Near-universal hospitalization of US emergency department patients with cancer and febrile neutropenia

IMPORTANCE: Febrile neutropenia (FN) is the most common oncologic emergency and is among the most deadly. Guidelines recommend risk stratification and outpatient management of both pediatric and adult FN patients deemed to be at low risk of complications or mortality, but our prior single-center research demonstrated that the vast majority (95%) are hospitalized. OBJECTIVE: From a nationwide perspective, to determine the proportion of cancer patients of all ages hospitalized after an emergency department (ED) visit for FN, and to analyze variability in hospitalization rates. Our a priori hypothesis was that >90% of US cancer-associated ED FN visits would end in hospitalization. DESIGN: Analysis of data from the Nationwide Emergency Department Sample, 2006-2014. SETTING: Stratified probability sample of all US ED visits. PARTICIPANTS: Inclusion criteria were: (1) Clinical Classification Software code indicating cancer, (2) diagnostic code indicating fever, and (3) diagnostic code indicating neutropenia. We excluded visits ending in transfer. EXPOSURE: The hospital at which the visit took place. MAIN OUTCOMES AND MEASURES: Our main outcome is the proportion of ED FN visits ending in hospitalization, with an a priori hypothesis of >90%. Our secondary outcomes are: (a) hospitalization rates among subsets, and (b) proportion of variability in the hospitalization rate attributable to which hospital the patient visited, as measured by the intra-class correlation coefficient (ICC). RESULTS: Of 348,868 visits selected to be representative of all US ED visits, 94% ended in hospitalization (95% Confidence Interval [CI] 93-94%). Each additional decade of age conferred 1.23x increased odds of hospitalization. Those with private (92%), self-pay (92%), and other (93%) insurance were less likely to be hospitalized than those with public insurance (95%, odds ratios [OR] 0.74-0.76). Hospitalization was least likely at non-metropolitan hospitals (84%, OR 0.15 relative to metropolitan teaching hospitals), and was also less likely at metropolitan non-teaching hospitals (94%, OR 0.64 relative to metropolitan teaching hospitals). The ICC adjusted for hospital random effects and patient and hospital characteristics was 26% (95%CI 23-29%), indicating that 26% of the variability in hospitalization rate was attributable to which hospital the patient visited. CONCLUSIONS AND RELEVANCE: Nearly all cancer-associated ED FN visits in the US end in hospitalization. Inter-hospital variation in hospitalization practices explains 26% of the limited variability in hospitalization decisions. Simple, objective tools are needed to improve risk stratification for ED FN patients

Association of Obesity With Severity of Heart Failure Exacerbation: A Population‐Based Study

Background: Obesity and heart failure (HF) are important public health problems in the United States. Although studies have reported the association between obesity and higher chronic morbidity of HF, little is known about the relations of obesity with severity of HF exacerbation and in‐hospital mortality; therefore, we aimed to investigate the associations of obesity with severity of HF exacerbation and in‐hospital mortality. Methods and Results: This retrospective cohort study of adults hospitalized for HF exacerbation used population‐based data sets (the State Inpatient Databases) of 7 US states from 2012 to 2013. The outcomes were acute severity measures—use of positive pressure ventilation and hospital length of stay—and in‐hospital mortality. We determined the associations between obesity and these outcomes, including adjustment for sociodemographic factors and comorbidities. We identified 219 465 patients hospitalized for HF exacerbation. Of those, 37 539 (17.1%) were obese. Obese patients had a significantly higher risk of positive pressure ventilation use compared with nonobese patients (13.6% versus 8.8%), with a corresponding adjusted odds ratio of 1.61 (95% confidence interval, 1.55–1.68; P<0.001). Likewise, obese patients were more likely to have hospital length of stay of ≥4 days compared with nonobese patients (62.5% versus 56.7%), with an adjusted odds ratio of 1.40 (95% confidence interval, 1.37–1.44; P<0.001). In contrast, obese patients had significantly lower in‐hospital mortality compared with nonobese patients (1.7% versus 3.3%), with an adjusted odds ratio of 0.87 (95% confidence interval, 0.80–0.95; P=0.002). Conclusions: Based on large population‐based data sets of patients with HF exacerbation, obesity was associated with higher acute severity measures but lower in‐hospital mortality

Emergency Department Utilization by Children in the USA, 2010–2011

Introduction: Epidemiological surveillance data for emergency department (ED) visits by children are imperative to guide resource allocation and to develop health policies that advance pediatric emergency care. However, there are sparse population-based data on patient-level information (e.g., the number of children who present to the emergency department [ED]). In this context, we aimed to investigate both the patient- and visit-level rates of ED utilization by children. Methods: This was a retrospective cohort study using population-based multipayer data – state ED databases (SEDD) and state inpatient databases (SID) – from six geographically-dispersed U.S. states (California, Florida, Iowa, Nebraska, New York, and Utah) in 2010 and 2011. We identified all children aged <18 years who presented to the ED and described the patient-level ED visit rate, visit-level ED visit rate, and proportion of all ED visits made by children. We conducted the analysis using the 2011 SEDD and SID data. We also repeated the analysis using the 2010 data to determine the consistency of the results across different years. Results: In 2011, 2.9 million children with a patient identifier presented to EDs in the six U.S. states. At the patient-level, 15 out of every 100 children presented to an ED at least once per year. Of these children, 25% presented to EDs 2–3 times per year with an approximately 1.5-fold variation across the states (e.g., 19% in Utah vs. 28% in Florida). In addition, 5% presented to EDs ≥4 times per year. At the visit-level, 6.7 million ED visits were made by children in 2011 – 34 ED visits per 100 children annually. ED visits by children accounted for 22% of all ED visits (including both adults and children), with a relatively small variation across the states (e.g., 20% in New York vs. 24% in Nebraska). Analysis of the 2010 data gave similar results for the ED utilization by children. Conclusion: By using large population-based data, we found a substantial burden of ED visits at both patient- and visit-levels. These findings provide a strong foundation for policy makers and professional organizations to strengthen emergency care for children

Emergency department triage prediction of clinical outcomes using machine learning models

Abstract Background Development of emergency department (ED) triage systems that accurately differentiate and prioritize critically ill from stable patients remains challenging. We used machine learning models to predict clinical outcomes, and then compared their performance with that of a conventional approach—the Emergency Severity Index (ESI). Methods Using National Hospital and Ambulatory Medical Care Survey (NHAMCS) ED data, from 2007 through 2015, we identified all adult patients (aged ≥ 18 years). In the randomly sampled training set (70%), using routinely available triage data as predictors (e.g., demographics, triage vital signs, chief complaints, comorbidities), we developed four machine learning models: Lasso regression, random forest, gradient boosted decision tree, and deep neural network. As the reference model, we constructed a logistic regression model using the five-level ESI data. The clinical outcomes were critical care (admission to intensive care unit or in-hospital death) and hospitalization (direct hospital admission or transfer). In the test set (the remaining 30%), we measured the predictive performance, including area under the receiver-operating-characteristics curve (AUC) and net benefit (decision curves) for each model. Results Of 135,470 eligible ED visits, 2.1% had critical care outcome and 16.2% had hospitalization outcome. In the critical care outcome prediction, all four machine learning models outperformed the reference model (e.g., AUC, 0.86 [95%CI 0.85–0.87] in the deep neural network vs 0.74 [95%CI 0.72–0.75] in the reference model), with less under-triaged patients in ESI triage levels 3 to 5 (urgent to non-urgent). Likewise, in the hospitalization outcome prediction, all machine learning models outperformed the reference model (e.g., AUC, 0.82 [95%CI 0.82–0.83] in the deep neural network vs 0.69 [95%CI 0.68–0.69] in the reference model) with less over-triages in ESI triage levels 1 to 3 (immediate to urgent). In the decision curve analysis, all machine learning models consistently achieved a greater net benefit—a larger number of appropriate triages considering a trade-off with over-triages—across the range of clinical thresholds. Conclusions Compared to the conventional approach, the machine learning models demonstrated a superior performance to predict critical care and hospitalization outcomes. The application of modern machine learning models may enhance clinicians’ triage decision making, thereby achieving better clinical care and optimal resource utilization

Cohort Study of Maternal Gestational Weight Gain, Gestational Diabetes, and Childhood Asthma

Data on the association of maternal gestational weight gain (GWG) and gestational diabetes mellitus (GDM) with childhood asthma are limited and inconsistent. We aimed to investigate these associations in a U.S. pre-birth cohort. Analyses included 16,351 mother–child pairs enrolled in the Massachusetts General Hospital Maternal-Child Cohort (1998–2010). Data were obtained by linking electronic health records for prenatal visits/delivery to determine BMI, GWG, and GDM (National Diabetes Data Group criteria) and to determine asthma incidence and allergies (atopic dermatitis or allergic rhinitis) for children. The associations of prenatal exposures with asthma were evaluated using logistic regression adjusted for maternal characteristics. A total of 2306 children (14%) developed asthma by age 5 years. Overall, no association was found between GWG and asthma. GDM was positively associated with offspring asthma (OR 1.46, 95% CI 1.14–1.88). Associations between GDM and asthma were observed only among mothers with early pregnancy BMI between 20 and 24.9 kg/m2 (OR 2.31, CI 1.46–3.65, p-interaction 0.02). We report novel findings on the impact of prenatal exposures on asthma, including increased risk among mothers with GDM, particularly those with a normal BMI. These findings support the strengthening of interventions targeted toward a healthier pregnancy, which may also be helpful for childhood asthma prevention