Project description:IntroductionPediatric asthma exacerbations account for >1.8 million emergency department (ED) visits annually. Asthma guidelines are intended to guide time-dependent treatment decisions that improve clinical outcomes; however, guideline adherence is inadequate. We examined whether an automatic disease detection system increases clinicians' use of paper-based guidelines and decreases time to a disposition decision.MethodsWe evaluated a computerized asthma detection system that triggered NHLBI-adopted, evidence-based practice to improve care in an urban, tertiary care pediatric ED in a 3-month (7/09-9/09) prospective, randomized controlled trial. A probabilistic system screened all ED patients for acute asthma. For intervention patients, the system generated the asthma protocol at triage for intervention patients to guide early treatment initiation, while clinicians followed standard processes for control patients. The primary outcome measures included time to patient disposition.ResultsThe system identified 1100 patients with asthma exacerbations, of which 704 had a final asthma diagnosis determined by a physician-established reference standard. The positive predictive value for the probabilistic system was 65%. The median time to disposition decision did not differ among the intervention (289 min; IQR = (184, 375)) and control group (288 min; IQR = (185, 375)) (p=0.21). The hospital admission rate was unchanged between intervention (37%) and control groups (35%) (p = 0.545). ED length of stay did not differ among the intervention (331 min; IQR = (226, 581)) and control group (331 min; IQR = (222, 516)) (p = 0.568).ConclusionDespite a high level of support from the ED leadership and staff, a focused education effort, and implementation of an automated disease detection, the use of the paper-based asthma protocol remained low and time to patient disposition did not change.
Project description:BackgroundDisadvantaged minority children are disproportionately affected by asthma. This group is also known to frequently use the emergency department (ED) for asthma care. Understanding decisions for use of the ED is important to prevent high cost.ObjectiveTo examine caregiver factors associated with the decision to use the ED for asthma care in inner-city children with asthma.MethodsOne hundred fifty participants in a randomized clinical trial testing the effectiveness of a home-based asthma intervention were enrolled, and questionnaires were administered to caregivers during the child's ED asthma visit. Sociodemographics, health characteristic data, and caregiver interview data were examined to ascertain factors that affected caregiver decision making to use the ED for asthma care. A cluster analysis was performed to correlate caregiver reasons for the decision to use the ED for asthma care.ResultsThree clusters emerged for decision making: urgency, preference for the use of the ED, and access to care issues. The perception of urgency was the most common reason reported by caregivers (91%) followed by reporting a preference for the ED for care (37%) and reporting access to care issues (31%). Access to care was primarily attributable to the inability to get a same-day appointment with their primary care practitioner (24%).ConclusionThe caregiver factors involved in the decision to use the ED can provide a basis for further intervention and investigation. Such factors include caregiver asthma home management, improvement in relationships with primary care practitioners, and access to care-related issues.
Project description:Asthma disparities have complex, neighborhood-level drivers that are not well understood. Consequently, identifying particular contextual factors that contribute to disparities is a public health goal. We study pediatric asthma emergency department (ED) visit disparities and neighborhood factors associated with them in South Carolina (SC) census tracts from 1999 to 2015. Leveraging a Bayesian framework, we identify risk clusters, spatially-varying relationships, and risk percentile-specific associations. Clusters of high risk occur in both rural and urban census tracts with high probability, with neighborhood-specific associations suggesting unique risk factors for each locale. Bayesian methods can help clarify the neighborhood drivers of health disparities.
Project description:RationaleCertain outdoor air pollutants cause asthma exacerbations in children. To advance understanding of these relationships, further characterization of the dose-response and pollutant lag effects are needed, as are investigations of pollutant species beyond the commonly measured criteria pollutants.ObjectivesInvestigate short-term associations between ambient air pollutant concentrations and emergency department visits for pediatric asthma.MethodsDaily counts of emergency department visits for asthma or wheeze among children aged 5 to 17 years were collected from 41 Metropolitan Atlanta hospitals during 1993-2004 (n = 91,386 visits). Ambient concentrations of gaseous pollutants and speciated particulate matter were available from stationary monitors during this time period. Rate ratios for the warm season (May to October) and cold season (November to April) were estimated using Poisson generalized linear models in the framework of a case-crossover analysis.Measurements and main resultsBoth ozone and primary pollutants from traffic sources were associated with emergency department visits for asthma or wheeze; evidence for independent effects of ozone and primary pollutants from traffic sources were observed in multipollutant models. These associations tended to be of the highest magnitude for concentrations on the day of the emergency department visit and were present at relatively low ambient concentrations.ConclusionsEven at relatively low ambient concentrations, ozone and primary pollutants from traffic sources independently contributed to the burden of emergency department visits for pediatric asthma.
Project description:ObjectivesThe emergency department (ED) is a challenging setting to conduct pharmacogenomic studies and integrate that data into fast-paced and potentially life-saving treatment decisions. Therefore, our objective is to present the methods and feasibility of a pilot pharmacogenomic study set in the ED that measured pediatric bronchodilator response (BDR) during acute asthma exacerbations.MethodsThis is an exploratory pilot study that collected buccal swabs for DNA and measured BDR during ED encounters for pediatric asthma exacerbations. We evaluated the study's feasibility with a qualitative analysis of ED provider surveys and quantitatively by the proportion of eligible patients enrolled.ResultsWe enrolled 59 out of 90 patients (65%) that were identified and considered eligible during a 5-month period (target enrollment 60 patients over 12 months). The median patient age was 7 years (interquartile range 4-9 years), 61% (N = 36) were male, and 92% (N = 54) were African American. Quality DNA collection was successful for all 59 patients. The ED provider survey response rate was 100%. Most ED providers reported that the study did not impact their workflow (98% of physicians, 88% of nurses, and 90% of respiratory therapists). ED providers did report difficulties with spirometry in the younger age group.ConclusionsPharmacogenomic studies can be conducted in the ED setting, and enroll a younger patient population with a high proportion of minority participants. By disseminating this study's methods and feasibility analysis, we aim to increase interest in pharmacogenomic studies set in the ED and aimed toward future ED-based pharmacogenomic decision-making.
Project description:Epidemiologic studies utilizing source apportionment (SA) of fine particulate matter have shown that particles from certain sources might be more detrimental to health than others; however, it is difficult to quantify the uncertainty associated with a given SA approach. In the present study, we examined associations between source contributions of fine particulate matter and emergency department visits for pediatric asthma in Atlanta, Georgia (2002-2010) using a novel ensemble-based SA technique. Six daily source contributions from 4 SA approaches were combined into an ensemble source contribution. To better account for exposure uncertainty, 10 source profiles were sampled from their posterior distributions, resulting in 10 time series with daily SA concentrations. For each of these time series, Poisson generalized linear models with varying lag structures were used to estimate the health associations for the 6 sources. The rate ratios for the source-specific health associations from the 10 imputed source contribution time series were combined, resulting in health associations with inflated confidence intervals to better account for exposure uncertainty. Adverse associations with pediatric asthma were observed for 8-day exposure to particles generated from diesel-fueled vehicles (rate ratio = 1.06, 95% confidence interval: 1.01, 1.10) and gasoline-fueled vehicles (rate ratio = 1.10, 95% confidence interval: 1.04, 1.17).
Project description:Background: Treatment response to systemic corticosteroid in asthmatic children is heterogeneous and may be mediated by epigenetic mechanism(s). We aim to identify DNA methylation (DNAm) changes responsive to steroid, and DNAm biomarkers that distinguish treatment response.Materials and methods: We followed 33 children (ages 5-18) presenting to the Emergency Department (ED) for asthma exacerbation. Based on whether they met discharge criteria in ?24 hours, participants were grouped into good and poor responders to steroid treatment. Nasal samples were collected upon presentation to the ED (T0) and 18-24 hours later (T1). Genome-wide DNAm was measured for both time points in 20 subjects, and compared between T0 and T1 in good and poor responders respectively. DNAm at T1 was also compared between two responder groups. DNAm of selected CpGs was verified in the complete cohort, and expression of associated genes was examined. Interactions between DNAm, common single nucleotide polymorphism (SNP) located at the CpG sites and treatment responses were assessed.Results: Three CpGs located in the OTX2 promoter showed responder-specific DNAm changes from T0 to T1, in which DNAm decreased in good but not in poor responders. Good and poor responders showed differential DNAm at T1 in 127 CpGs without and 182 CpGs with common SNP co-localization. Negative correlations between DNAm and gene expression were observed at CpGs located within the LDHC promoter, suggesting an impact of DNAm on gene regulation. Interactions between SNPs, DNAm and treatment response were detected.Conclusion: Acute systemic steroid treatment modifies nasal DNAm in good responders. Nasal DNAm, dependent or independent of SNPs, can differentiate response to treatment in acute asthmatic children.
Project description:BackgroundBecause ambient air pollution exposure occurs as mixtures, consideration of joint effects of multiple pollutants may advance our understanding of the health effects of air pollution.MethodsWe assessed the joint effect of air pollutants on pediatric asthma emergency department visits in Atlanta during 1998-2004. We selected combinations of pollutants that were representative of oxidant gases and secondary, traffic, power plant, and criteria pollutants, constructed using combinations of criteria pollutants and fine particulate matter (PM2.5) components. Joint effects were assessed using multipollutant Poisson generalized linear models controlling for time trends, meteorology, and daily nonasthma upper respiratory emergency department visit counts. Rate ratios (RRs) were calculated for the combined effect of an interquartile range increment in each pollutant's concentration.ResultsIncreases in all of the selected pollutant combinations were associated with increases in warm-season pediatric asthma emergency department visits (eg, joint-effect RR = 1.13 [95% confidence interval = 1.06-1.21] for criteria pollutants, including ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, and PM2.5). Cold-season joint effects from models without nonlinear effects were generally weaker than warm-season effects. Joint-effect estimates from multipollutant models were often smaller than estimates based on single-pollutant models, due to control for confounding. Compared with models without interactions, joint-effect estimates from models including first-order pollutant interactions were largely similar. There was evidence of nonlinear cold-season effects.ConclusionsOur analyses illustrate how consideration of joint effects can add to our understanding of health effects of multipollutant exposures and also illustrate some of the complexities involved in calculating and interpreting joint effects of multiple pollutants.