Understanding Disparities in the Pediatric ICU: A Scoping Review.

BACKGROUND AND OBJECTIVES: Health disparities are pervasive in pediatrics. We aimed to describe disparities among patients who are likely to be cared for in the PICU and delineate how sociodemographic data are collected and categorized. METHODS: Using MEDLINE as a data source, we identified studies which included an objective to assess sociodemographic disparities among PICU patients in the United States. We created a review rubric, which included methods of sociodemographic data collection and analysis, outcome and exposure variables assessed, and study findings. Two authors reviewed every study. We used the National Institute on Minority Health and Health Disparities Research Framework to organize outcome and exposure variables. RESULTS: The 136 studies included used variable methods of sociodemographic data collection and analysis. A total of 30 of 124 studies (24%) assessing racial disparities used self- or parent-identified race. More than half of the studies (52%) dichotomized race as white and "nonwhite" or "other" in some analyses. Socioeconomic status (SES) indicators also varied; only insurance status was used in a majority of studies (72%) evaluating SES. Consistent, although not uniform, disadvantages existed for racial minority populations and patients with indicators of lower SES. The authors of only 1 study evaluated an intervention intended to mitigate health disparities. Requiring a stated objective to evaluate disparities aimed to increase the methodologic rigor of included studies but excluded some available literature. CONCLUSIONS: Variable, flawed methodologies diminish our understanding of disparities in the PICU. Meaningfully understanding and addressing health inequity requires refining how we collect, analyze, and interpret relevant data.

A Tale of 8 Cities: Pediatric Critical Care Redeployment to Adult Care During Wave 1 of COVID-19.

BACKGROUND: Pediatric hospital resources including critical care faculty (intensivists) redeployed to provide care to adults in adult ICUs or repurposed PICUs during wave 1 of the coronavirus disease 2019 (COVID-19) pandemic. OBJECTIVES: To determine the magnitude of pediatric hospital resource redeployment and the experience of pediatric intensivists who redeployed to provide critical care to adults with COVID-19. METHODS: A mixed methods study was conducted at 9 hospitals in 8 United States cities where pediatric resources were redeployed to provide care to critically ill adults with COVID-19. A survey of redeployed pediatric hospital resources and semistructured interviews of 40 redeployed pediatric intensivists were simultaneously conducted. Quantitative data were summarized as median (interquartile range) values. RESULTS: At study hospitals, there was expansion in adult ICU beds from a baseline median of 100 (86-107) to 205 (108-250). The median proportion (%) of redeployed faculty (88; 66-100), nurses (46; 10-100), respiratory therapists (48; 18-100), invasive ventilators (72; 0-100), and PICU beds (71; 0-100) was substantial. Though driven by a desire to help, faculty were challenged by unfamiliar ICU settings and culture, lack of knowledge of COVID-19 and fear of contracting it, limited supplies, exhaustion, and restricted family visitation. They recommended deliberate preparedness with interprofessional collaboration and cross-training, and establishment of a robust supply chain infrastructure for future public health emergencies and will redeploy again if asked. CONCLUSIONS: Pediatric resource redeployment was substantial and pediatric intensivists faced formidable challenges yet would readily redeploy again.

Clinician Accuracy in Identifying and Predicting Organ Dysfunction in Critically Ill Children.

OBJECTIVES: To determine clinician accuracy in the identification and prediction of multiple organ dysfunction syndrome. DESIGN: Prospective cohort study. SETTING: University of Michigan's C.S. Mott Children's Hospital PICU. PATIENTS: Patients admitted to the PICU with an anticipated PICU length of stay greater than 48 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: For each patient, the clinical team (attending, fellow, resident/nurse practitioner) was surveyed regarding existing and anticipated organ dysfunction. The primary outcomes were clinicians' accuracy at identifying multiple organ dysfunction syndrome and predicting new or progressive multiple organ dysfunction syndrome, compared to the objective assessment of multiple organ dysfunction syndrome using Proulx criteria. We also measured sensitivity, specificity, negative and positive predictive values, and negative and positive likelihood ratios of clinician assessments. We tested for differences in accuracy by clinician type using chi-square tests. Clinicians rated their confidence in prediction on a 5-point Likert scale. There were 476 eligible PICU admissions, for whom 1,218 surveys were completed. Multiple organ dysfunction syndrome was present in 89 patients (18.7%) at enrollment, and new or progressive multiple organ dysfunction syndrome occurred in 39 (8.2%). Clinicians correctly identified multiple organ dysfunction syndrome with 79.9% accuracy and predicted additional organ dysfunction with 82.6% accuracy. However, the positive and negative likelihood ratios for new or progressive multiple organ dysfunction syndrome prediction were 3.0 and 0.7, respectively, indicating a weak relationship between the clinician prediction and development of new or progressive multiple organ dysfunction syndrome. The positive predictive value of new or progressive multiple organ dysfunction syndrome prediction was just 22.1%. We found no differences in accuracy by clinician type for either identification of multiple organ dysfunction syndrome (80.2% vs 78.2% vs 81.0%; p = 0.57) or prediction of new or progressive multiple organ dysfunction syndrome (84.8% vs 82.8% vs 80.3%; p = 0.26) for attendings, fellows, and residents/nurse practitioners, respectively. There was a weak correlation between the confidence and accuracy of prediction (pairwise correlation coefficient, 0.26; p < 0.001). CONCLUSIONS: PICU clinicians correctly identified multiple organ dysfunction syndrome and predicted new or progressive multiple organ dysfunction syndrome with 80% accuracy. However, only 8% of patients developed new or progressive multiple organ dysfunction syndrome, so accuracy was largely due to true negative predictions. The positive predictive value for new or progressive multiple organ dysfunction syndrome prediction was just 22%. Accuracy did not differ by clinician type, but was correlated with self-rated confidence and was higher for negative predictions.