Geomedicine: area-based socioeconomic measures for assessing risk of hospital reutilization among children admitted for asthma

Lower opportunity ZIP code is associated with worse outcomes after listing in pediatric heart transplantation

BACKGROUND

The Child Opportunity Index (COI) comprehensively measures children's social determinants of health. We describe association between COI and outcomes after listing for heart transplantation.

METHODS

We conducted a retrospective review of the United Network for Organ Sharing (UNOS) database for U.S. children listed for heart transplant between 2012 and 2020. ZIP codes were utilized to assign COI. Primary outcome was survival from time of listing. Secondary outcomes included waitlist survival, 1-year post-transplant survival, and conditional 1-year post-transplant survival. Cox regression was performed adjusting for payor, age, race, diagnosis, and support at listing for all outcomes except waitlist survival, for which Fine-Gray competing risk analysis was performed.

RESULTS

Of 5,723 children listed, 109 were excluded due to missing ZIP codes. Race/ethnicity and payor were associated with COI (p < 0.001). Patients living in very low COI ZIP codes compared to all others had increased mortality from time of listing (HR 1.16, CI 1.03-1.32, p = 0.02) with 1-, 5-, and 9-year survival of 79.3% vs 82.2%, 66.5% vs 73.0%, and 53.6% vs 64.7% respectively, were more likely to be removed from the waitlist due to death or being too sick (subdistribution HR 1.26, 95% CI 1.10-1.42), and had increased mortality conditional on one-year post-transplant survival (HR 1.38, 1.09-1.74, p = 0.008) with 1-, 3-, and 5- year survival of 94.7% vs 97.3%, 87.0% vs 93.1%, and 78.6% vs 86.9%.

CONCLUSIONS

Children living in lower opportunity ZIP codes had poorer survival from time of listing, poorer waitlist survival, and poorer conditional one-year post-transplant survival.

Building a regional pediatric asthma learning health system in support of optimal, equitable outcomes

Introduction

Asthma is characterized by preventable morbidity, cost, and inequity. We sought to build an Asthma Learning Health System (ALHS) to coordinate regional pediatric asthma improvement activities.

Methods

We generated quantitative and qualitative insights pertinent to a better, more equitable care delivery system. We used electronic health record data to calculate asthma hospitalization rates for youth in our region. We completed an "environmental scan" to catalog the breadth of asthma-related efforts occurring in our children's hospital and across the region. We supplemented the scan with group-level assessments and focus groups with parents, clinicians, and community partners. We used insights from this descriptive epidemiology to inform the definition of shared aims, drivers, measures, and prototype interventions.

Results

Greater Cincinnati's youth are hospitalized for asthma at a rate three times greater than the U.S. average. Black youth are hospitalized at a rate five times greater than non-Black youth. Certain neighborhoods bear the disproportionate burden of asthma morbidity. Across Cincinnati, there are many asthma-relevant activities that seek to confront this morbidity; however, efforts are largely disconnected. Qualitative insights highlighted the importance of cross-sector coordination, evidence-based acute and preventive care, healthy homes and neighborhoods, and accountability. These insights also led to a shared, regional aim: to equitably reduce asthma-related hospitalizations. Early interventions have included population-level pattern recognition, multidisciplinary asthma action huddles, and enhanced social needs screening and response.

Conclusion

Learning health system methods are uniquely suited to asthma's complexity. Our nascent ALHS provides a scaffold atop which we can pursue better, more equitable regional asthma outcomes.

Children with uncontrolled asthma from economically disadvantaged neighborhoods: Needs assessment and the development of a school-based telehealth and electronic inhaler monitoring system

BACKGROUND

Children from economically disadvantaged communities often encounter healthcare access barriers, increasing risk for poorly controlled asthma and subsequent healthcare utilization. This highlights the need to identify novel intervention strategies for these families.

OBJECTIVE

To better understand the needs and treatment preferences for asthma management in children from economically disadvantaged communities and to develop a novel asthma management intervention based on an initial needs assessment and stakeholder feedback.

METHODS

Semistructured interviews and focus groups were conducted with 19 children (10-17 years old) with uncontrolled asthma and their caregivers, 14 school nurses, 8 primary care physicians, and three school resource coordinators from economically disadvantaged communities. Interviews and focus groups were audio-taped and transcribed verbatim and then analyzed thematically to inform intervention development. Using stakeholder input, an intervention was developed for children with uncontrolled asthma and presented to participants for feedback to fully develop a novel intervention.

RESULTS

The needs assessment resulted in five themes: (1) barriers to quality asthma care, (2) poor communication across care providers, (3) problems identifying and managing symptoms and triggers among families, (4) difficulties with adherence, and (5) stigma. A proposed video-based telehealth intervention was proposed to stakeholders who provided favorable and informative feedback for the final development of the intervention for children with uncontrolled asthma.

CONCLUSIONS

Stakeholder input and feedback provided information critical to the development of a multicomponent (medical and behavioral) intervention in a school setting that uses technology to facilitate care, collaboration, and communication among key stakeholders to improve asthma management for children from economically disadvantaged neighborhoods.

Factors associated with future hospitalization among children with asthma: a systematic review

OBJECTIVE

Asthma is a leading cause of emergency department (ED) visits and hospitalizations in children, though many could be prevented. Our study objective was to identify factors from the published literature that are associated with future hospitalization for asthma beyond 30 days following an initial asthma ED visit.

DATA SOURCES

We searched CINAHL, CENTRAL, MEDLINE, and Embase for all studies examining factors associated with asthma-related hospitalization in children from January 1, 1992 to February 7, 2022.Selecting Studies: All citations were reviewed independently by two reviewers and studies meeting inclusion criteria were assessed for risk of bias. Data on all reported variables were extracted from full text and categorized according to identified themes. Where possible, data were pooled for meta-analysis using random effects models.

RESULTS

Of 2262 studies, 68 met inclusion criteria. We identified 28 risk factors and categorized these into six themes. Factors independently associated with future hospitalization in meta-analysis include: exposure to environmental tobacco smoke (OR = 1.94 95%CI 0.67-5.61), pets exposure (OR = 1.67 95%CI 1.17-2.37), and previous asthma hospitalizations (OR = 3.47 95% CI 2.95-4.07). Additional related factors included previous acute care visits, comorbid health conditions (including atopy), allergen exposure, severe-persistent asthma phenotype, inhaled steroid use prior to ED visit, poor asthma control, higher severity symptoms at ED presentation, warmer season at admission, longer length of stay or ICU admission, and African-American race/ethnicity.

CONCLUSIONS

We identified multiple factors that are consistently associated with future asthma hospitalization in children and could be used to identify those who would benefit from targeted preventative interventions.

Predictors of Acute Care Reutilization in Pediatric Patients With Amoxicillin-Associated Reactions

BACKGROUND

Amoxicillin-associated reactions (AARs) contribute to substantial health care utilization, with a reutilization rate of 10% in pediatric emergency department (ED) and urgent care (UC) settings.

OBJECTIVE

To identify predictors of ED/UC reutilization by examining patients' clinical features and providers' management of AARs.

METHODS

Through a retrospective chart review of 668 patients presenting with AARs over 2 years to the pediatric ED/UC, we examined clinical features associated with ED/UC reutilization, including rash phenotype, systemic symptoms (fever, angioedema, joint involvement, gastrointestinal symptoms), and providers' management (pharmacologic treatment and counseling). We then constructed a statistical model to predict ED/UC reutilization using stepwise backward model selection.

RESULTS

ED/UC reutilizers were more likely to be male (P = .008) and have fever (P = .0001), angioedema (P < .0001), joint involvement (P < .0001), and gastrointestinal symptoms (P = .0001) during their AAR course. Rash phenotypes differed between groups (P < .0001), as ED/UC reutilizers more frequently exhibited urticaria. However, there were no differences in clinical management between groups, including pharmacologic recommendations, at the initial ED/UC encounter. In addition, our statistical model identified younger patients <2 years of age as more likely to reutilize ED/UC resources if providers did not document specific return precautions (odds ratio, 3.6; 95% confidence interval, 1.7-7.7).

CONCLUSION

Recognition of clinical features and treatment gaps associated with ED/UC reutilization will guide interventions to optimize care in children presenting with AARs, such as improved anticipatory guidance and early allergy consultation. Prospective studies are needed to determine whether these interventions will reduce ED/UC reutilization and facilitate timely allergy testing.

Hospital-Level Neighborhood Opportunity and Rehospitalization for Common Diagnoses at US Children's Hospitals

OBJECTIVE

Neighborhood conditions influence child health outcomes, but data examining association between local factors and hospital utilization are lacking. We determined if hospitals' mix of patients by neighborhood opportunity correlates with rehospitalization for common diagnoses at US children's hospitals.

METHODS

We analyzed all discharges in 2018 for children ≤18 years at 47 children's hospitals for 14 common diagnoses. The exposure was hospital-level mean neighborhood opportunity - measured by Child Opportunity Index (COI) - for each diagnosis. The outcome was same-cause rehospitalization within 365 days. We measured association via Pearson correlation coefficient. For diagnoses with significant associations, we also examined shorter rehospitalization time windows and compared unadjusted and COI-adjusted rehospitalization rates.

RESULTS

There were 256,871 discharges included. Hospital-level COI ranged from 17th to 70th percentile nationally. Hospitals serving lower COI neighborhoods had more frequent rehospitalization for asthma (ρ -0.34 [95% confidence interval -0.57, -0.06]) and diabetes (ρ -0.33 [-0.56, -0.04]), but fewer primary mental health rehospitalizations (ρ 0.47 [0.21, 0.67]). There was no association for 11 other diagnoses. Secondary timepoint analysis revealed increasing correlation over time, with differences by diagnosis. Adjustment for hospital-level COI resulted in 26%, 32%, and 45% of hospitals changing >1 decile in rehospitalization rank order for diabetes, asthma, and mental health diagnoses, respectively.

CONCLUSIONS

Children's hospitals vary widely in their mix of neighborhoods served. Asthma, diabetes, and mental health rehospitalization rates correlate with COI, suggesting that neighborhood factors may influence outcome disparities for these conditions. Hospital outcomes may be affected by neighborhood opportunity, which has implications for benchmarking.

Using Geomarkers and Sociodemographics to Inform Assessment of Caregiver Adversity and Resilience

BACKGROUND AND OBJECTIVES

A high level of caregiver adverse childhood experiences (ACEs) and/or low resilience is associated with poor outcomes for both caregivers and their children after hospital discharge. It is unknown if sociodemographic or area-based measures (ie, "geomarkers") can inform the assessment of caregiver ACEs or resilience. Our objective was to determine if caregiver ACEs or resilience can be identified by using any combinations of sociodemographic measures, geomarkers, and/or caregiver-reported household characteristics.

METHODS

Eligible participants for this cohort study were English-speaking caregivers of children hospitalized on a hospital medicine team. Caregivers completed the ACE questionnaire, Brief Resilience Scale, and strain surveys. Exposures included sociodemographic characteristics available in the electronic health record (EHR), geomarkers tied to a patient's geocoded home address, and household characteristics that are not present in the EHR (eg, income). Primary outcomes were a high caregiver ACE score (≥4) and/or a low BRS Score (<3).

RESULTS

Of the 1272 included caregivers, 543 reported high ACE or low resilience, and 63 reported both. We developed the following regression models: sociodemographic variables in EHR (Model 1), EHR sociodemographics and geomarkers (Model 2), and EHR sociodemographics, geomarkers, and additional survey-reported household characteristics (Model 3). The ability of models to identify the presence of caregiver adversity was poor (all areas under receiver operating characteristics curves were <0.65).

CONCLUSIONS

Models using EHR data, geomarkers, and household-level characteristics to identify caregiver adversity had limited utility. Directly asking questions to caregivers or integrating risk and strength assessments during pediatric hospitalization may be a better approach to identifying caregiver adversity.

Association of Primary Care Shortage Areas with Adverse Outcomes after Pediatric Liver Transplant

OBJECTIVE

To characterize associations between living in primary care shortage areas and graft failure/death for children after liver transplantation.

STUDY DESIGN

This was an observational study of all pediatric patients (aged <19 years) who received a liver transplant between January 1, 2005, and December 31, 2015 in the US, with follow-up through January 2019 (N = 5964). One hundred ninety-five patients whose home ZIP code could not be matched to primary care shortage area status were excluded. The primary outcome was a composite endpoint of graft failure or death. We used Cox proportional hazards to model the associations between health professional shortage area (HPSA) and graft failure/death.

RESULTS

Children living in HPSAs had lower estimated graft survival rates at 10 years compared with those not in HPSAs (76% vs 80%; P < .001). In univariable analysis, residence in an HPSA was associated with a 22% higher hazard of graft failure/death than non-residence in an HPSA (hazard ratio [HR], 1.22; 95% CI, 1.09-1.36; P < .001). Black children from HPSAs had a 67% higher hazard of graft failure/death compared with those not in HPSAs (HR, 1.67; 95% CI, 1.29 to 2.16; P = .006); the effect of HPSA status was less pronounced for White children (HR, 1.11; 95% CI, 0.98-1.27; P = .10).

CONCLUSIONS

Children living in primary care shortage areas are at increased risk of graft failure and death after liver transplant, and this risk is particularly salient for Black children. Future work to understand how living in these regions contributes to adverse outcomes may enable teams to mitigate this risk for all children with chronic illness.

Prospective study of factors associated with asthma attack recurrence (ATTACK) in children from three Ecuadorian cities during COVID-19: a study protocol

INTRODUCTION

Asthma is a growing health problem in children in marginalised urban settings in low-income and middle-income countries. Asthma attacks are an important cause of emergency care attendance and long-term morbidity. We designed a prospective study, the Asthma Attacks study, to identify factors associated with recurrence of asthma attacks (or exacerbations) among children and adolescents attending emergency care in three Ecuadorian cities.

METHODS AND ANALYSIS

Prospective cohort study designed to identify risk factors associated with recurrence of asthma attacks in 450 children and adolescents aged 5-17 years attending emergency care in public hospitals in three Ecuadorian cities (Quito, Cuenca and Portoviejo). The primary outcome will be rate of asthma attack recurrence during up to 12 months of follow-up. Data are being collected at baseline and during follow-up by questionnaire: sociodemographic data, asthma history and management (baseline only); recurrence of asthma symptoms and attacks (monthly); economic costs of asthma to family; Asthma Control Test; Pediatric Asthma Quality of life Questionnaire; and Newcastle Asthma Knowledge Questionnaire (baseline only). In addition, the following are being measured at baseline and during follow-up: lung function and reversibility by spirometry before and after salbutamol; fractional exhaled nitric oxide (FeNO); and presence of IgG antibodies to SARS-CoV-2 in blood. Recruitment started in 2019 but because of severe disruption to emergency services caused by the COVID-19 pandemic, eligibility criteria were modified to include asthmatic children with uncontrolled symptoms and registered with collaborating hospitals. Data will be analysed using logistic regression and survival analyses.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the Hospital General Docente de Calderon (CEISH-HGDC 2019-001) and Ecuadorian Ministry of Public Health (MSP-CGDES-2021-0041-O N° 096-2021). The study results will be disseminated through presentations at conferences and to key stakeholder groups including policy-makers, postgraduate theses, peer-review publications and a study website. Participants gave informed consent to participate in the study before taking part.

Community-Level Social Determinants of Health and Well-Child Visits Among Alabama Medicaid Enrollees

Well-child visits focus on health promotion and disease detection and are critical to the appropriate provision of care. Evidence has shown that participation in well-child visits is associated with various patient-level factors; however, there has been an increasing focus on the influence of community-level social determinants of health (SDoH). This study explored associations between well-child visits and community-level SDoH at the census tract level among children enrolled in Alabama Medicaid. Through this analysis, it is possible to understand the distribution of care among this underserved population in different geographic settings, thus identifying potential disparities and areas for targeted intervention. Using administrative data from 2015 to 2017 enrollees in Alabama Medicaid that have been geographically linked to information on urbanicity and poverty, logistic regressions (both in total and stratified by age group) were estimated with separate community-level urbanicity, poverty variables, and individual characteristics. The regressions were repeated using a combined urbanicity/poverty variable. Looking at urbanicity and poverty together, with the exception of the least urban areas, it was those living in census tracts where there was discordance in urbanicity and poverty that had the highest likelihood of receiving well-child visits compared with those in census tracts classified as medium poverty (all urbanicity levels). There is a positive effect for Medicaid enrollees in the middle tertile of urbanicity in areas of low and high poverty and in wealthier more urban areas. If poverty and urbanicity were explored separately, some of the nuances would not have been apparent.

Comparing Artificial Intelligence and Traditional Methods to Identify Factors Associated With Pediatric Asthma Readmission

OBJECTIVE

To identify and contrast risk factors for six-month pediatric asthma readmissions using traditional models (Cox proportional-hazards and logistic regression) and artificial neural-network modeling.

METHODS

This retrospective cohort study of the 2013 Nationwide Readmissions Database included children 5 to 18 years old with a primary diagnosis of asthma. The primary outcome was time to asthma readmission in the Cox model, and readmission within 180 days in logistic regression. A basic neural network construction with 2 hidden layers and multiple replications considered all dataset variables and potential variable interactions to predict 180-day readmissions. Logistic regression and neural-network models were compared on area-under-the receiver-operating curve.

RESULTS

Of 18,489 pediatric asthma hospitalizations, 1858 were readmitted within 180 days. In Cox and logistic models, longer index length of stay, public insurance, and nonwinter index admission seasons were associated with readmission risk, whereas micropolitan county was protective. In neural-network modeling, 9 factors were significantly associated with readmissions. Four overlapped with the Cox model (nonwinter-month admission, long length of stay, public insurance, and micropolitan hospitals), whereas 5 were unique (age, hospital bed number, teaching-hospital status, weekend index admission, and complex chronic conditions). The area under the curve was 0.592 for logistic regression and 0.637 for the neural network.

CONCLUSIONS

Different methods can produce different readmission models. Relying on traditional modeling alone overlooks key readmission risk factors and complex factor interactions identified by neural networks.

Revealing the racial and spatial disparity in pediatric asthma: A Kansas City case study

Black and other socially disadvantaged children are disproportionately burdened by high rates of pediatric asthma. Intraurban variation in environmental risk factors and limited access to high-resolution health data make it difficult to identify vulnerable patients, communities, or the immediate exposures that may contribute to pediatric asthma exacerbation. This article presents a novel, interdisciplinary health disparities research and intervention strategy applied to the problem of pediatric asthma in Kansas City. First, address-level electronic health records from a major children's hospital in the Kansas City region are used to map the distribution of asthma encounters in 2012 at a high spatial resolution. Census tract Environmental Justice Screening Method (EJSM) indicators are then developed to scan for patterns in both the population health risks and vulnerabilities that may contribute to the burden of asthma in different communities. A Bayesian Profile Regression cluster analysis is used to systematically explore the complex relationships between census tract EJSM indicators and pediatric asthma incidence rates, helping to identify population characteristics and risk factors associated with both high and low rates of pediatric asthma throughout the region. The EJSM scanning exercise and BPR analysis demonstrate that each community faces a distinct set of risks and vulnerabilities that can contribute to the rate of acute pediatric asthma acute care encounters, providing targets for research and intervention. It is clear, however, that different forms of social disadvantage are driving high rates of pediatric asthma, which is closely tied to uneven development patterns and racial residential segregation. The results provide a starting point for designing place-based health disparities research and intervention strategies catered to the unique needs of vulnerable patients and communities; disparities-focused research and intervention strategies that leverage local knowledge and resources through community-based practices.

Social Risk Screening in Pediatric Primary Care Anticipates Acute Care Utilization

OBJECTIVE

The aim of the study was to assess whether responses to a standardized social risk screen administered during pediatric well-child visits (WCV) were associated with emergency department (ED) or urgent care (UC) utilization.

METHODS

This was a retrospective cohort study of 26,509 children younger than 13 years with a WCV between January 1, 2012, and December 31, 2013. Exposure was positive response(s) on a standardized social risk screening questionnaire at the index WCV. Primary outcome was number of ED or UC visits in the 12 months after the WCV.

RESULTS

The cohort was 50.9% male and 65.7% black, with a median age of 3.6 years. More than 20% had a positive response to at least one question on the social risk screen. For those reporting any social risk, 46.7% had 1 or more EDs or UC visit within 12 months. Each additional reported risk was associated with a 4% increase in the rate of ED utilization (incidence rate ratio = 1.04, 95% confidence interval = 1.02-1.07) and a 16% increase in the rate of hospitalizations (incidence rate ratio = 1.16, 95% confidence interval = 1.08-1.24). Similar patterns were noted for those visiting the ED 4 times or more (adjusted odds ratio = 1.09, 1.03-1.15) and hospitalization 2 times or more (adjusted odds ratio = 1.19, 1.04-1.35) in the year after the WCV. Those who screened positive on food insecurity, safety, and desire to meet with a social worker questions also had higher odds of ED or UC utilization.

CONCLUSIONS

Families reporting a social concern on a standardized screen during a WCV had increased acute care utilization in the subsequent year. Identifying socially at-risk families may allow for the creation of more effective strategies to prevent future utilization.

Understanding Pediatric Surgery Cancellation: Geospatial Analysis

BACKGROUND

Day-of-surgery cancellation (DoSC) represents a substantial wastage of hospital resources and can cause significant inconvenience to patients and families. Cancellation is reported to impact between 2% and 20% of the 50 million procedures performed annually in American hospitals. Up to 85% of cancellations may be amenable to the modification of patients' and families' behaviors. However, the factors underlying DoSC and the barriers experienced by families are not well understood.

OBJECTIVE

This study aims to conduct a geospatial analysis of patient-specific variables from electronic health records (EHRs) of Cincinnati Children's Hospital Medical Center (CCHMC) and of Texas Children's Hospital (TCH), as well as linked socioeconomic factors measured at the census tract level, to understand potential underlying contributors to disparities in DoSC rates across neighborhoods.

METHODS

The study population included pediatric patients who underwent scheduled surgeries at CCHMC and TCH. A 5-year data set was extracted from the CCHMC EHR, and addresses were geocoded. An equivalent set of data >5.7 years was extracted from the TCH EHR. Case-based data related to patients' health care use were aggregated at the census tract level. Community-level variables were extracted from the American Community Survey as surrogates for patients' socioeconomic and minority status as well as markers of the surrounding context. Leveraging the selected variables, we built spatial models to understand the variation in DoSC rates across census tracts. The findings were compared to those of the nonspatial regression and deep learning models. Model performance was evaluated from the root mean squared error (RMSE) using nested 10-fold cross-validation. Feature importance was evaluated by computing the increment of the RMSE when a single variable was shuffled within the data set.

RESULTS

Data collection yielded sets of 463 census tracts at CCHMC (DoSC rates 1.2%-12.5%) and 1024 census tracts at TCH (DoSC rates 3%-12.2%). For CCHMC, an L2-normalized generalized linear regression model achieved the best performance in predicting all-cause DoSC rate (RMSE 1.299%, 95% CI 1.21%-1.387%); however, its improvement over others was marginal. For TCH, an L2-normalized generalized linear regression model also performed best (RMSE 1.305%, 95% CI 1.257%-1.352%). All-cause DoSC rate at CCHMC was predicted most strongly by previous no show. As for community-level data, the proportion of African American inhabitants per census tract was consistently an important predictor. In the Texas area, the proportion of overcrowded households was salient to DoSC rate.

CONCLUSIONS

Our findings suggest that geospatial analysis offers potential for use in targeting interventions for census tracts at a higher risk of cancellation. Our study also demonstrates the importance of home location, socioeconomic disadvantage, and racial minority status on the DoSC of children's surgery. The success of future efforts to reduce cancellation may benefit from taking social, economic, and cultural issues into account.

Risk Factors for Pediatric Asthma Readmissions: A Systematic Review

OBJECTIVE

To systematically review the literature on pediatric asthma readmission risk factors.

STUDY DESIGN

We searched PubMed/MEDLINE, CINAHL, Scopus, PsycINFO, and Cochrane Central Register of Controlled Trials for published articles (through November 2019) on pediatric asthma readmission risk factors. Two authors independently screened titles and abstracts and consensus was reached on disagreements. Full-text articles were reviewed and inclusion criteria applied. For articles meeting inclusion criteria, authors abstracted data on study design, patient characteristics, and outcomes, and 4 authors assessed bias risk.

RESULTS

Of 5749 abstracts, 74 met inclusion criteria. Study designs, patient populations, and outcome measures were highly heterogeneous. Risk factors consistently associated with early readmissions (≤30 days) included prolonged length of stay (OR range, 1.1-1.6) and chronic comorbidities (1.7-3.2). Risk factors associated with late readmissions (>30 days) included female sex (1.1-1.6), chronic comorbidities (1.5-2), summer discharge (1.5-1.8), and prolonged length of stay (1.04-1.7). Across both readmission intervals, prior asthma admission was the most consistent readmission predictor (1.3-5.4).

CONCLUSIONS

Pediatric asthma readmission risk factors depend on the readmission interval chosen. Prior hospitalization, length of stay, sex, and chronic comorbidities were consistently associated with both early and late readmissions.

TRIAL REGISTRATION

CRD42018107601.

Neighborhood Conditions and Recurrent Emergency Department Utilization by Children in the United States

OBJECTIVE

To determine the associations of social and physical neighborhood conditions with recurrent emergency department (ED) utilization by children in the US.

STUDY DESIGN

This cross-sectional study was conducted with the National Survey of Children's Health from 2016 to 2018 to determine the associations of neighborhood characteristics of cohesion, safety, amenities, and detractors with the proportions of children aged 1-17 years with recurrent ED utilization, defined as 2 or more ED visits during the past 12 months. A multivariable regression model was used to determine the independent association of each neighborhood characteristic with recurrent ED utilization controlling for individual-level characteristics.

RESULTS

In this study of 98 711 children weighted to a population of 70 million nationally, children had significantly greater rates of recurrent ED utilization if they lived in neighborhoods that were not cohesive, were not safe, or had detractors present (all P < .001). With adjustment for individual-level covariates and the other neighborhood characteristics, only neighborhood detractors were independently associated with recurrent ED utilization (1 detractor: aOR 1.32, 95% CI 1.03-1.68; 2 or 3 detractors: aOR 1.37, 95% CI 1.04-1.81).

CONCLUSIONS

Among neighborhood characteristics, the presence of physical detractors such as rundown housing and vandalism was most strongly associated with recurrent ED utilization by children. Negative attributes of the built environment may be a potential target for neighborhood-level, place-based interventions to alleviate disparities in child healthcare utilization.

Association Between Neighborhood-level Socioeconomic Deprivation and the Medication Level Variability Index for Children Following Liver Transplantation

BACKGROUND

Neighborhood socioeconomic deprivation is associated with adverse health outcomes. We sought to determine if neighborhood socioeconomic deprivation was associated with adherence to immunosuppressive medications after liver transplantation.

METHODS

We conducted a secondary analysis of a multicenter, prospective cohort of children enrolled in the medication adherence in children who had a liver transplant study (enrollment 2010-2013). Participants (N = 271) received a liver transplant ≥1 year before enrollment and were subsequently treated with tacrolimus. The primary exposure, connected to geocoded participant home addresses, was a neighborhood socioeconomic deprivation index (range 0-1, higher indicates more deprivation). The primary outcome was the medication level variability index (MLVI), a surrogate measure of adherence to immunosuppression in pediatric liver transplant recipients. Higher MLVI indicates worse adherence behavior; values ≥2.5 are predictive of late allograft rejection.

RESULTS

There was a 5% increase in MLVI for each 0.1 increase in deprivation index (95% confidence interval, -1% to 11%; P = 0.08). Roughly 24% of participants from the most deprived quartile had an MLVI ≥2.5 compared with 12% in the remaining 3 quartiles (P = 0.018). Black children were more likely to have high MLVI even after adjusting for deprivation (adjusted odds ratio 4.0 95% confidence interval, 1.7-10.6).

CONCLUSIONS

This is the first study to evaluate associations between neighborhood socioeconomic deprivation and an objective surrogate measure of medication adherence in children posttransplant. These findings suggest that neighborhood context may be an important consideration when assessing adherence. Differential rates of medication adherence may partly explain links between neighborhood factors and adverse health outcomes following pediatric liver transplantation.

Pediatric asthma hospitalization: individual and environmental characteristics of high utilizers in South Texas

OBJECTIVE

Few studies have examined factors affecting the high frequency of hospitalization for pediatric asthma. This study identifies individual and environmental characteristics of children with asthma from a low-income community with a high number of hospitalizations.

METHODS

The study population included 902 children admitted at least once to a children's hospital in South Texas because of asthma from 2010 to 2016. The population was divided into three groups by utilization frequency (high: ≥4 times, medium: 2-3 times, or low: 1 time). Individual-level factors at index admission and environmental factors were included for the analysis. Unadjusted and adjusted multivariate ordered logistic regression models were applied to identify significant characteristics of high hospital utilizers.

RESULTS

The high utilization group comprised 2.4% of total patients and accounted for substantial hospital resource utilization: 10.8% of all admissions and 13.5% of days stayed in the hospital. Patients in the high utilization group showed longer length of stay (LOS) and shorter time between admissions on average than the other two groups. The multivariate ordered logistic regression models revealed that age of 5-11 years (OR = 0.57, 95%CI = 0.35-0.93), longer LOS (2 days: OR = 1.80, 95%CI = 1.15-2.84; ≥3 days: OR = 3.38, 95%CI = 2.10-5.46), warm season at index admission (OR = 1.49, 95%CI = 1.01-2.20), and higher average ozone level in children's residential neighborhoods (OR = 1.78, 95%CI = 1.01-3.14) were significantly associated with a higher number of asthma hospitalizations.

CONCLUSIONS

The findings suggest the importance of monitoring high hospital utilizers and establishing strategies for such patients based on their characteristics to reduce repeated hospitalizations and to increase optimal use of hospital resources.

Social determinants of health, emergency department utilization, and people with intellectual and developmental disabilities

BACKGROUND

People with intellectual and developmental disabilities' (IDD's) health is largely dependent on the government services they receive. Medicaid managed care has emerged as one mechanism used to provide services to people with disabilities in an attempt to reduce costs. In managed care, there has been an emphasis on reducing emergency department visits and hospital admissions in an effort to reduce expenditures.

OBJECTIVE

The purpose of this exploratory study was to examine the impact social determinants of health -"conditions in the environments in which people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks" (n.p.)¹ - had on the emergency department utilization of people with IDD.

METHODS

We had the following research question: what is the relationship between social determinants and emergency department utilization (visits) among adults with IDD? To explore this research question, a negative binomial regression analysis was used with secondary social determinant outcomes data (from Personal Outcome Measures®) and emergency department visit data from a random sample of 251 people with IDD. We also examined relationships with participants' demographics.

RESULTS

Our findings revealed for every one unit increase in the number of social determinant outcomes present, there was a 7.97% decrease in emergency department visits. There were also significant relationships between emergency department visits, and complex support needs, intellectual disability level, primary communication method, and residence type.

CONCLUSIONS

Social determinants are critical to promote the quality of life and health equity of people with IDD.

Neighborhood socioeconomic deprivation is associated with worse patient and graft survival following pediatric liver transplantation

Long-term outcomes remain suboptimal following pediatric liver transplantation; only one third of children have normal biochemical liver function without immunosuppressant comorbidities 10 years posttransplant. We examined the association between an index of neighborhood socioeconomic deprivation with graft and patient survival using the Scientific Registry of Transplant Recipients. We included children <19 years who underwent liver transplantation between January 1, 2008 to December 31, 2013 (n = 2868). Primary exposure was a neighborhood socioeconomic deprivation index-linked via patient home ZIP code-with a range of 0-1 (values nearing 1 indicate neighborhoods with greater socioeconomic deprivation). Primary outcome measures were graft failure and death, censored at 10 years posttransplant. We modeled survival using Cox proportional hazards. In univariable analysis, each 0.1 increase in the deprivation index was associated with a 14.3% (95% confidence interval [CI]): 3.8%-25.8%) increased hazard of graft failure and a 12.5% (95% CI: 2.5%-23.6%) increased hazard of death. In multivariable analysis adjusted for race, each 0.1 increase in the deprivation index was associated with a 11.5% (95% CI: 1.6%-23.9%) increased hazard of graft failure and a 9.6% (95% CI: -0.04% to 20.7%) increased hazard of death. Children from high deprivation neighborhoods have diminished graft and patient survival following liver transplantation. Greater attention to neighborhood context may result in improved outcomes for children following liver transplantation.

Home Oxygen Use and 1-Year Readmission among Infants Born Preterm with Bronchopulmonary Dysplasia Discharged from Children's Hospital Neonatal Intensive Care Units

OBJECTIVE

To determine associations between home oxygen use and 1-year readmissions for preterm infants with bronchopulmonary dysplasia (BPD) discharged from regional neonatal intensive care units.

STUDY DESIGN

We performed a secondary analysis of the Children's Hospitals Neonatal Database, with readmission data via the Pediatric Hospital Information System and demographics using ZIP-code-linked census data. We included infants born <32 weeks of gestation with BPD, excluding those with anomalies and tracheostomies. Our primary outcome was readmission by 1 year corrected age; secondary outcomes included readmission duration, mortality, and readmission diagnosis-related group codes. A staged multivariable logistic regression was adjusted for center, clinical, and social risk factors; at each stage we included variables associated at P < .1 in bivariable analysis with home oxygen use or readmission.

RESULTS

Home oxygen was used in 1906 of 3574 infants (53%) in 22 neonatal intensive care units. Readmission occurred in 34%. Earlier gestational age, male sex, gastrostomy tube, surgical necrotizing enterocolitis, lower median income, nonprivate insurance, and shorter hospital-to-home distance were associated with readmission. Home oxygen was not associated with odds of readmission (OR, 1.2; 95% CI, 0.98-1.56), readmission duration, or mortality. Readmissions for infants with home oxygen were more often coded as BPD (16% vs 4%); readmissions for infants on room air were more often gastrointestinal (29% vs 22%; P < .001). Clinical risk factors explained 72% of center variance in readmission.

CONCLUSIONS

Home oxygen use is not associated with readmission for infants with BPD in regional neonatal intensive care units. Center variation in home oxygen use does not impact readmission risk. Nonrespiratory problems are important contributors to readmission risk for infants with BPD.

Telehealth delivery of adherence and medication management system improves outcomes in inner-city children with asthma

Healthcare disparities exist in pediatric asthma in the United States. Children from minority, low-income families in inner-city areas encounter barriers to healthcare, leading to greater rates of poorly controlled asthma and healthcare utilization. Finding an effective way to deliver high-quality healthcare to this underserved population to improve outcomes, reduce morbidity and mortality, and reduce healthcare utilization is of the utmost importance. The purpose of this study was to assess the feasibility and efficacy of a novel school-based care delivery model that incorporates video-based telehealth (VBT) medical and self-management visits with electronic inhaler monitoring to improve asthma outcomes. Over a 6-month period, children from inner-city, low-income schools with uncontrolled asthma completed seven scheduled medical visits with an asthma specialist and five self-management visits with an adherence psychologist at school using VBT. Composite Asthma Severity Index (CASI) scores and electronic inhaler monitor data were recorded and analyzed. A total of 21 patients were enrolled in the study. Study subjects with higher baseline severity (CASI ≥ 4 at visit 1) demonstrated a greater reduction in their score than those with lower baseline severity (CASI < 4 at visit 1). The CASI domains showed improvement in daytime symptoms, nighttime symptoms, and exacerbations. Adherence results demonstrated a significant improvement in adherence from baseline to postintervention. Study retention was 100%. This study demonstrates that a multicomponent medical and behavioral interventional program delivered by VBT to a school-based setting is feasible and can significantly improve asthma outcomes and care in a challenging population.

Identifying Modifiable Health Care Barriers to Improve Health Equity for Hospitalized Children

BACKGROUND

Children from socially disadvantaged families experience worse hospital outcomes compared with other children. We sought to identify modifiable barriers to care to target for intervention.

METHODS

We conducted a prospective cohort study of hospitalized children over 15 months. Caregivers completed a survey within 3 days of admission and 2 to 8 weeks after discharge to assess 10 reported barriers to care related to their interactions within the health care system (eg, not feeling like they have sufficient skills to navigate the system and experiencing marginalization). Associations between barriers and outcomes (30-day readmissions and length of stay) were assessed by using multivariable regression. Barriers associated with worse outcomes were then tested for associations with a cumulative social disadvantage score based on 5 family sociodemographic characteristics (eg, low income).

RESULTS

Of eligible families, 61% (n = 3651) completed the admission survey; of those, 48% (n = 1734) completed follow-up. Nine of 10 barriers were associated with at least 1 worse hospital outcome. Of those, 4 were also positively associated with cumulative social disadvantage: perceiving the system as a barrier (adjusted β = 1.66; 95% confidence interval [CI] 1.02 to 2.30), skill barriers (β = 3.82; 95% CI 3.22 to 4.43), cultural distance (β = 1.75; 95% CI 1.36 to 2.15), and marginalization (β = .71; 95% CI 0.30 to 1.11). Low income had the most consistently strong association with reported barriers.

CONCLUSIONS

System barriers, skill barriers, cultural distance, and marginalization were significantly associated with both worse hospital outcomes and social disadvantage, suggesting these are promising targets for intervention to decrease disparities for hospitalized children.

Severe Asthma in Childhood

Severe asthma is broadly defined as asthma requiring a high level of therapy, usually high doses of inhaled corticosteroids, to bring under control. Children who remain symptomatic despite such treatment are a heterogeneous population, and bear a high burden of disease and require high resource utilization. Children with severe asthma require a comprehensive evaluation, careful consideration of alternative diagnoses and comorbid conditions, assessment of medication adherence and environmental conditions, and frequent disease monitoring.

Comparison of Factors Identified by Patients and Physicians Associated with Hospital Readmission (COMPARE2)

OBJECTIVE

Factors contributing to hospital readmission have rarely been sought from the patient perspective. Furthermore, it is unclear how patients and physicians compare in identifying factors contributing to readmission. The objective of the study was to identify and compare factors contributing to hospital readmission identified by patients and physicians by surveying participants upon hospital readmission to a teaching medicine service.

METHODS

Patients 18 years and older who were discharged and readmitted to the same service within 30 days and the physicians caring for these patients were surveyed to identify factors contributing to readmission. Secondary outcomes included comparing responses between groups and determining level of agreement. Patients could be surveyed multiple times on subsequent readmissions; physicians could be surveyed for multiple patients.

RESULTS

A total of 131 patients and 37 physicians were consented. The mean patient age was 60.1 years (standard deviation 16.8 years) and 55.6% were female; 56.4% were white, and 42.1% were black/African American. In total, 179 patient surveys identified "multiple medical problems" (48.6%), "trouble completing daily activities" (45.8%), and "discharged too soon" (43.6%) most frequently as contributing factors; 231 physician surveys identified "multiple medical problems" (45.0%) and "medical condition too difficult to care for at home" (35.6%) most frequently as contributing factors. Paired survey results were available for 135 readmissions and showed fair agreement for only 1 factor but no agreement for 5 factors.

CONCLUSIONS

Patients identified previously unknown factors contributing to readmission. Little agreement existed between patients and physicians. Additional research is needed to determine how best to address patient-identified factors contributing to readmission.

Achievable Benchmarks of Care for Pediatric Readmissions

BACKGROUND

Most inpatient care for children occurs outside tertiary children's hospitals, yet these facilities often dictate quality metrics. Our objective was to calculate the mean readmission rates and the Achievable Benchmarks of Care (ABCs) for pediatric diagnoses by different hospital types: metropolitan teaching, metropolitan nonteaching, and nonmetropolitan hospitals.

METHODS

We used a cross-sectional retrospective study of 30-day, all-cause, same-hospital readmission of patients less than 18 years old using the 2014 Healthcare Utilization Project National Readmission Database. For each hospital type, we calculated the mean readmission rates and corresponding ABCs for the 17 most common readmission diagnoses. We define outlier as any hospital whose readmission rate fell outside the 95% CI for an ABC within their hospital type.

RESULTS

We analyzed 690,949 discharges at 525 metropolitan teaching hospitals (550,039 discharges), 552 metropolitan nonteaching hospitals (97,207 discharges), and 587 nonmetropolitan hospitals (43,703 discharges). Variation in readmission rates existed among hospital types; however, sickle cell disease (SCD) had the highest readmission rate and ABC across all hospital types: metropolitan teaching hospitals 15.7% (ABC 7.0%), metropolitan nonteaching 14.7% (ABC 2.6%), and nonmetropolitan 12.8% (ABC not calculated). For diagnoses in which ABCs were available, outliers were prominent in bipolar disorders, major depressive disorders, and SCD.

CONCLUSIONS

ABCs based on hospital type may serve as a better metric to explain case-mix variation among different hospital types in pediatric inpatient care. The mean rates and ABCs for SCD and mental health disorders were much higher and with more outlier hospitals, which indicate high-value targets for quality improvement.

Neighborhood Risk and Hospital Use for Pediatric Asthma, Rhode Island, 2005-2014

INTRODUCTION

Studies consistently show that children living in poor neighborhoods have worse asthma outcomes. The objective of our study was to assess the association between negative neighborhood factors (ie, neighborhood risk) and pediatric asthma hospital use.

METHODS

This retrospective study used data from children aged 2 to 17 years in a statewide (Rhode Island) hospital network administrative database linked to US Census Bureau data. We defined an asthma visit as an International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code of 493 in any diagnosis field. We used 8 highly correlated measures for each census-block group to construct an index of neighborhood risk. We used maps and linear regression to assess the association of neighborhood risk with average annual census-block-group rates of asthma emergency department visits and hospitalizations. We used multivariable analyses to identify child characteristics and neighborhood risk associated with an asthma revisit, accounting for the child's sociodemographic information, season, and multiple measurements per child.

RESULTS

From 2005 through 2014, we counted 359,195 visits for 146,889 children. Of these, 12,699 children (8.6%) had one or more asthma visits. Linear regression results showed 1.18 (95% confidence interval, 1.06-1.30) more average annual emergency departments visits per 100 children and 0.41 (95% confidence interval, 0.34-0.47) more average annual hospitalizations per 100 children in neighborhoods in the highest-risk index quintile than in neighborhoods in the lowest-risk index quintile.

CONCLUSION

Interventions to improve asthma outcomes among children should move beyond primary care or clinic settings and involve a careful evaluation of social context and environmental triggers.

Socioeconomic Characteristics of Neighborhoods where Youth in Out-of-Home Care Reside

In the U.S., little is known about the neighborhoods where youth in out-of-home care live prior to emancipation. This study describes the socioeconomic characteristics of such neighborhoods. Addresses for 229 youth aged 16-20 years and residing in out-of-home care in a single Midwest county were used. Addresses were geocoded and linked to U.S. Census' data at the census tract level. Neighborhoods, or tracts, with youth in out-of-home care were significantly more disadvantaged across five area-based socioeconomic indicators. Findings suggest that youth in out-of-home care live in neighborhoods with disproportionately high rates of socioeconomic disadvantage.

Health Disparities in the Hospitalized Child

Health care disparities exist along the continuum of care for children admitted to the hospital; they start before admission, impact hospital course, and continue after discharge. During an acute illness, risk of admission, length of stay, hospital costs, communication during family-centered rounds, and risk of readmission have all been shown to vary by socioeconomic status, race, and ethnicity. Understanding factors beyond the acute illness that increase a child's risk of admission, increase hospital course complications, and lower discharge quality is imperative for the new generation of pediatric hospitalists focused on improving health for a population of children. In this article, we describe a framework to conceptualize socioeconomic, racial, and ethnic health disparities for the hospitalized child. Additionally, we offer actions pediatric hospitalists can take to address disparities within their practices.

Pervasive Income-Based Disparities In Inpatient Bed-Day Rates Across Conditions And Subspecialties

Building a culture of health in hospitals means more than participating in community partnerships. It also requires an enhanced capacity to recognize and respond to disparities in utilization patterns across populations. We identified all pediatric hospitalizations at Cincinnati Children's Hospital Medical Center, in the period 2011-16. Each hospitalized child's address was geocoded, allowing us to calculate inpatient bed-day rates for each census tract in Hamilton County, Ohio, across all causes and for specific conditions and pediatric subspecialties. We then divided the census tracts into quintiles based on their underlying rates of child poverty and calculated bed-day rates per quintile. Poorer communities disproportionately bore the burden of pediatric hospital days. If children from all of the county's census tracts spent the same amount of time in the hospital each year as those from the most affluent tracts, approximately twenty-two child-years of hospitalization time would be prevented. Of particular note were "hot spots" in high-poverty census tracts neighboring the hospital, where bed-day rates were more than double the county average. Hospitals that address disparities would benefit from a more comprehensive understanding of the culture of health-a culture that is more cohesive inside the hospital and builds bridges into the community.

The Use of Geographic Data to Improve Asthma Care Delivery and Population Health

The authors examine uses of geographic data to improve asthma care delivery and population health and describe potential practice changes and areas for future research.

Predictors of repeated acute hospital attendance for asthma in children: A systematic review and meta-analysis

BACKGROUND

Asthma attacks are common and have significant physical, psychological, and financial consequences. Improving the assessment of a child's risk of subsequent asthma attacks could support front-line clinicians' decisions on augmenting chronic treatment or specialist referral. We aimed to identify predictors for emergency department (ED) or hospital readmission for asthma from the published literature.

METHODS

We searched MEDLINE, EMBASE, AMED, PsycINFO, and CINAHL with no language, location, or time restrictions. We retrieved observational studies and randomized controlled trials (RCT) assessing factors (personal and family history, and biomarkers) associated with the risk of ED re-attendance or hospital readmission for acute childhood asthma.

RESULTS

Three RCTs and 33 observational studies were included, 31 from Anglophone countries and none from Asia or Africa. There was an unclear or high risk of bias in 14 of the studies, including 2 of the RCTs. Previous history of emergency or hospital admissions for asthma, younger age, African-American ethnicity, and low socioeconomic status increased risk of subsequent ED and hospital readmissions for acute asthma. Female sex and concomitant allergic diseases also predicted hospital readmission.

CONCLUSION

Despite the global importance of this issue, there are relatively few high quality studies or studies from outside North America. Factors other than symptoms are associated with the risk of emergency re-attendance for acute asthma among children. Further research is required to better quantify the risk of future attacks and to assess the role of commonly used biomarkers.

Mapping Neighborhood Health Geomarkers To Clinical Care Decisions To Promote Equity In Child Health

Health disparities, which can be understood as disadvantages in health associated with one's social, racial, economic, or physical environment, originate in childhood and persist across an individual's life course. One's neighborhood may drive or influence these disparities. Information on neighborhoods that can characterize their risks-what we call place-based risks-is rarely used in patient care. Community-level data, however, could inform and personalize interventions such as arranging for mold removal from the home of a person with asthma from the moment that person's address is recorded at the site of care. Efficient risk identification could lead to the tailoring of recommendations and targeting of resources, to improve care experiences and clinical outcomes while reducing disparities and costs. In this article we highlight how data on place-based social determinants of health from national and local sources could be incorporated more directly into patient-centered care, adding precision to risk assessment and mitigation. We also discuss how this information could stimulate cross-sector interventions that promote health equity: the attainment of the highest level of health for neighborhoods, patient panels, and individuals. Finally, we draw attention to research questions that focus on the role of geographical place at the bedside.

Neighborhood Child Opportunity and Individual-Level Pediatric Acute Care Use and Diagnoses

: media-1vid110.1542/5751513300001PEDS-VA_2017-2309Video Abstract OBJECTIVES: Although health care providers and systems are increasingly interested in patients' nonmedical needs as a means to improve health, little is known about neighborhood conditions that contribute to child health problems. We sought to determine if a novel, publicly available measure of neighborhood context, the Child Opportunity Index, was associated with pediatric acute care visit frequency and diagnoses.

METHODS

This cross-sectional study included San Francisco residents <18 years of age with an emergency department and/or urgent care visit to any of 3 medical systems (N = 47 175) between 2007 and 2011. Hot-spot analysis was used to compare the spatial distribution of neighborhood child opportunity and income. Generalized estimating equation logistic regression models were used to examine independent associations between neighborhood child opportunity and frequent acute care use (≥4 visits per year) and diagnosis group after adjusting for neighborhood income and patient age, sex, race and/or ethnicity, payer, and health system.

RESULTS

Neighborhood child opportunity and income had distinct spatial distributions, and we identified different clusters of high- and low-risk neighborhoods. Children living in the lowest opportunity neighborhoods had significantly greater odds of ≥4 acute care visits per year (odds ratio 1.33; 95% confidence interval 1.03-1.73) compared with those in the highest opportunity neighborhoods. Neighborhood child opportunity was negatively associated with visits for respiratory conditions, asthma, assault, and ambulatory care-sensitive conditions but positively associated with injury-related visits.

CONCLUSIONS

The Child Opportunity Index could be an effective tool for identifying neighborhood factors beyond income related to child health.

Neighborhood Deprivation and Childhood Asthma Outcomes, Accounting for Insurance Coverage

OBJECTIVES

Collecting social determinants data is challenging. We assigned patients a neighborhood-level social determinant measure, the area of deprivation index (ADI), by using census data. We then assessed the association between neighborhood deprivation and asthma hospitalization outcomes and tested the influence of insurance coverage.

METHODS

A retrospective cohort study of children 2 to 17 years old admitted for asthma at 8 hospitals. An administrative database was used to collect patient data, including hospitalization outcomes and neighborhood deprivation status (ADI scores), which were grouped into quintiles (ADI 1, the least deprived neighborhoods; ADI 5, the most deprived neighborhoods). We used multivariable models, adjusting for covariates, to assess the associations and added a neighborhood deprivation status and insurance coverage interaction term.

RESULTS

A total of 2270 children (median age 5 years; 40.6% girls) were admitted for asthma. We noted that higher ADI quintiles were associated with greater length of stay, higher cost, and more asthma readmissions (P < .05 for most quintiles). Having public insurance was independently associated with greater length of stay (β: 1.171; 95% confidence interval [CI]: 1.117-1.228; P < .001), higher cost (β: 1.147; 95% CI: 1.093-1.203; P < .001), and higher readmission odds (odds ratio: 1.81; 95% CI: 1.46-2.24; P < .001). There was a significant deprivation-insurance effect modification, with public insurance associated with worse outcomes and private insurance with better outcomes across ADI quintiles (P < .05 for most combinations).

CONCLUSIONS

Neighborhood-level ADI measure is associated with asthma hospitalization outcomes. However, insurance coverage modifies this relationship and needs to be considered when using the ADI to identify and address health care disparities.

The Child Opportunity Index and Disparities in Pediatric Asthma Hospitalizations Across One Ohio Metropolitan Area, 2011-2013

OBJECTIVES

To determine whether the Child Opportunity Index (COI), a nationally available measure of relative educational, health/environmental, and social/economic opportunity across census tracts within metropolitan areas, is associated with population- and patient-level asthma morbidity.

STUDY DESIGN

This population-based retrospective cohort study was conducted between 2011 and 2013 in a southwest Ohio county. Participants included all children aged 1-16 years with hospitalizations or emergency department visits for asthma or wheezing at a major pediatric hospital. Patients were identified using discharge diagnosis codes and geocoded to their home census tract. The primary population-level outcome was census tract asthma hospitalization rate. The primary patient-level outcome was rehospitalization within 12 months of the index hospitalization. Census tract opportunity was characterized using the COI and its educational, health/environmental, and social/economic domains.

RESULTS

Across 222 in-county census tracts, there were 2539 geocoded hospitalizations. The median asthma-related hospitalization rate was 5.0 per 1000 children per year (IQR, 1.9-8.9). Median hospitalization rates in very low, low, moderate, high, and very high opportunity tracts were 9.1, 7.6, 4.6, 2.1, and 1.8 per 1000, respectively (P < .0001). The social/economic domain had the most variables significantly associated with the outcome at the population level. The adjusted patient-level analyses showed that the COI was not significantly associated with a patient's risk of rehospitalization within 12 months.

CONCLUSIONS

The COI was associated with population-level asthma morbidity. The details provided by the COI may inform interventions aimed at increasing opportunity and reducing morbidity across regions.

Socioeconomic Background and Commercial Health Plan Spending

BACKGROUND

Risk-adjustment algorithms typically incorporate demographic and clinical variables to equalize compensation to insurers for enrollees who vary in expected cost, but including information about enrollees' socioeconomic background is controversial.

METHODS

We studied 1 182 847 continuously insured 0 to 19-year-olds using 2008-2012 Blue Cross Blue Shield of Massachusetts and American Community Survey data. We characterized enrollees' socioeconomic background using the validated area-based socioeconomic measure and calculated annual plan payments using paid claims. We evaluated the relationship between annual plan payments and geocoded socioeconomic background using generalized estimating equations (γ distribution and log link). We expressed outcomes as the percentage difference in spending and utilization between enrollees with high and low socioeconomic backgrounds.

RESULTS

Geocoded socioeconomic background had a significant, positive association with annual plan payments after applying standard adjusters. Every 1 SD increase in socioeconomic background was associated with a 7.8% (95% confidence interval, 7.2% to 8.3%; P < .001) increase in spending. High socioeconomic background enrollees used higher-priced outpatient and pharmacy services more frequently than their counterparts from low socioeconomic backgrounds (eg, 25% more outpatient encounters annually; 8% higher price per encounter; P < .001), which outweighed greater emergency department spending among low socioeconomic background enrollees.

CONCLUSIONS

Higher socioeconomic background is associated with greater levels of pediatric health care spending in commercially insured children. Including socioeconomic information in risk-adjustment algorithms may address concerns about adverse selection from an economic perspective, but it would direct funds away from those caring for children and adolescents from lower socioeconomic backgrounds who are at greater risk of poor health.

National estimates of 30-day readmissions among children hospitalized for asthma in the United States

OBJECTIVE

Previous single-center studies have reported that up to 40% of children hospitalized for asthma will be readmitted. The study objectives are to investigate the prevalence and timing of 30-day readmissions in children hospitalized with asthma, and to identify factors associated with 30-day readmissions.

METHODS

Data (n = 12,842) for children aged 6-18 years hospitalized for asthma were obtained from the 2013 Nationwide Readmission Database (NRD). The primary study outcome was time to readmission within 30 days after discharge attributable to any cause. Several predictors associated with the risk of admission were included: patient (age, sex, median household income, insurance type, county location, and pediatric chronic complex condition), admission (type, day, emergency services utilization, length of stay (LOS), and discharge disposition), and hospital (ownership, bed size, and teaching status). Cox's proportional hazards model was used to identify predictors.

RESULTS

Of 12,842 asthma-related index hospitalizations, 2.5% were readmitted within 30-days post-discharge. Time to event models identified significantly higher risk of readmission among asthmatic children aged 12-18 years, those who resided in micropolitan counties, those with >4-days LOS during index hospitalization, those who were hospitalized in an urban hospital, who had unfavorable discharge (hazard ratio 2.53, 95% confidence interval 1.33-4.79), and those who were diagnosed with a pediatric complex chronic condition, respectively, than children in respective referent categories.

CONCLUSION

A multi-dimensional approach including effective asthma discharge action plans and follow-up processes, home-based asthma education, and neighborhood/community-level efforts to address disparities should be integrated into the routine clinical care of asthma children.

Using Address Information to Identify Hardships Reported by Families of Children Hospitalized With Asthma

OBJECTIVE

Socioeconomic hardship is common among children hospitalized for asthma but often not practically measurable. Information on where a child resides is universally available. We sought to determine the correlation between neighborhood-level socioeconomic data and family-reported hardships.

METHODS

Caregivers of 774 children hospitalized with asthma answered questions regarding income, financial strain, and primary care access. Addresses were geocoded and linked to zip code-, census tract-, and block group-level (neighborhood) data from the US Census. We then compared neighborhood median household income with family-reported household income; percentage of neighborhood residents living in poverty with family-reported financial strain; and percentage of neighborhood households without an available vehicle with family-reported access to primary care. We constructed heat maps and quantified correlations using Kendall rank correlation coefficient. Receiver operator characteristic curves were used to assess predictive abilities of neighborhood measures.

RESULTS

The cohort was 57% African American and 73% publicly-insured; 63% reported income <$30,000, 32% endorsed ≥4 financial strain measures, and 38% reported less than adequate primary care access. Neighborhood median household income was significantly and moderately correlated with and predictive of reported household income; neighborhood poverty was similarly related to financial strain; neighborhood vehicle availability was weakly correlated with and predictive of primary care access. Correlations and predictions provided by zip code measures were similar to those of census tract and block group.

CONCLUSIONS

Universally available neighborhood information might help efficiently identify children and families with socioeconomic hardships. Systematic screening with area-level socioeconomic measures has the potential to inform resource allocation more efficiently.

San Francisco children living in redeveloped public housing used acute services less than children in older public housing

Understanding the links between housing and health is increasingly important. Poor housing quality is a predictor of poor health and developmental problems in low-income children. We examined associations between public housing type and recurrent pediatric emergency and urgent care hospital visits. Children ages 0-18 with public insurance who sought emergency care from any of three large medical systems in San Francisco were categorized by whether they lived in public housing redeveloped through the federal HOPE VI program, nonredeveloped public housing, or nonpublic housing in a census tract that also contained public housing. After we adjusted for potential confounding characteristics, we found that children living in nonredeveloped public housing were 39 percent more likely to have one or more repeat visits within one year for acute health care services unrelated to the initial visit, compared to children who lived in redeveloped HOPE VI housing. We observed no differences in repeat visits between children in redeveloped HOPE VI housing and those in nonpublic housing. These findings support the continued redevelopment of public housing as a means of both improving the health of vulnerable high-risk children from low-income neighborhoods and reducing health care costs.

Housing code violation density associated with emergency department and hospital use by children with asthma

Local agencies that enforce housing policies can partner with the health care system to target pediatric asthma care. These agencies retain data that can be used to pinpoint potential clusters of high asthma morbidity. We sought to assess whether the density of housing code violations in census tracts-the in-tract asthma-relevant violations (such as the presence of mold or cockroaches) divided by the number of housing units-was associated with population-level asthma morbidity and could be used to predict a hospitalized patient's risk of subsequent morbidity. We found that increased density in housing code violations was associated with population-level morbidity independent of poverty, and that the density explained 22 percent of the variation in rates of asthma-related emergency department visits and hospitalizations. Children who had been hospitalized for asthma had 1.84 greater odds of a revisit to the emergency department or a rehospitalization within twelve months if they lived in the highest quartile of housing code violation tracts, compared to those living in the lowest quartile. Integrating housing and health data could highlight at-risk areas and patients for targeted interventions.

Socioeconomic status influences the toll paediatric hospitalisations take on families: a qualitative study

BACKGROUND

Stress caused by hospitalisations and transition periods can place patients at a heightened risk for adverse health outcomes. Additionally, hospitalisations and transitions to home may be experienced in different ways by families with different resources and support systems. Such differences may perpetuate postdischarge disparities.

OBJECTIVE

We sought to determine, qualitatively, how the hospitalisation and transition experiences differed among families of varying socioeconomic status (SES).

METHODS

Focus groups and individual interviews were held with caregivers of children recently discharged from a children's hospital. Sessions were stratified based on SES, determined by the percentage of individuals living below the federal poverty level in the census tract or neighbourhood in which the family lived. An open-ended, semistructured question guide was developed to assess the family's experience. Responses were systematically compared across two SES strata (tract poverty rate of <15% or ≥15%).

RESULTS

A total of 61 caregivers who were 87% female and 46% non-white participated; 56% resided in census tracts with ≥15% of residents living in poverty (ie, low SES). Interrelated logistical (eg, disruption in-home life, ability to adhere to discharge instructions), emotional (eg, overwhelming and exhausting nature of the experience) and financial (eg, cost of transportation and meals, missed work) themes were identified. These themes, which were seen as key to the hospitalisation and transition experiences, were emphasised and described in qualitatively different ways across SES strata.

CONCLUSIONS

Families of lower SES may experience challenges and stress from hospitalisations and transitions in different ways than those of higher SES. Care delivery models and discharge planning that account for such challenges could facilitate smoother transitions that prevent adverse events and reduce disparities in the postdischarge period.

TRIAL REGISTRATION NUMBER

NCT02081846; Pre-results.

Areas with High Rates of Police-Reported Violent Crime Have Higher Rates of Childhood Asthma Morbidity

OBJECTIVES

To assess whether population-level violent (and all) crime rates were associated with population-level child asthma utilization rates and predictive of patient-level risk of asthma reutilization after a hospitalization.

STUDY DESIGN

A retrospective cohort study of 4638 pediatric asthma-related emergency department visits and hospitalizations between 2011 and 2013 was completed. For population-level analyses, census tract asthma utilization rates were calculated by dividing the number of utilization events within a tract by the child population. For patient-level analyses, hospitalized patients (n = 981) were followed until time of first asthma-related reutilization. The primary predictor was the census tract rate of violent crime as recorded by the police; the all crime (violent plus nonviolent) rate was also assessed.

RESULTS

Census tract-level violent and all crime rates were significantly correlated with asthma utilization rates (both P < .0001). The violent crime rate explained 35% of the population-level asthma utilization variance and remained associated with increased utilization after adjustment for census tract poverty, unemployment, substandard housing, and traffic exposure (P = .002). The all crime rate explained 28% of the variance and was similarly associated with increased utilization after adjustment (P = .02). Hospitalized children trended toward being more likely to reutilize if they lived in higher violent (P = .1) and all crime areas (P = .01). After adjustment, neither relationship was significant.

CONCLUSIONS

Crime data could help facilitate early identification of potentially toxic stressors relevant to the control of asthma for populations and patients.

Will they participate? Predicting patients' response to clinical trial invitations in a pediatric emergency department

Objective (1) To develop an automated algorithm to predict a patient’s response (ie, if the patient agrees or declines) before he/she is approached for a clinical trial invitation; (2) to assess the algorithm performance and the predictors on real-world patient recruitment data for a diverse set of clinical trials in a pediatric emergency department; and (3) to identify directions for future studies in predicting patients’ participation response.

Materials and Methods We collected 3345 patients’ response to trial invitations on 18 clinical trials at one center that were actively enrolling patients between January 1, 2010 and December 31, 2012. In parallel, we retrospectively extracted demographic, socioeconomic, and clinical predictors from multiple sources to represent the patients’ profiles. Leveraging machine learning methodology, the automated algorithms predicted participation response for individual patients and identified influential features associated with their decision-making. The performance was validated on the collection of actual patient response, where precision, recall, F-measure, and area under the ROC curve were assessed.

Results Compared to the random response predictor that simulated the current practice, the machine learning algorithms achieved significantly better performance (Precision/Recall/F-measure/area under the ROC curve: 70.82%/92.02%/80.04%/72.78% on 10-fold cross validation and 71.52%/92.68%/80.74%/75.74% on the test set). By analyzing the significant features output by the algorithms, the study confirmed several literature findings and identified challenges that could be mitigated to optimize recruitment.

Conclusion By exploiting predictive variables from multiple sources, we demonstrated that machine learning algorithms have great potential in improving the effectiveness of the recruitment process by automatically predicting patients’ participation response to trial invitations.

Area-Level Socioeconomic Factors Are Associated With Noncompletion of Pediatric Preventive Services

We examined 4872 infants born consecutively, 2011-2012, and seen at 3 primary care centers to determine whether area-based socioeconomic measures were associated with noncompletion of common preventive services within the first 15 months. Addresses were geocoded and linked to census tract poverty, adult educational attainment, and household vehicle ownership rates. The quartile of patients in the highest poverty (adjusted odds ratio [aOR] 1.25; 95% confidence interval [CI] 1.01-1.54) and lowest vehicle ownership tracts (aOR 1.32; 95% CI 1.07-1.63) had significantly increased odds of service noncompletion. There were significant spatial clusters of low completion in Cincinnati's urban core. These findings have implications for preventive service delivery.