The impact of stay-at-home orders on the rate of emergency department child maltreatment diagnoses.

BACKGROUND: There is limited data regarding the rates and severity of child maltreatment in medical settings during the COVID-19 pandemic, and the reports are somewhat contradictory. OBJECTIVE: To examine the rates of emergency department (ED) child maltreatment (CM) diagnosis before and after the California statewide stay-at-home order, as well as potential disparities by age, gender, race/ethnicity, and Medicaid status. METHODS: A retrospective pre-post interrupted time series was conducted using data from the electronic health records of children (<18 years) with at least one emergency department visit between January 1, 2019 and September 30, 2021. Enactment of the stay-at-home order in California, March 2020 was used to determine a change in trend of rates of diagnosis of CM in the ED. RESULTS: Overall the study included 407,228 pediatric ED visits. There was a significant change in the percentage of CM visits immediately after the stay-at-home order, followed by small month to month decreases returning to near pre-stay-at-home order levels. This significant increase was driven by higher risk for children <4 years old. The increased rate of CM in the first month after the stay-at-home order was also elevated for female, Black, and Hispanic children. CONCLUSIONS: Our results indicated the rates of CM diagnoses in the ED doubled after the March 2020 stay-at-home order in California. Additionally, our findings suggest that some children may be at higher risk than others, which supports the importance of social safety nets for children in times of national emergency.

Healthcare Utilization Among Patients Diagnosed with COVID-19 in a Large Integrated Health System.

BACKGROUND: The demands for healthcare resources following a COVID-19 diagnosis are substantial, but not currently quantified. OBJECTIVE: To describe trends in healthcare utilization within 180 days for patients diagnosed with COVID-19 and identify patient factors associated with increased healthcare use. DESIGN: Observational cohort study. PATIENTS: A total of 64,011 patients with a test-confirmed COVID-19 diagnosis from March to September 2020 in a large integrated healthcare system in Southern California. MAIN MEASURES: Overall healthcare utilization during the 180 days following COVID-19 diagnosis, as well as encounter types and reasons for visits during the first 30 days. Poisson regression was used to identify patient factors associated with higher utilization. Analyses were performed separately for patients who were and were not hospitalized for COVID-19. KEY RESULTS: Healthcare utilization was about twice as high for hospitalized patients compared to non-hospitalized patients in all time periods. The average number of visits was highest in the first 30 days (hospitalized: 12.3 visits/30 person-days; non-hospitalized: 6.6) and gradually decreased over time. In the first 30 days, the majority of healthcare visits were telehealth encounters (hospitalized: 9.0 visits; non-hospitalized: 5.6 visits), and the most prevalent reasons for visits were COVID-related diagnoses, COVID-related symptoms, and respiratory-related conditions. For hospitalized patients, older age (≥65: RR 1.27, 95% CI 1.15-1.41), female gender (RR 1.07, 95% CI 1.05-1.09), and higher BMI (≥40: RR 1.07, 95% CI 1.03-1.10) were associated with higher total utilization. For non-hospitalized patients, older age, female gender, higher BMI, non-white race/ethnicity, former smoking, and greater number of pre-existing comorbidities were all associated with increased utilization. CONCLUSIONS: Patients with COVID-19 seek healthcare frequently within 30 days of diagnosis, placing high demands on health systems. Identifying ways to support patients diagnosed with COVID-19 while adequately providing the usual recommended care to our communities will be important as we recover from the pandemic.

Identifying patients with symptoms suspicious for COVID-19 at elevated risk of adverse events: The COVAS score.

OBJECTIVE: Develop and validate a risk score using variables available during an Emergency Department (ED) encounter to predict adverse events among patients with suspected COVID-19. METHODS: A retrospective cohort study of adult visits for suspected COVID-19 between March 1 - April 30, 2020 at 15 EDs in Southern California. The primary outcomes were death or respiratory decompensation within 7-days. We used least absolute shrinkage and selection operator (LASSO) models and logistic regression to derive a risk score. We report metrics for derivation and validation cohorts, and subgroups with pneumonia or COVID-19 diagnoses. RESULTS: 26,600 ED encounters were included and 1079 experienced an adverse event. Five categories (comorbidities, obesity/BMI ≥ 40, vital signs, age and sex) were included in the final score. The area under the curve (AUC) in the derivation cohort was 0.891 (95% CI, 0.880-0.901); similar performance was observed in the validation cohort (AUC = 0.895, 95% CI, 0.874-0.916). Sensitivity ranging from 100% (Score 0) to 41.7% (Score of ≥15) and specificity from 13.9% (score 0) to 96.8% (score ≥ 15). In the subgroups with pneumonia (n = 3252) the AUCs were 0.780 (derivation, 95% CI 0.759-0.801) and 0.832 (validation, 95% CI 0.794-0.870), while for COVID-19 diagnoses (n = 2059) the AUCs were 0.867 (95% CI 0.843-0.892) and 0.837 (95% CI 0.774-0.899) respectively. CONCLUSION: Physicians evaluating ED patients with pneumonia, COVID-19, or symptoms suspicious for COVID-19 can apply the COVAS score to assist with decisions to hospitalize or discharge patients during the SARS CoV-2 pandemic.

Obesity and Mortality Among Patients Diagnosed With COVID-19: Results From an Integrated Health Care Organization.

BACKGROUND: Obesity, race/ethnicity, and other correlated characteristics have emerged as high-profile risk factors for adverse coronavirus disease 2019 (COVID-19)-associated outcomes, yet studies have not adequately disentangled their effects. OBJECTIVE: To determine the adjusted effect of body mass index (BMI), associated comorbidities, time, neighborhood-level sociodemographic factors, and other factors on risk for death due to COVID-19. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Southern California, a large integrated health care organization. PATIENTS: Kaiser Permanente Southern California members diagnosed with COVID-19 from 13 February to 2 May 2020. MEASUREMENTS: Multivariable Poisson regression estimated the adjusted effect of BMI and other factors on risk for death at 21 days; models were also stratified by age and sex. RESULTS: Among 6916 patients with COVID-19, there was a J-shaped association between BMI and risk for death, even after adjustment for obesity-related comorbidities. Compared with patients with a BMI of 18.5 to 24 kg/m2, those with BMIs of 40 to 44 kg/m2 and greater than 45 kg/m2 had relative risks of 2.68 (95% CI, 1.43 to 5.04) and 4.18 (CI, 2.12 to 8.26), respectively. This risk was most striking among those aged 60 years or younger and men. Increased risk for death associated with Black or Latino race/ethnicity or other sociodemographic characteristics was not detected. LIMITATION: Deaths occurring outside a health care setting and not captured in membership files may have been missed. CONCLUSION: Obesity plays a profound role in risk for death from COVID-19, particularly in male patients and younger populations. Our capitated system with more equalized health care access may explain the absence of effect of racial/ethnic and socioeconomic disparities on death. Our data highlight the leading role of severe obesity over correlated risk factors, providing a target for early intervention. PRIMARY FUNDING SOURCE: Roche-Genentech.