Individuals with psychiatric disorders are vulnerable to adverse mental health outcomes following physical illness. This longitudinal cohort study defined risk profiles for readmission for suicidal behavior and self-harm after general hospitalization of adults with serious mental illness. Structured electronic health record data were analyzed from 15,644 general non-psychiatric index hospitalizations of individuals with depression, bipolar, and psychotic disorders admitted to an urban health system in the southwestern United States between 2006 and 2017. Using data from one-year prior to and including index hospitalization, supervised machine learning was implemented to predict risk of readmission for suicide attempt and self-harm in the following year. The Classification and Regression Tree algorithm produced a classification prediction with an area under the receiver operating curve (AUC) of 0.86 (95% confidence interval (CI) 0.74-0.97). Incidence of suicide-related behavior was highest after general non-psychiatric hospitalizations of individuals with prior suicide attempt or self-harm (18%; 69 cases/389 hospitalizations) and lowest after hospitalizations associated with very high medical morbidity burden (0 cases/3090 hospitalizations). Predictor combinations, rather than single risk factors, explained the majority of risk, including concomitant alcohol use disorder with moderate medical morbidity, and age ≤55-years-old with low medical morbidity. Findings suggest that applying an efficient and highly interpretable machine learning algorithm to electronic health record data may inform general hospital clinical decision support, resource allocation, and preventative interventions for medically ill adults with serious mental illness.

Background

The short-term risk of suicide after medical hospital discharge is four times higher among men compared with women. As previous work has identified female-specific antecedents of suicide-related behavior after medical hospitalization of women with serious mental illness, we examined predictors among a similar population of men with multimorbidity.

Methods

Classification and regression tree (CART) models were developed and validated using electronic health records (EHRs) from 1,423,161 medical (non-psychiatric) hospitalizations of men ≥ 18-years-old with an existing diagnosis of a depressive disorder, bipolar disorder, or chronic psychosis. Hospitalizations occurred between 2009 and 2017. Risk groups were evaluated using an independent testing set. The primary outcome was readmission within one year associated with ICD-9 or -10 code for self-harm or attempt.

Results

The 1-year readmission rate for intentional self-harm and suicide attempt was 3.9% (55,337/1,423,161 hospitalizations). The classification model discriminated risk with area under the curve (AUC) 0.73 (Confidence Interval [95%CI] 0.68-0.74), accuracy 0.82 (95%CI 0.71-0.83), sensitivity 82.6% (95%CI 81.2-84), and specificity 83.1% (95%CI 81.7-84.5). Strongest predictors were medical comorbidity, prior self-harm, age, and prior hospitalization. Men with greater medical comorbidity burden and prior self-harm were at highest risk (Odds Ratio [OR] 3.10, 95%CI 3.02-3.18), as were men < 62-years-old with few medical comorbidities (OR 1.11 95%CI 1.08-1.13).

Limitations

The study focused on medical hospitalizations for suicide attempt and thus captured only severe attempts resulting in hospitalization.

Conclusions

After medical hospitalization, men with serious mental illness experienced a high risk of self-harm (1:25 hospitalizations). Risk was particularly elevated among younger patients without prior medical conditions and older patients with medical comorbidity and prior self-harm.

Objective

This study aimed to examine changes in child emergency department (ED) discharges and hospitalizations for primary general medical (GM) and primary psychiatric disorders; prevalence of psychiatric disorders among acute care encounters; and change in acute mental health (MH) care encounters by disorder type and, within these categories, by child sociodemographic characteristics before and after statewide COVID-19–related school closure orders.

Methods

This retrospective, cross-sectional cohort study used the Pediatric Health Information System database to assess percent changes in ED discharges and hospitalizations (N=2,658,474 total encounters) among children ages 3–17 years in 44 U.S. children’s hospitals in 2020 compared with 2019, by using matched data for 36- and 12-calendar-week intervals.

Results

Decline in MH ED discharges accounted for about half of the decline in ED discharges and hospitalizations for primary GM disorders (−24.8% vs. −49.1%), and MH hospitalizations declined 3.4 times less (−8.0% vs. −26.8%) in 2020. Suicide attempt or self-injury and depressive disorders accounted for >50% of acute MH care encounters before and after the statewide school closures. The increase in both ED discharges and hospitalizations for suicide attempt or self-injury was 5.1 percentage points (p<0.001). By fall 2020, MH hospitalizations for suicide attempt or self-injury rose by 41.7%, with a 43.8% and 49.2% rise among adolescents and girls, respectively.

Conclusions

Suicide or self-injury and depressive disorders drove acute MH care encounters in 44 U.S. children’s hospitals after COVID-19–related school closures. Research is needed to identify continuing risk indicators (e.g., sociodemographic characteristics, psychiatric disorder types, and social determinants of health) of acute child MH care.

Objective

To measure univariate and covariate-adjusted trends in children's mental health-related emergency department (MH-ED) use across geographically diverse areas of the U.S. during the first wave of the Coronavirus-2019 (COVID-19) pandemic.

Method

This is a retrospective, cross-sectional cohort study using electronic health records from four academic health systems, comparing percent volume change and adjusted risk of child MH-ED visits among children aged 3-17 years, matched on 36-week (3/18/19-11/25/19 vs. 3/16/20-11/22/20) and 12-week seasonal time intervals. Adjusted incidence rate ratios (IRR) were calculated using multivariate Poisson regression.

Results

Visits declined during spring-fall 2020 (n = 3892 vs. n = 5228, -25.5%) and during spring (n = 1051 vs. n = 1839, -42.8%), summer (n = 1430 vs. n = 1469, -2.6%), and fall (n = 1411 vs. n = 1920, -26.5%), compared with 2019. There were greater declines among males (28.2% vs. females -22.9%), children 6-12-year (-28.6% vs. -25.9% for 3-5 years and -22.9% for 13-17 years), and Black children (-34.8% vs. -17.7% to -24.9%). Visits also declined for developmental disorders (-17.0%) and childhood-onset disorders (e.g., attention deficit and hyperactivity disorders; -18.0%). During summer-fall 2020, suicide-related visits rose (summer +29.8%, fall +20.4%), but were not significantly elevated from 2019 when controlling for demographic shifts. In contrast, MH-ED use during spring-fall 2020 was significantly reduced for intellectual disabilities (IRR 0.62 [95% CI 0.47-0.86]), developmental disorders (IRR 0.71 [0.54-0.92]), and childhood-onset disorders (IRR 0.74 [0.56-0.97]).

Conclusions

The early pandemic brought overall declines in child MH-ED use alongside co-occurring demographic and diagnostic shifts. Children vulnerable to missed detection during instructional disruptions experienced disproportionate declines, suggesting need for future longitudinal research in this population.