) 488 (23%) 342 (24%) 429 (25%) 
 Feeding and eating disorders 232 (0.9%) 115 (0.6%) 17 (2.1%) 40 (1.3%) 20 (1.0%) 19 (1.3%) 21 (1.2%) 
 Schizophrenia spectrum and other psychotic disorders 469 (1.7%) 307 (1.7%) 16 (1.9%) 53 (1.7%) 35 (1.7%) 31 (2.2%) 27 (1.6%) 
 Substance abuse and addictive disorders 1969 (7.2%) 1256 (7.0%) 72 (8.7%) 228 (7.3%) 149 (7.1%) 97 (6.8%) 167 (9.6%) 

Data from INSIGHT Clinical Research Network visits among patients younger than age 18 years with mental health–related primary discharge diagnosis. Statistics presented: n (column %). Time periods: overall, January 1, 2016–June 12, 2022; pre-COVID, January 1, 2016–February 29, 2020; wave 1, March 1, 2020–July 31, 2020; wave 2, August 1, 2020–June 30, 2021; wave 3, July 1, 2021–November 30, 2021; wave 4, December 1, 2021–March 5, 2022; wave 5, March 6, 2022–June 12, 2022, emergency department.

a

Visit mental health diagnosis category row values do not equal group totals or add to 100% because the 6 categories in this table represent a subset of the 30 categories defined by the Child and Adolescent Mental Health Disorders Classification System (CAMHD-CS).

The proportion of MH-ED visits exhibited a consistent seasonal pattern, with peaks in April and November and nadirs in January and July. These MH-ED visits, measured per 10 000 ED visits, increased during each wave of the COVID-19 pandemic compared with predictions based on prepandemic seasonal trends. This was especially apparent during wave 2. After adjusting for baseline seasonal patterns, we estimated an average 64.7-visit excess for MH-ED visits per 10 000 ED visits (95% CI, 8.0–121.5) compared with what would be predicted during wave 1; 134.1-visit excess per 10 000 (95% CI, 90.2–178.1) during wave 2; 71.3-visit excess per 10 000 (95% CI, 14.4–128.3) during wave 3; 119.0-visit excess per 10 000 (95% CI, 47.6–190.5) during wave 4; and 69.5-visit excess per 10 000 (95% CI, –4.6 to 143.6) during wave 5 (Fig 1; Supplemental Table 2).

FIGURE 1

Observed and predicted NYC pediatric mental health emergency rates during the COVID-19 pandemic. Observed (black line) and forecasted (red line) pediatric MH-ED visits per 10 000 ED visits. Forecasted proportions were determined using seasonal baseline trends from pre-COVID-19 data (January 1, 2016–February 29, 2020). Data were modeled and presented on a weekly scale, and all lines were smoothed using a 4-week rolling mean. ED, emergency department; MH, mental health; NYC, New York City.

FIGURE 1

Observed and predicted NYC pediatric mental health emergency rates during the COVID-19 pandemic. Observed (black line) and forecasted (red line) pediatric MH-ED visits per 10 000 ED visits. Forecasted proportions were determined using seasonal baseline trends from pre-COVID-19 data (January 1, 2016–February 29, 2020). Data were modeled and presented on a weekly scale, and all lines were smoothed using a 4-week rolling mean. ED, emergency department; MH, mental health; NYC, New York City.

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Excess MH-ED visit rates varied by MHE diagnosis. Excess anxiety disorder–related MH-ED visit rates were highest during wave 1 (75.3%; 95% CI, 47.9–102.8) and wave 2 (65.7%; 95% CI, 46.8–84.5) and also increased above predicted in wave 4 (39.5%; 95% CI, 2.6–76.4) and wave 5 (40.6%; 95% CI, 5.9–75.4). There were increases in MH-ED visit rates during wave 2 for both depressive disorder–related visits (28.2%; 95% CI, 9.9–46.5) and suicidality-related visits (53.4%; 95% CI, 32.5–74.2). Excess eating disorder–related MH-ED visit rates were significantly increased above predicted for all 5 waves, with the largest increase during wave 1 (545.5%; 95% CI, 489.8–601.4). Schizophrenia spectrum and other psychotic disorder–related MH-ED visit rates statistically significantly increased above predicted during wave 1 (118.0%; 95% CI, 32.9–203.1). Substance and addictive disorder–related MH-ED visit rates increased during wave 2 (61.9%; 95% CI, 38.8–85.0), wave 4 (86.5%; 95% CI, 42.2–130.8), and wave 5 (131.1%; 95% CI, 88.1–174.1). (Fig 2; Supplemental Table 2 and Supplemental Table 3).

FIGURE 2

Observed and predicted NYC pediatric mental health emergency rates, by primary discharge diagnoses. (A) Observed (black lines) and forecasted (red lines) pediatric MH-ED visits per 10 000 ED visits. Forecasted proportions were determined using seasonal baseline trends from pre-COVID-19 data (January 1, 2016–February 29, 2020). Data were modeled and presented on a weekly scale, and all lines were smoothed using a 4-week rolling mean. The presented baseline data were truncated before 2018 for visualization purposes but included in models. (B) Change from predicted baseline MH-ED visits per 10 000 ED visits calculated by dividing each substratum wave–specific ARIMA regression coefficient by the mean substratum wave–specific predicted baseline MH-ED proportion. 95% confidence intervals were derived from estimates of regression coefficient errors. ARIMA, autoregressive moving average error processes; ED, emergency department; MH, mental health; NYC, New York City; psych., psychotic disorders; SUD, substance use disorders.

FIGURE 2

Observed and predicted NYC pediatric mental health emergency rates, by primary discharge diagnoses. (A) Observed (black lines) and forecasted (red lines) pediatric MH-ED visits per 10 000 ED visits. Forecasted proportions were determined using seasonal baseline trends from pre-COVID-19 data (January 1, 2016–February 29, 2020). Data were modeled and presented on a weekly scale, and all lines were smoothed using a 4-week rolling mean. The presented baseline data were truncated before 2018 for visualization purposes but included in models. (B) Change from predicted baseline MH-ED visits per 10 000 ED visits calculated by dividing each substratum wave–specific ARIMA regression coefficient by the mean substratum wave–specific predicted baseline MH-ED proportion. 95% confidence intervals were derived from estimates of regression coefficient errors. ARIMA, autoregressive moving average error processes; ED, emergency department; MH, mental health; NYC, New York City; psych., psychotic disorders; SUD, substance use disorders.

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MH-ED visits increased above predicted across all 5 waves for female patients, with the highest increase during wave 2 (55.9%; 95% CI, 41.2–70.7), and increased for male patients in waves 1, 2, and 4, with the highest increase during wave 4 (26.7%; 95% CI, 6.9–46.6). In adolescents, MH-ED visits were above predicted across all 5 waves, with the largest relative increase during wave 2 (28.6%; 95% CI, 20.2–37), whereas children had smaller increases overall, reported only during wave 2 (12.8%; 95% CI, 2.9–22.7) and wave 4 (25.5%; 95% CI, 5.7–45.3). Asian patients experienced the highest relative increases in MH-ED visit rates from predicted, with the greatest increases occurring during wave 2 (162.8%; 95% CI, 122.2–203.4), wave 3 (155.4%; 95% CI, 83.8–227), and wave 4 (154.6%; 95% CI, 86.8–222.3). White patients also experienced significant increases during waves 2, 3, and 4, but less so compared with Asian patients. The greatest relative increases for Hispanic patients occurred during wave 2 (41.9%; 95% CI, 21.7–62) and for patients of “Other” race during wave 4 (36.7%; 95% CI, 7–66.5). Black patients experienced a relative increase during wave 2 (38.1%; 95% CI, 20.7–55.6). Children in the high COI quintile experienced increased MH-ED visit rates in all 5 waves, with wave 2 being highest (92.7%; 95% CI, 66.5–118.9) (Fig 3, Supplemental Table 2 and Supplemental Table 3).

FIGURE 3

Change from predicted NYC pediatric mental health emergency rate, by COVID-19 wave and patient sociodemographics. Change from predicted baseline MH-ED visits per 10 000 ED visits calculated by dividing each substratum wave–specific ARIMA regression coefficient by the mean substratum-wave-specific predicted baseline MH-ED proportion. 95% confidence intervals were derived from estimates of regression coefficient errors. COI, Child Opportunity Index; ED, emergency department; MH, mental health; NYC, New York City.

FIGURE 3

Change from predicted NYC pediatric mental health emergency rate, by COVID-19 wave and patient sociodemographics. Change from predicted baseline MH-ED visits per 10 000 ED visits calculated by dividing each substratum wave–specific ARIMA regression coefficient by the mean substratum-wave-specific predicted baseline MH-ED proportion. 95% confidence intervals were derived from estimates of regression coefficient errors. COI, Child Opportunity Index; ED, emergency department; MH, mental health; NYC, New York City.

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MH-ED visit rates were not significantly associated with 2 specific aspects of the COVID-19 pandemic: (1) NYC COVID-19 prevalence and (2) New York State Stringency Index. Adjusting for baseline seasonality and COVID-19 wave, MH-ED visits were estimated to change by an average of –9.15 visits per 10 000 ED visits (95% CI, –28.6 to 10.3) based on COVID-19 cases, and by –0.54 visits per 10 000 ED visits (95% CI, –3.1 to 2.0) for the New York State Stringency Index (per 1-unit increase on the log2-scale in COVID-19 case prevalence [ie, a doubling of prevalence] and 1-unit increase in the Stringency Index) (Fig 4).

FIGURE 4

NYC pediatric mental health emergency rates, NYC COVID-19 prevalence, and New York State Stringency Index. Observed pediatric MH-ED visits per 10 000 ED visits (black line) during the first 5 waves, smoothed using a 4-week rolling mean. Observed COVID-19 cases per 10 000 NYC residents (orange line) during the first 5 waves, smoothed using a 1-week rolling mean. Stringency Index (green line) of New York State government response. Data are presented on a daily scale. ED, emergency department; MH, mental health; NYC, New York City.

FIGURE 4

NYC pediatric mental health emergency rates, NYC COVID-19 prevalence, and New York State Stringency Index. Observed pediatric MH-ED visits per 10 000 ED visits (black line) during the first 5 waves, smoothed using a 4-week rolling mean. Observed COVID-19 cases per 10 000 NYC residents (orange line) during the first 5 waves, smoothed using a 1-week rolling mean. Stringency Index (green line) of New York State government response. Data are presented on a daily scale. ED, emergency department; MH, mental health; NYC, New York City.

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Using the INSIGHT Clinical Research Network database in NYC, a COVID-19 pandemic epicenter, we found an increase in the proportion of pediatric MH-ED visits during each of the first 5 COVID-19 waves, relative to what was predicted based on adjusted prepandemic seasonal trends. We found the greatest increase in MH-ED visit rates compared with predicted during wave 2 followed by wave 4. All MHE diagnoses of interest exhibited excess MH-ED visit rates during the pandemic; however, the magnitude of excess differed by diagnosis and varied over the five waves. Female, adolescent, and Asian race patients had the highest increases in MH-ED visit rates above baseline predictions across all waves. MH-ED visit rates were not significantly associated with COVID-19 case prevalence in NYC or with the severity of New York State COVID-19–related societal restrictions, measured by the Stringency Index.

It is well described that the proportion of MH-ED visits increased with the onset of the COVID-19 pandemic, but this study contributes to existing data by examining the impact of COVID-19 over 2 years beyond the initial stages of the pandemic.7,12,4850  Additionally, we sought to further understand these patterns by applying a robust methodology adjusting for seasonal trends and using a large multisite database. We built on prior studies that used similar methodology to adjust for seasonal variations but focused on MH hospitalizations as opposed to emergencies, were based outside of the United States demonstrating a different pandemic experience, or did not also explore associations between MH-ED visit rates and specific indicators of pandemic intensity.7,10,12,15,34,48,49,51,52  We report that increases in MH-ED visit rates were greatest in wave 2, both overall and across most MHE diagnoses. Wave 2 was approximately 2 to 3 times longer than other waves, which may have increased our statistical power to detect excesses in MH-ED visit rates during this period. However, we do not believe this was the only reason for positive findings during wave 2, for at least 2 reasons: (1) MH-ED visit rates were distinctly higher, on average, during this period (Fig 1), which is not a function of the length of the wave; and (2) significant findings were persistent throughout our study period, even during comparatively shorter waves. This sustained increase in MH-ED visit rates was measured through June 2022, despite widespread vaccination for both children and adolescents by that time, as well as return to in-person school across communities.5355 

Examining excess MH-ED visit rates during COVID-19 by wave and MHE diagnosis demonstrated that patients with distinct MH diagnoses were affected differently over time.34  Patients with eating disorders and anxiety disorders experienced increased MH-ED visit rates across all waves (excluding wave 3 for anxiety disorders), whereas visit rates for patients with depressive disorders were initially high and then returned to prepandemic levels following wave 2.11,12,56,57  Patients with substance use disorders experienced increased MH-ED visit rates during waves 2, 4, and 5. Although previous studies have broadly demonstrated decreases in youth substance use during the pandemic,5860  our study may add nuance to these findings: in our sample, despite presumed substance use decreases, substance use disorder-related emergency visit rates among youth were still disproportionately higher during some periods of the pandemic. We also found an increase in MH-ED visit rates for youth with schizophrenia spectrum and other psychotic disorders during wave 1, an observation not previously reported. Youth with these conditions likely represent a more chronically ill group with a higher severity of disease and are likely more vulnerable to disruptions in outpatient mental health services that occurred at the onset of the pandemic, contributing to the initial increases in ED utilization in this population.61  The sustained high rates of ED utilization for MH emergencies through wave 5 of the pandemic may reflect continued insufficient resources and sociocultural barriers to mental health care services for youth.58,62 

Examining the relationship between excess MH-ED visit rates and sociodemographics can help identify youth at higher risk for MH emergencies. We found MH-ED visit rates for Asian youth had the largest relative increase during COVID-19 compared with other racial and ethnic groups. Although suicide rates were increasing in Asian youth before the pandemic, related increases in anti-Asian racism may be a factor contributing to our findings, which could guide targeted interventions.6365 

Despite the pandemic’s disproportionate impact on youth living in poverty, we saw the largest relative increase in MH-ED visits among patients from high COI ZIP codes.66  This finding mirrors the overall pandemic effect on pediatric acute care utilization.67  Fritz et al report that patients in higher COI quintiles, a population that experienced a relatively greater loss of access to outpatient resources, were more likely to use the ED for acute health care. In contrast, structural barriers and disparities related to health care access may have contributed to decreased MH-ED visits in lower COI quintiles during the first 5 waves of the pandemic.68,69 

Prior literature suggests that COVID-19 pandemic intensity contributed to the rise in youth MHE.13,21,22,70,71  In our primary analysis, MH-ED visit rates were increased above forecasts throughout the first 5 COVID-19 waves. However, in our secondary analysis, we did not detect significant associations between COVID-19 case prevalence and MH-ED visit rates. This could be due to several reasons. First, the causes of MH-ED visit rate increases during these waves were likely complex and multifactorial. Representing 2 aspects of these factors numerically (using COVID-19 prevalence and an index of societal restrictions) may have ignored interactions between these and other clinical and societal stressors. Second, as the COVID-19 pandemic progressed and responses to each wave became more multifactorial (eg, vaccines became more widely available, school closures became rarer, isolation policies loosened), the relationships between COVID-19 prevalence, societal restrictions, and youth mental health outcomes likely grew more complex over time. Future studies that observe specific exposures in limited time periods may reveal more conclusive (and potentially differing) relationships with pediatric MH-ED rates.

The New York State Stringency Index was also not significantly associated with the increase in MHE in our cohort. We postulate that the state-level Stringency Index may not reflect city-specific policies and micropolicies that impacted youth in NYC during the pandemic.72  The Stringency Index also does not account for psychosocial losses, such as missed family gatherings or important school events important to youth.20,73  Finally, these restrictive policies may have effectively influenced health care–seeking behavior, with a resultant decrease in MH-ED visits. More research is needed to understand causal pathways between the COVID-19 pandemic and the youth mental health crisis.

Our study had limitations inherent to secondary datasets, such as misclassification or missingness in primary mental health diagnoses and sociodemographic information including race and ethnicity. Our dataset also did not include disposition of patients following their MH-ED visit. However, our study benefited from a large and diverse sample and the corroboration of diagnosis data through manual chart review. Additionally, calculations of excess MH-ED visit rates comparing baseline to predicted were derived based on pre-COVID trends. Thus, some of the ARIMA models used to estimate baseline levels of MH-ED visit rates contained residual autocorrelation, which may have biased or affected the statistical precision of results. Last, although our study includes data from 5 large urban medical centers, the impact of COVID-19 on NYC youth may not be representative across other geographic regions,8  nor the population of youth who use the NYC municipal hospital system. Furthermore, without NYC population-level data, we cannot determine if changes in MH-ED visit rates over time represent changes in population-level prevalence or solely in the 5 NYC hospitals in our dataset.

This seasonally adjusted time-series analysis of the first 5 waves of the COVID-19 pandemic in NYC demonstrated higher rates of MH-ED visits compared with the prepandemic period. Most notably, the relative increase in MH-ED visits persisted across each of the first 5 COVID-19 waves. MH-ED visit rates were not significantly associated with city-level COVID-19 case prevalence or state-level societal restrictions. Our findings demonstrate the lasting impact of the COVID-19 pandemic on youth MH and their continued vulnerability despite our resumption of normal activity.24  Sociodemographic differences highlight opportunities to focus MH resources on high-risk groups. However, further research is needed to identify root causes and potential targets for interventions that will mitigate the persistent and continually growing youth mental health crisis.

Writing-review and editing: Crystal Herron, PhD, ELS, Redwood Ink.

Drs Levine, Oh, Nash, Grinspan, Abramson, Platt, and Green conceptualized and designed the study, drafted the initial manuscript, and critically reviewed and revised the manuscript; Mr Simmons collected data, carried out the analyses, and critically reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: All phases of this study were supported by an award from RTW Foundation.

CONFLICT OF INTEREST DISCLOSURES: There are no conflicts of interest to disclose for any authors. The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

ARIMA

autoregressive moving average error processes

CI

confidence interval

COI

Child Opportunity Index

ED

emergency department

MH

mental health emergency visits

MHE

Mental health emergencies

NYC

New York City

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