A Bayesian spatio-temporal analysis of neighborhood pediatric asthma emergency department visit disparities.
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ABSTRACT:
SUBMITTER: Bozigar M
PROVIDER: S-EPMC8591955 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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.
| S-EPMC3646328 | biostudies-literature
Project description:BackgroundAsthma exacerbation leading to emergency department (ED) visit is prevalent, an indicator of poor control of asthma, and is a potentially preventable clinical outcome.ObjectiveWe propose to utilize multiple data elements available in electronic medical records (EMRs) and claims database to create separate algorithms with high validity for clinical and research purposes to identify asthma exacerbation-related ED visit among the general population.MethodsWe performed a retrospective study with inclusion criteria of patients aged 4 to 40 years, a visit to Geisinger ED from January 1, 2006, to October 28, 2013, with asthma on their problem list. Different electronic data elements including chief complaints, vitals, season, smoking, medication use, and discharge diagnoses were obtained to create the algorithm. A stratified random sample was generated to select the charts for review. Chart review was performed to classify patients with asthma-related ED visit, that is, the gold standard. Two reviewers performed the chart review and validation was done on a small subset.ResultsThere were 966 eligible ED visits in the EMR sample and 731 in the claims sample. Agreement between reviewers was 95.45% and kappa statistic was 0.91. Mean age of the EMR sample was 22 years, and mostly white (93%). Multiple models conventionally used in studies were evaluated and the final model chosen included principal diagnosis, bronchodilator, and steroid use for both algorithms, chief complaints for EMR, and secondary diagnosis for claims. Area under the curve was 0.93 (95% confidence interval: 0.91-0.94) and 0.94 (0.93-0.96), respectively, for EMR and claims data, with positive predictive value of?>?94%. The algorithms are visually presented using nomograms.ConclusionWe were able to develop two separate algorithms for EMR and claims to identify asthma exacerbation-related ED visit with excellent diagnostic ability and varying discrimination threshold for clinical and research purposes.
| S-EPMC6051766 | biostudies-literature
Project description:Studies in urban emergency departments (EDs) have found poor quality of chronic asthma care and identified beliefs and barriers associated with low rates of follow-up with a primary care provider (PCP).To develop an ED-based intervention including asthma symptom screening, a video addressing beliefs and a mailed reminder; and measure the effect on PCP follow-up and asthma-related outcomes.This randomized, controlled trial enrolled children aged 1 to 18 years who were discharged after asthma treatment in an urban pediatric ED. Control subjects received instructions to follow-up with a PCP within 3 to 5 days. In addition, intervention subjects (1) received a letter to take to their PCP if they screened positive for persistent asthma symptoms, (2) viewed a video featuring families and providers discussing the importance of asthma control, and (3) received a mailed reminder to follow-up with a PCP. All subjects were contacted by telephone 1, 3, and 6 months after the ED visit, and follow-up was confirmed by PCP record review. Asthma-related quality of life (AQoL), symptoms, and beliefs about asthma care were assessed by using validated surveys.A total of 433 subjects were randomly assigned, and baseline measures were similar between study groups. After the intervention and before ED discharge, intervention subjects were more likely to endorse beliefs about the benefits of follow-up than controls. However, rates of PCP follow-up during the month after the ED visit (44.5%) were similar to control subjects (43.8%) as were AQoL, medication use, and ED visits.An ED-based intervention influenced beliefs but did not increase PCP follow-up or asthma-related outcomes.
| S-EPMC2803082 | biostudies-literature
Project description:Disadvantaged 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.To examine caregiver factors associated with the decision to use the ED for asthma care in inner-city children with asthma.One 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.Three 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%).The 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.
| S-EPMC5117360 | biostudies-literature
Project description:Predicting the magnitude of the annual seasonal peak in influenza-like illness (ILI)-related emergency department (ED) visit volumes can inform the decision to open influenza care clinics (ICCs), which can mitigate pressure at the ED. Using ILI-related ED visit data from the Alberta Real Time Syndromic Surveillance Net for Edmonton, Alberta, Canada, we developed (training data, 1 August 2004-31 July 2008) and tested (testing data, 1 August 2008-19 February 2014) spatio-temporal statistical prediction models of daily ILI-related ED visits to estimate high visit volumes 3 days in advance. Our Main Model, based on a generalised linear mixed model with random intercept, incorporated prediction residuals over 14 days and captured increases in observed volume ahead of peaks. During seasonal influenza periods, our Main Model predicted volumes within ±30% of observed volumes for 67%-82% of high-volume days and within 0.3%-21% of observed seasonal peak volumes. Model predictions were not as successful during the 2009 H1N1 pandemic. Our model can provide early warning of increases in ILI-related ED visit volumes during seasonal influenza periods of differing intensities. These predictions may be used to support public health decisions, such as if and when to open ICCs, during seasonal influenza epidemics.
| S-EPMC7003624 | biostudies-literature
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.
| S-EPMC2921597 | biostudies-literature
Project description: Not available
| S-EPMC7483361 | biostudies-literature
Project description:ObjectiveTo document erosion in the New York University Emergency Department (ED) visit algorithm's capability to classify ED visits and to provide a "patch" to the algorithm.Data sourcesThe Nationwide Emergency Department Sample.Study designWe used bivariate models to assess whether the percentage of visits unclassifiable by the algorithm increased due to annual changes to ICD-9 diagnosis codes. We updated the algorithm with ICD-9 and ICD-10 codes added since 2001.Principal findingsThe percentage of unclassifiable visits increased from 11.2 percent in 2006 to 15.5 percent in 2012 (p < .01), because of new diagnosis codes. Our update improves the classification rate by 43 percent in 2012 (p < .01).ConclusionsOur patch significantly improves the precision and usefulness of the most commonly used ED visit classification system in health services research.
| S-EPMC5517669 | biostudies-literature
Project description:Disparities in hypertensive disorders of pregnancy (HDP) exist among racial and ethnic groups in the US. However, little is known about spatio-temporal variations in HDP disparities. We used a Bayesian hierarchical regression approach to investigate spatio-temporal variations in HDP disparities from 2005 to 2014. County-level variation was firstly examined, followed by census tract-level variation assessment in counties where high HDP disparities were observed. A significant disadvantage in HDP was revealed for African Americans in Florida overall (Odds Ratio: 1.27, 95% Confidence Interval: 1.25, 1.29), with significant spatial variations. The greatest HDP disparities between African Americans and non-African Americans occurred in North Central Florida counties (the Big Bend region of Florida), with consistent patterns from 2005 to 2014. Analyses at census tract-level further revealed significant neighborhood disparities within these counties. Findings from this study provide important information for public health agencies and policymakers to reduce HDP disparities at the population level.
| S-EPMC6631343 | biostudies-literature
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).
| S-EPMC4447814 | biostudies-other