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

Development of a multimodal geomarker pipeline to assess the impact of social, economic, and environmental factors on pediatric health outcomes

OBJECTIVES

We sought to create a computational pipeline for attaching geomarkers, contextual or geographic measures that influence or predict health, to electronic health records at scale, including developing a tool for matching addresses to parcels to assess the impact of housing characteristics on pediatric health.

MATERIALS AND METHODS

We created a geomarker pipeline to link residential addresses from hospital admissions at Cincinnati Children's Hospital Medical Center (CCHMC) between July 2016 and June 2022 to place-based data. Linkage methods included by date of admission, geocoding to census tract, street range geocoding, and probabilistic address matching. We assessed 4 methods for probabilistic address matching.

RESULTS

We characterized 124 244 hospitalizations experienced by 69 842 children admitted to CCHMC. Of the 55 684 hospitalizations with residential addresses in Hamilton County, Ohio, all were matched to 7 temporal geomarkers, 97% were matched to 79 census tract-level geomarkers and 13 point-level geomarkers, and 75% were matched to 16 parcel-level geomarkers. Parcel-level geomarkers were linked using our exact address matching tool developed using the best-performing linkage method.

DISCUSSION

Our multimodal geomarker pipeline provides a reproducible framework for attaching place-based data to health data while maintaining data privacy. This framework can be applied to other populations and in other regions. We also created a tool for address matching that democratizes parcel-level data to advance precision population health efforts.

CONCLUSION

We created an open framework for multimodal geomarker assessment by harmonizing and linking a set of over 100 geomarkers to hospitalization data, enabling assessment of links between geomarkers and hospital admissions.

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.

Combining zip code-based population data and pharmacy administrative claims data to create measures of social determinants of health

BACKGROUND

Social determinants of health (SDoH) are key factors that impact health outcomes. However, there are many barriers to collecting SDoH data (eg, cost of data collection, technological barriers, and lack of standardized measures). Population data may provide an accessible alternative to collecting SDoH data for patients.

OBJECTIVE

To explain how population data can be leveraged to create SDoH measures, assess the association of population SDoH measures with diabetic medication adherence, and discuss how understanding a patient's SDoH can inform care plans and patient engagement.

METHODS

A nationally representative commercial sample of patients who were aged 18 years and older and met Pharmacy Quality Alliance inclusion criteria for diabetes mellitus were analyzed (N = 37,789). US Census and North American Industry Classification System data were combined with pharmacy administrative claims data to create SDoH measures. Derived measures represent 2 SDoH domains: (1) economic stability (housing density, housing relocation, jobs per resident, and average salary) and (2) health care access and quality (urban/rural classification, distance traveled to prescriber and pharmacy, use of a primary care provider [PCP], and residents per PCP). The association of population SDoH measures with diabetic medication adherence (proportion of days covered) was assessed via logistic regression, which included covariates (eg, sex, age, comorbidities, and prescription plan attributes).

RESULTS

As housing density (houses per resident) increased, so did the likelihood of adherence (odds ratio = 1.54, 95% CI = 1.21-1.97, P = 0.001). Relative to patients who did not move, patients who moved once had 0.87 (95% CI = 0.81-0.93, P < 0.001) the odds of being adherent, and patients who moved 2 or more times had 0.82 (95% CI = 0.71-0.95, P = 0.008) the odds of being adherent. Compared with areas with fewer jobs per resident, patients living within a zip code with 0.16 to 0.26 jobs per resident were 1.12 (95% CI = 1.04-1.20, P = 0.002) times more likely to be adherent. Patients who lived in an urban cluster were 1.11 (95% CI = 1.01-1.22, P = 0.037) times more likely to be adherent than patients living in a rural area. Patients who travel at least 25 miles to their prescriber had 0.82 (95% CI = 0.77-0.86, P < 0.001) the odds of being adherent. Community pharmacy users had 0.65 (95% CI = 0.59-0.71, P < 0.001) the odds of being adherent compared with mail order pharmacy users. Patients who had a PCP were 1.26 (95% CI = 1.18-1.34, P < 0.001) times more likely to be adherent to their medication.

CONCLUSIONS

Leveraging publicly available population data to create SDoH measures is an accessible option to overcome barriers to SDoH data collection. Derived measures can be used to increase equity in care received by identifying patients who could benefit from assistance with medication adherence.

Garnering effective telehealth to help optimize multidisciplinary team engagement (GET2HOME) for children with medical complexity: Protocol for a pragmatic randomized control trial

BACKGROUND

Children and young adults with medical complexity (CMC) experience high rates of healthcare reutilization following hospital discharge. Prior studies have identified common hospital-to-home transition failures that may increase the risk for reutilization, including medication, technology and equipment issues, financial concerns, and confusion about which providers can help with posthospitalization needs. Few interventions have been developed and evaluated for CMC during this transition period.

OBJECTIVE

We will compare the effectiveness of the garnering effective telehealth 2 help optimize multidisciplinary team engagement (GET2HOME) transition bundle intervention to the standard hospital-based care coordination discharge process by assessing healthcare reutilization and patient- and family-centered outcomes.

DESIGNS, SETTINGS, AND PARTICIPANTS

We will conduct a pragmatic 2-arm randomized controlled trial (RCT) comparing the GET2HOME bundle intervention to the standard hospital-based care discharge process on CMC hospitalized and discharged from hospital medicine at two sites of our pediatric medical center between November 2022 and February 2025. CMC of any age will be identified as having complex chronic disease using the Pediatric Medical Complexity Algorithm tool. We will exclude CMC who live independently, live in skilled nursing facilities, are in custody of the county, or are hospitalized for suicidal ideation or end-of-life care.

INTERVENTION

We will randomize participants to the bundle intervention or standard hospital-based care coordination discharge process. The bundle intervention includes (1) predischarge telehealth huddle with inpatient providers, outpatient providers, patients, and their families; (2) care management discharge task tracker; and (3) postdischarge telehealth huddle with similar participants within 7 days of discharge. As part of the pragmatic design, families will choose if they want to complete the postdischarge huddle. The standard hospital-based discharge process includes a pharmacist, social worker, and care management support when consulted by the inpatient team but does not include huddles between providers and families.

MAIN OUTCOME AND MEASURES

Primary outcome will be 30-day urgent healthcare reutilization (unplanned readmission, emergency department, and urgent care visits). Secondary outcomes include 7-day urgent healthcare reutilization, patient- and family-reported transition quality, quality of life, and time to return to baseline using electronic health record and surveys at 7, 30, 60, and 90 days following discharge. We will also evaluate heterogeneity of treatment effect for the intervention across levels of financial strain and for CMC with high-intensity neurologic impairment. The primary analysis will follow the intention-to-treat principle with logistic regression used to study reutilization outcomes and generalized linear mixed modeling to study repeated measures of patient- and family-reported outcomes over time.

RESULTS

This pragmatic RCT is designed to evaluate the effectiveness of enhanced discharge transition support, including telehealth huddles and a care management discharge tool, for CMC and their families. Enrollment began in November 2022 and is projected to complete in February 2025. Primary analysis completion is anticipated in July 2025 with reporting of results following.

Population-level SDOH and Pediatric Asthma Health Care Utilization: A Systematic Review

CONTEXT

Spatial analysis is a population health methodology that can determine geographic distributions of asthma outcomes and examine their relationship to place-based social determinants of health (SDOH).

OBJECTIVES

To systematically review US-based studies analyzing associations between SDOH and asthma health care utilization by geographic entities.

DATA SOURCES

Pubmed, Medline, Web of Science, Scopus, and Cumulative Index to Nursing and Allied Health Literature.

STUDY SELECTION

Empirical, observational US-based studies were included if (1) outcomes included asthma-related emergency department visits or revisits, and hospitalizations or rehospitalizations; (2) exposures were ≥1 SDOH described by the Healthy People (HP) SDOH framework; (3) analysis occurred at the population-level using a geographic entity (eg, census-tract); (4) results were reported separately for children ≤18 years.

DATA EXTRACTION

Two reviewers collected data on study information, demographics, geographic entities, SDOH exposures, and asthma outcomes. We used the HP SDOH framework's 5 domains to organize and synthesize study findings.

RESULTS

The initial search identified 815 studies; 40 met inclusion criteria. Zip-code tabulation areas (n = 16) and census-tracts (n = 9) were frequently used geographic entities. Ten SDOH were evaluated across all HP domains. Most studies (n = 37) found significant associations between ≥1 SDOH and asthma health care utilization. Poverty and environmental conditions were the most often studied SDOH. Eight SDOH-poverty, higher education enrollment, health care access, primary care access, discrimination, environmental conditions, housing quality, and crime - had consistent significant associations with asthma health care utilization.

CONCLUSIONS

Population-level SDOH are associated with asthma health care utilization when evaluated by geographic entities. Future work using similar methodology may improve this research's quality and utility.

Gene-environment interactions and their impact on human health

The molecular processes underlying human health and disease are highly complex. Often, genetic and environmental factors contribute to a given disease or phenotype in a non-additive manner, yielding a gene-environment (G × E) interaction. In this work, we broadly review current knowledge on the impact of gene-environment interactions on human health. We first explain the independent impact of genetic variation and the environment. We next detail well-established G × E interactions that impact human health involving environmental toxicants, pollution, viruses, and sex chromosome composition. We conclude with possibilities and challenges for studying G × E interactions.

Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years

IMPORTANCE

Readmission is often considered a hospital quality measure, yet no validated risk prediction models exist for children.

OBJECTIVE

To develop and validate a tool identifying patients before hospital discharge who are at risk for subsequent readmission, applicable to all ages.

DESIGN, SETTING, AND PARTICIPANTS

This population-based prognostic analysis used electronic health record-derived data from a freestanding children's hospital from January 1, 2016, to December 31, 2019. All-cause 30-day readmission was modeled using 3 years of discharge data. Data were analyzed from June 1 to November 30, 2021.

MAIN OUTCOMES AND MEASURES

Three models were derived as a complementary suite to include (1) children 6 months or older with 1 or more prior hospitalizations within the last 6 months (recent admission model [RAM]), (2) children 6 months or older with no prior hospitalizations in the last 6 months (new admission model [NAM]), and (3) children younger than 6 months (young infant model [YIM]). Generalized mixed linear models were used for all analyses. Models were validated using an additional year of discharges.

RESULTS

The derivation set contained 29 988 patients with 48 019 hospitalizations; 50.1% of these admissions were for children younger than 5 years and 54.7% were boys. In the derivation set, 4878 of 13 490 admissions (36.2%) in the RAM cohort, 2044 of 27 531 (7.4%) in the NAM cohort, and 855 of 6998 (12.2%) in the YIM cohort were followed within 30 days by a readmission. In the RAM cohort, prior utilization, current or prior procedures indicative of severity of illness (transfusion, ventilation, or central venous catheter), commercial insurance, and prolonged length of stay (LOS) were associated with readmission. In the NAM cohort, procedures, prolonged LOS, and emergency department visit in the past 6 months were associated with readmission. In the YIM cohort, LOS, prior visits, and critical procedures were associated with readmission. The area under the receiver operating characteristics curve was 83.1 (95% CI, 82.4-83.8) for the RAM cohort, 76.1 (95% CI, 75.0-77.2) for the NAM cohort, and 80.3 (95% CI, 78.8-81.9) for the YIM cohort.

CONCLUSIONS AND RELEVANCE

In this prognostic study, the suite of 3 prediction models had acceptable to excellent discrimination for children. These models may allow future improvements in tailored discharge preparedness to prevent high-risk readmissions.

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.

Social Determinants of Health and At-Risk Rates for Pediatric Asthma Morbidity

BACKGROUND AND OBJECTIVES

Compared with population-based rates, at-risk rates (ARRs) account for underlying variations of asthma prevalence. When applied with geospatial analysis, ARRs may facilitate more accurate evaluations of the contribution of place-based social determinants of health (SDOH) to pediatric asthma morbidity. Our objectives were to calculate ARRs for pediatric asthma-related emergency department (ED) encounters and hospitalizations by census-tract in Washington, the District of Columbia (DC) and evaluate their associations with SDOH.

METHODS

This population-based, cross-sectional study identified children with asthma, 2 to 17 years old, living in DC, and included in the DC Pediatric Asthma Registry from January 2018 to December 2019. ED encounter and hospitalization ARRs (outcomes) were calculated for each DC census-tract. Five census-tract variables (exposures) were selected by using the Healthy People 2030 SDOH framework: educational attainment, vacant housing, violent crime, limited English proficiency, and families living in poverty.

RESULTS

During the study period, 4321 children had 7515 ED encounters; 1182 children had 1588 hospitalizations. ARRs varied 10-fold across census-tracts for both ED encounters (64-728 per 1000 children with asthma) and hospitalizations (20-240 per 1000 children with asthma). In adjusted analyses, decreased educational attainment was significantly associated with ARRs for ED encounters (estimate 12.1, 95% confidence interval [CI] 8.4 to 15.8, P <.001) and hospitalizations (estimate 1.2, 95% CI 0.2 to 2.2, P = .016). Violent crime was significantly associated with ARRs for ED encounters (estimate 35.3, 95% CI 10.2 to 60.4, P = .006).

CONCLUSION

Place-based interventions addressing SDOH may be an opportunity to reduce asthma morbidity among children with asthma.

Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium

Importance

In the United States, Black and Hispanic children have higher rates of asthma and asthma-related morbidity compared with White children and disproportionately reside in communities with economic deprivation.

Objective

To determine the extent to which neighborhood-level socioeconomic indicators explain racial and ethnic disparities in childhood wheezing and asthma.

Design, Setting, and Participants

The study population comprised children in birth cohorts located throughout the United States that are part of the Children's Respiratory and Environmental Workgroup consortium. Cox proportional hazard models were used to estimate hazard ratios (HRs) of asthma incidence, and logistic regression was used to estimate odds ratios of early and persistent wheeze prevalence accounting for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, and region and decade of birth.

Exposures

Neighborhood-level socioeconomic indicators defined by US census tracts calculated as z scores for multiple tract-level variables relative to the US average linked to participants' birth record address and decade of birth. The parent or caregiver reported the child's race and ethnicity.

Main Outcomes and Measures

Prevalence of early and persistent childhood wheeze and asthma incidence.

Results

Of 5809 children, 46% reported wheezing before age 2 years, and 26% reported persistent wheeze through age 11 years. Asthma prevalence by age 11 years varied by cohort, with an overall median prevalence of 25%. Black children (HR, 1.47; 95% CI, 1.26-1.73) and Hispanic children (HR, 1.29; 95% CI, 1.09-1.53) were at significantly increased risk for asthma incidence compared with White children, with onset occurring earlier in childhood. Children born in tracts with a greater proportion of low-income households, population density, and poverty had increased asthma incidence. Results for early and persistent wheeze were similar. In effect modification analysis, census variables did not significantly modify the association between race and ethnicity and risk for asthma incidence; Black and Hispanic children remained at higher risk for asthma compared with White children across census tracts socioeconomic levels.

Conclusions and Relevance

Adjusting for individual-level characteristics, we observed neighborhood socioeconomic disparities in childhood wheeze and asthma. Black and Hispanic children had more asthma in neighborhoods of all income levels. Neighborhood- and individual-level characteristics and their root causes should be considered as sources of respiratory health inequities.

Adjusting for Social Risk Factors in Pediatric Quality Measures: Adding to the Evidence Base

BACKGROUND

Outcome and utilization quality measures are adjusted for patient case-mix including demographic characteristics and comorbid conditions to allow for comparisons between hospitals and health plans. However, controversy exists around whether and how to adjust for social risk factors.

OBJECTIVE

To assess an approach to incorporating social risk variables into a pediatric measure of utilization from the Pediatric Quality Measures Program (PQMP).

METHODS

We used data from California Medicaid claims (2015-16) and Massachusetts All Payer Claims Database (2014-2015) to calculate health plan performance using measure specifications from the Pediatric Asthma Emergency Department Use measure. Health plan performance categories were assessed using mixed effect negative binomial models with and without adjustment for social risk factors, with both models adjusting for age, gender and chronic condition category. Mixed effects linear models were then used to compare patient social risk for health plans that changed performance categories to patient social risk for health plans that did not.

RESULTS

Of 133 health plans, serving 404,649 pediatric patients with asthma, 7% to 13% changed performance categories after social risk adjustment. Health plans that moved to higher performance categories cared for lower socioeconomic status (SES) patients whereas those that moved to lower performance categories cared for higher SES patients.

CONCLUSIONS

Adjustment for social risk factors changed performance rankings on the PQMP Pediatric Asthma Emergency Department Use measure for a substantial number of health plans. Some health plans caring for higher risk patients performed more poorly when social risk factors were not included in risk adjustment models. In light of this, social risk factors are incorporated into the National Quality Forum-endorsed measure; whether to incorporate social risk factors into pediatric quality measures will differ depending on the use case.

Neighborhood Socioeconomic Deprivation and Health Care Utilization of Medically Complex Children

OBJECTIVES

To assess the association between neighborhood socioeconomic deprivation and health care utilization in a cohort of children with medical complexity (CMC).

METHODS

Cross-sectional study of children aged <18 years receiving care in our institution's patient-centered medical home (PCMH) for CMC in 2016 to 2017. Home addresses were assigned to census tracts and a tract-level measure of socioeconomic deprivation (Deprivation Index with range 0-1, higher numbers represent greater deprivation). Health care utilization outcomes included emergency department visits, hospitalizations, inpatient bed days, and missed PCMH clinic appointments. To evaluate the independent association between area-level socioeconomic deprivation and utilization outcomes, multivariable Poisson and linear regression models were used to control for demographic and clinical covariates.

RESULTS

The 512 included CMC lived in neighborhoods with varying degrees of socioeconomic deprivation (median 0.32, interquartile range 0.26-0.42, full range 0.12-0.82). There was no association between area-level deprivation and emergency department visits (adjusted risk ratio [aRR] 0.98; 95% confidence interval [CI]: 0.93 to 1.04), hospitalizations (aRR 0.97; 95% CI: 0.92 to 1.01), or inpatient bed-days (aRR 1.00, 95% CI: 0.80 to 1.27). However, there was a 13% relative increase in the missed clinic visit rate for every 0.1 unit increase in Deprivation Index (95% CI: 8%-18%).

CONCLUSIONS

A child's socioeconomic context is associated with their adherence to PCMH visits. Our PCMH for CMC includes children living in neighborhoods with a range of socioeconomic deprivation and may blunt effects from harmful social determinants. Incorporating knowledge of the socioeconomic context of where CMC and their families live is crucial to ensure equitable health outcomes.

Follow-Up After Asthma Emergency Department Visits and Its Relationship With Subsequent Asthma-Related Utilization

OBJECTIVE

To assess the association between follow-up after an asthma-related emergency department (ED) visit and the likelihood of subsequent asthma-related ED utilization.

METHODS

Using data from California Medicaid (2014-2016), and Vermont (2014-2016) and Massachusetts (2013-2015) all-payer claims databases, we identified asthma-related ED visits for patients ages 3 to 21. Follow-up was defined as a visit within 14 days with a primary care provider or an asthma specialist.

OUTCOME

asthma-related ED revisit after the initial ED visit. Models included logistic regression to assess the relationship between 14-day follow-up and the outcome at 60 and 365 days, and mixed-effects negative binomial regression to assess the relationship between 14-day follow-up and repeated outcome events (# ED revisits/100 child-years). All models accounted for zip-code level clustering.

RESULTS

There were 90,267 ED visits, of which 22.6% had 14-day follow-up. Patients with follow-up were younger and more likely to have commercial insurance, complex chronic conditions, and evidence of prior asthma. 14-day follow-up was associated with decreased subsequent asthma-related ED revisits at 60 days (5.7% versus 6.4%, P < .001) and at 365 days (25.0% versus 28.3%, P < 0.001). Similarly, 14-day follow-up was associated with a decrease in the rate of repeated subsequent ED revisits (66.7 versus 77.3 revisits/100 child-years; P < 0.001).

CONCLUSIONS

We found a protective association between outpatient 14-day follow-up and asthma-related ED revisits. This may reflect improved asthma control as providers follow the NHLBI guideline stepwise approach. Our findings highlight an opportunity for improvement, with only 22.6% of those with asthma-related ED visits having 14-day follow-up.

Socioeconomic Impact on Outcomes During the First Year of Life of Patients with Single Ventricle Heart Disease: An Analysis of the National Pediatric Cardiology Quality Improvement Collaborative Registry

Socioeconomic status (SES) affects a range of health outcomes but has not been extensively explored in the single ventricle population. We investigate the impact of community-level deprivation on morbidity and mortality for infants with single ventricle heart disease in the first year of life. Retrospective cohort analysis of infants enrolled in the National Pediatric Cardiology Improvement Collaborative who underwent staged single ventricle palliation examining mortality and length of stay (LOS) using a community-level deprivation index (DI). 974 patients met inclusion criteria. Overall mortality was 20.5%, with 15.7% of deaths occurring between the first and second palliations. After adjusting for clinical risk factors, the DI was associated with death (log relative hazard [Formula: see text] = 8.92, p = 0.030) and death or transplant (log relative hazard [Formula: see text] = 8.62, p = 0.035) in a non-linear fashion, impacting those near the mean DI. Deprivation was associated with LOS following the first surgical palliation (S1P) (p = 0.031) and overall hospitalization during the first year of life (p = 0.018). For every 0.1 increase in the DI, LOS following S1P increased by 3.35 days (95% confidence interval 0.31-6.38) and total hospitalized days by 5.08 days (95% CI 0.88-9.27). Community deprivation is associated with mortality and LOS for patients with single ventricle congenital heart disease. While patients near the mean DI had a higher hazard of one year mortality compared to those at the extremes of the DI, LOS and DI were linearly associated, demonstrating the complex nature of SES factors.

The Association of the Childhood Opportunity Index on Pediatric Readmissions and Emergency Department Revisits

OBJECTIVE

Reutilization following discharge is costly to families and the health care system. Singular measures of the social determinants of health (SDOH) have been shown to impact utilization; however, the SDOH are multifactorial. The Childhood Opportunity Index (COI) is a validated approach for comprehensive estimation of the SDOH. Using the COI, we aimed to describe the association between SDOH and 30-day revisit rates.

METHODS

This retrospective study included children 0 to 17 years within 48 children's hospitals using the Pediatric Health Information System from 1/1/2019 to 12/31/2019. The main exposure was a child's ZIP code level COI. The primary outcome was unplanned readmissions and emergency department (ED) revisits within 30 days of discharge. Primary outcomes were summarized by COI category and compared using chi-square or Kruskal-Wallis tests. Adjusted analysis used generalized linear mixed effects models with adjustments for demographics, clinical characteristics, and hospital clustering.

RESULTS

Of 728,997 hospitalizations meeting inclusion criteria, 30-day unplanned returns occurred for 96,007 children (13.2%). After adjustment, the patterns of returns were significantly associated with COI. For example, 30-day returns occurred for 19.1% (95% confidence interval [CI]: 18.2, 20.0) of children living within very low opportunity areas, with a gradient-like decrease as opportunity increased (15.5%, 95% CI: 14.5, 16.5 for very high). The relative decrease in utilization as COI increased was more pronounced for ED revisits.

CONCLUSIONS

Children living in low opportunity areas had greater 30-day readmissions and ED revisits. Our results suggest that a broader approach, including policy and system-level change, is needed to effectively reduce readmissions and ED revisits.

Community Health Worker Intervention to Address Social Determinants of Health for Children Hospitalized With Asthma

BACKGROUND

Social determinants of health (SDOH) contribute to racial disparities in asthma outcomes. Community health worker (CHW) programs represent a promising way to screen for SDOH and connect patients to resources, but the impact of CHW programs in the inpatient pediatric setting has been examined in few studies. In this study, we aimed to evaluate a CHW program for children hospitalized with asthma in a predominantly Hispanic community by examining rates of SDOH and social resource navigation.

METHODS

This pilot study involved a CHW intervention to improve pediatric asthma care. Patients were included if they were hospitalized with asthma over an 18-month period and enrolled in the CHW program during their hospitalization. In an intake interview, CHWs screened caregivers for SDOH and provided tailored social resource navigation. Descriptive statistics were used to assess rates of social risk factors and social resource navigation.

RESULTS

Eighty patients underwent SDOH screening. The majority of patients were Hispanic (81.3%, n = 65). Half of caregivers reported food or housing insecurity over the past 12 months (50.0%, n = 40), and most reported inadequate housing conditions (63.8%, n = 51). CHWs coordinated social resources for the majority of families (98.8%, n = 79), with the most common being food resources (42.5%, n = 34), housing resources (82.5%, n = 66), and appointment navigation (41.3%, n = 33).

CONCLUSIONS

CHWs identified a high burden of unmet social needs and provided associated social resource navigation in a largely Hispanic pediatric population hospitalized for asthma. CHW programs have potential to improve asthma outcomes by linking high-risk patients with social resources.

Impact of a National Quality Collaborative on Pediatric Asthma Care Quality by Insurance Status

OBJECTIVE

To assess whether disparities in asthma care and outcomes based on insurance type existed before a national quality improvement (QI) collaborative, and to determine the effects of the collaborative on these disparities.

METHODS

Secondary analysis of data from Pathways for Improving Pediatric Asthma Care (PIPA), a national collaborative to standardize emergency department (ED) and inpatient asthma management. PIPA included children aged 2 to 17 with a diagnosis of asthma. Disparities were examined based on insurance status (public vs private). Outcomes included guideline adherence and health care utilization measures, assessed for 12 months before and 15 months after the start of PIPA.

RESULTS

We analyzed 19,204 ED visits and 11,119 hospitalizations from 89 sites. At baseline, children with public insurance were more likely than those with private insurance to receive early administration of corticosteroids (52.3% vs 48.9%, P= .01). However, they were more likely to be admitted (20.0% vs 19.4%, P = .01), have longer inpatient length of stay (31 vs 29 hours, P = .01), and have a readmission/ED revisit within 30 days (7.4% vs 5.6%, P = .02). We assessed the effects of PIPA on these disparities by insurance status and found no significant changes across 6 guideline adherence and 4 health care utilization measures.

CONCLUSION

At baseline, children with public insurance had higher asthma health care utilization than those with private insurance, despite receiving more evidence-based care. The PIPA collaborative did not affect pre-existing disparities in asthma outcomes. Future research should identify effective strategies for leveraging QI to better address disparities.

Barriers and Facilitators of Asthma Management as Experienced by African American Caregivers of Children with Asthma: An Integrative Review

INTRODUCTION

African American children with asthma demonstrate significant health disparities and poor health outcomes. Understanding the burdens faced by parents and caregivers of children with asthma may be helpful to develop future interventions to address this disparity.

PURPOSE

The purpose of this integrative review was to reveal the barriers and facilitators of child asthma management experienced by African American caregivers.

METHOD

Whittemore and Knafl's (2005) method of integrative review was used to review 40 articles. The integrative review involved appraising the quality of the literature, conducting a thematic analysis, and evaluating the barriers and facilitators of pediatric asthma management experienced by African American caregivers.

RESULTS

Barriers and facilitators were identified as themes. Barriers included caregiver burdens, and lack of home and neighborhood safety. Facilitators were family and community support, education and empowerment, and culturally competent healthcare providers.

DISCUSSION

To improve the care of African American children with asthma, nurses should work to engage, communicate, and foster trust with families. Nurses should assess and address the family caregivers' burdens while emphasizing support systems.

Effect of Parental Adverse Childhood Experiences and Resilience on a Child's Healthcare Reutilization

BACKGROUND

Adverse childhood experiences (ACEs) are associated with poor health outcomes in adults. Resilience may mitigate this effect. There is limited evidence regarding how parents' ACEs and resilience may be associated with their children's health outcomes.

OBJECTIVE

To determine the association of parental ACEs and resilience with their child's risk of unanticipated healthcare reutilization.

DESIGN, SETTING, AND PARTICIPANTS

We conducted a prospective cohort study (August 2015 to October 2016) at a tertiary, freestanding pediatric medical center in Cincinnati, Ohio. Eligible participants were English-speaking parents of children hospitalized on a Hospital Medicine or Complex Services team. A total of 1,320 parents of hospitalized children completed both the ACE questionnaire and the Brief Resilience Scale Survey.

EXPOSURE

Number of ACEs and Brief Resilience Scale Score among parents.

MAIN OUTCOMES

Unanticipated reutilization by children, defined as returning to the emergency room, urgent care, or being readmitted to the hospital within 30 days of hospital discharge.

RESULTS

In adjusted analyses, children of parents with 4 or more ACEs had 1.69-times higher odds (95% CI, 1.11-2.60) of unanticipated reutilization after an index hospitalization, compared with children of parents with no ACEs. Resilience was not significantly associated with reutilization.

CONCLUSION

Parental history of ACEs is strongly associated with higher odds of their child having unanticipated healthcare reutilization after a hospital discharge, highlighting an intergenerational effect. Screening may be an important tool for outcome prediction and intervention guidance following pediatric hospitalization.

Influences of environmental exposures on individuals living with cystic fibrosis

INTRODUCTION

Natural, social, and constructed environments play a critical role in the development and exacerbation of respiratory diseases. However, less is known regarding the influence of these environmental/community risk factors on the health of individuals living with cystic fibrosis (CF), compared to other pulmonary disorders.

AREAS COVERED

Here, we review current knowledge of environmental exposures related to CF, which suggests that environmental/community risk factors do interact with the respiratory tract to affect outcomes. Studies discussed in this review were identified in PubMed between March 2019 and March 2020. Although the limited data available do not suggest that avoiding potentially detrimental exposures other than secondhand smoke could improve outcomes, additional research incorporating novel markers of environmental exposures and community characteristics obtained at localized levels is needed.

EXPERT OPINION

As we outline, some environmental exposures and community characteristics are modifiable; if not by the individual, then by policy. We recommend a variety of strategies to advance understanding of environmental influences on CF disease progression.

The impact of driving time on pediatric TBI follow-up visit attendance

Objective: Examine the effect of driving time on follow-up visit attendance for children hospitalized with a traumatic brain injury (TBI). We hypothesized that families who lived further from the hospital would show poorer follow-up attendance.Participants: 368 children admitted to the hospital with TBI.Design & Outcome Measures: Using a retrospective chart review, we calculated driving time from patients' homes. The primary outcome was attendance at the first appointment post-discharge. We used logistic regression to examine the effect of driving time on attendance, including an analysis of the effects of injury and sociodemographic covariates on the model.Results: Majority of children attended their first appointment. Patients living 30-60 min from the hospital were most likely to attend, and those living 15 min away were least likely to attend. After adjusting for patient characteristics, families with driving time of 30-60 min had significantly higher odds of returning for follow-up than those with driving time <15 min, though the significance of this relationship disappeared after specific socioeconomic (SES) factors were included.Conclusions: Distance plays a significant role on follow-up attendance for pediatric patients with TBI. However, neighborhood SES may be an additional factor that influences the significance of the distance effect.Abbreviations: TBI: Traumatic brain injury; SES: socioeconomic status; ISS: Injury severity scale; AIS: Abbreviated injury scale.

Individual and Neighborhood Factors Associated with Undiagnosed Asthma in a Large Cohort of Urban Adolescents

Undiagnosed asthma adds to the burden of asthma and is an especially significant public health concern among urban adolescents. While much is known about individual-level demographic and neighborhood-level factors that characterize those with diagnosed asthma, limited data exist regarding these factors and undiagnosed asthma. This observational study evaluated associations between undiagnosed asthma and individual and neighborhood factors among a large cohort of urban adolescents. We analyzed data from 10,295 New York City adolescents who reported on asthma symptoms and diagnosis; a subset (n = 6220) provided addresses that we were able to geocode into US Census tracts. Multivariable regression models estimated associations between undiagnosed asthma status and individual-level variables. Hierarchical linear modeling estimated associations between undiagnosed asthma status and neighborhood-level variables. Undiagnosed asthma prevalence was 20.2%. Females had higher odds of being undiagnosed (adjusted odds ratio (AOR) = 1.25; 95% confidence interval (CI) = 1.13-1.37). Compared to White, non-Hispanic adolescents, Asian-Americans had higher risk of being undiagnosed (AOR = 1.41; 95% CI = 1.01-1.95); Latinos (AOR = 0.67; 95% CI = 0.45-0.83); and African-Americans/Blacks (AOR = 0.66; 95% CI = 0.52-0.87) had lower risk; Latinos and African-Americans/Blacks did not differ significantly. Living in a neighborhood with a lower concentration of Latinos relative to White non-Latinos was associated with lower risk of being undiagnosed (AOR = 0.66; CI = 0.43-0.95). Living in a neighborhood with health care provider shortages was associated with lower risk of being undiagnosed (AOR = 0.80; 95% CI =0.69-0.93). Public health campaigns to educate adolescents and their caregivers about undiagnosed asthma, as well as education for health care providers to screen adolescent patients for asthma, are warranted.

Integrating Social and Behavioral Determinants of Health into Population Health Analytics: A Conceptual Framework and Suggested Road Map

There is growing recognition that social and behavioral risk factors impact population health outcomes. Interventions that target these risk factors can improve health outcomes. This study presents a review of existing literature and proposes a conceptual framework for the integration of social and behavioral data into population health analytics platforms. The authors describe several use cases for these platforms at the patient, health system, and community levels, and align these use cases with the different types of prevention identified by the Centers for Disease Control and Prevention. They then detail the potential benefits of these use cases for different health system stakeholders and explore currently available and potential future sources of social and behavioral domains data. Also noted are several potential roadblocks for these analytic platforms, including limited data interoperability, expense of data acquisition, and a lack of standardized technical terminology for socio-behavioral factors.

Effects of a 1-Time Nurse-Led Telephone Call After Pediatric Discharge: The H2O II Randomized Clinical Trial

Importance

Families often struggle after discharge of a child from the hospital. Postdischarge challenges can lead to increased use of urgent health care services.

Objective

To determine whether a single nurse-led telephone call after pediatric discharge decreased the 30-day reutilization rate for urgent care services and enhanced overall transition success.

Design, Setting, and Participants

This Hospital-to-Home Outcomes (H2O) randomized clinical trial included 966 children and adolescents younger than 18 years (hereinafter referred to as children) admitted to general medicine services at a free-standing tertiary care children's hospital from May 11 through October 31, 2016. Data were analyzed as intention to treat and per protocol.

Interventions

A postdischarge telephone call within 4 days of discharge compared with standard discharge.

Main Outcomes and Measures

The primary outcome was the 30-day reutilization rate for urgent health care services (ie, unplanned readmission, emergency department visit, or urgent care visit). Secondary outcomes included additional utilization measures, as well as parent coping, return to normalcy, and understanding of clinical warning signs measured at 14 days.

Results

A total of 966 children were enrolled and randomized (52.3% boys; median age [interquartile range], 2.4 years [0.5-7.8 years]). Of 483 children randomized to the intervention, the nurse telephone call was completed for 442 (91.5%). Children in the intervention and control arms had similar reutilization rates for 30-day urgent health care services (intervention group, 77 [15.9%]; control group, 63 [13.1%]; P = .21). Parents of children in the intervention group recalled more clinical warning signs at 14 days (mean, 1.8 [95% CI, 1.7-2.0] in the intervention group; 1.5 [95% CI, 1.4-1.6] in the control group; ratio of intervention to control, 1.2 [95% CI, 1.1-1.3]).

Conclusions and Relevance

Although postdischarge nurse contact did not decrease the reutilization rate of postdischarge urgent health care services, this method shows promise to bolster postdischarge education.

Trial Registration

ClinicalTrials.gov Identifier: NCT02081846.

Lost Earnings and Nonmedical Expenses of Pediatric Hospitalizations

BACKGROUND AND OBJECTIVES

Hospitalization-related nonmedical costs, including lost earnings and expenses such as transportation, meals, and child care, can lead to challenges in prioritizing postdischarge decisions. In this study, we quantify such costs and evaluate their relationship with sociodemographic factors, including family-reported financial and social hardships.

METHODS

This was a cross-sectional analysis of data collected during the Hospital-to-Home Outcomes Study, a randomized trial designed to determine the effects of a nurse home visit after standard pediatric discharge. Parents completed an in-person survey during the child's hospitalization. The survey included sociodemographic characteristics of the parent and child, measures of financial and social hardship, household income and also evaluated the family's total nonmedical cost burden, which was defined as all lost earnings plus expenses. A daily cost burden (DCB) standardized it for a 24-hour period. The daily cost burden as a percentage of daily household income (DCBi) was also calculated.

RESULTS

Median total cost burden for the 1372 households was $113, the median DCB was $51, and the median DCBi was 45%. DCB and DCBi varied across many sociodemographic characteristics. In particular, single-parent households (those with less work flexibility and more financial hardships experienced significantly higher DCB and DCBi. Those who reported ≥3 financial hardships lost or spent 6-times more of their daily income on nonmedical costs than those without hardships. Those with ≥1 social hardships lost or spent double their daily income compared with those without social hardships.

CONCLUSIONS

Nonmedical costs place burdens on families of children who are hospitalized, disproportionately affecting those with competing socioeconomic challenges.

Postdischarge Nurse Home Visits and Reuse: The Hospital to Home Outcomes (H2O) Trial

BACKGROUND

Hospital discharge is stressful for children and families. Poor transitional care is linked to unplanned health care reuse. We evaluated the effects of a pediatric transition intervention, specifically a single nurse home visit, on postdischarge outcomes in a randomized controlled trial.

METHODS

We randomly assigned 1500 children hospitalized on hospital medicine, neurology services, or neurosurgery services to receive either a single postdischarge nurse-led home visit or no visit. We excluded children discharged with skilled home nursing services. Primary outcomes included 30-day unplanned, urgent health care reuse (composite measure of unplanned readmission, emergency department, or urgent care visit). Secondary outcomes, measured at 14 days, included postdischarge parental coping, number of days until parent-reported return to normal routine, and number of "red flags" or clinical warning signs a parent or caregiver could recall.

RESULTS

The 30-day reuse rate was 17.8% in the intervention group and 14.0% in the control group. In the intention-to-treat analysis, children randomly assigned to the intervention group had higher odds of 30-day health care use (odds ratio: 1.33; 95% confidence interval: 1.003-1.76). In the per protocol analysis, there were no differences in 30-day health care use (odds ratio: 1.14; confidence interval: 0.84-1.55). Postdischarge coping scores and number of days until returning to a normal routine were similar between groups. Parents in the intervention group recalled more red flags at 14 days (mean: 1.9 vs 1.6; P < .01).

CONCLUSIONS

Children randomly assigned to the intervention had higher rates of 30-day postdischarge unplanned health care reuse. Parents in the intervention group recalled more clinical warning signs 2 weeks after discharge.

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.

Is a Patient's Current Address of Record a Reasonable Measure of Neighborhood Deprivation Exposure? A Case for the Use of Point in Time Measures of Residence in Clinical Care

Purpose: Interest is increasing in the use of geocoded patient address data to understand the effects that social determinants of health have on healthcare outcomes. Use of a patient's current address of record is often problematic given population mobility. Intragenerational economic mobility research suggests that patients will reside within neighborhoods with similar relative deprivation over time despite geographic mobility. The purpose of this study was to measure evidence of patient neighborhood deprivation persistence given a change in address of record.

Methods: A retrospective cohort study of patients receiving active care in an integrated delivery system in a high-mobility United States region. Neighborhood deprivation was measured using a block-group level area deprivation index. Neighborhood deprivation persistence was measured as the probability that an individual with an address of record change remained within a neighborhood with a similar deprivation score. Logistic regression was used to conduct multivariate analysis.

Results: Geographic mobility was highest among patients living in the most deprived neighborhoods versus least-deprived (odds ratio 1.75; 95% confidence interval: 1.71–1.79). Seventy-eight percent of all patients with a change of address did so to a neighborhood with a similar deprivation quintile. The probability that a random patient selected from the study had a change of address outside the same or neighboring quintile within a 1-year period ranged from 2% to 13%.

Conclusions: Neighborhood deprivation persistence was high among this population of patients from a high mobility region. A current address of record is a reasonable indicator of patient exposure to neighborhood deprivation within a 1–3-year timeframe that is useful in evaluating healthcare disparities.

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.

Uses and Misuses of Patient- and Neighborhood-level Social Determinants of Health Data

Health care leaders in the US are actively exploring strategies to identify and address patients' social and economic hardships as part of high-quality clinical care. The result has been a proliferation of screening tools and interventions related to patients' social determinants of health, but little guidance on effective strategies to implement them. Some of these tools rely on patient- or household-level screening data collected from patients during medical encounters. Other tools rely on data available at the neighborhood-level that can be used to characterize the environment in which patients live or to approximate patients' social or economic risks. Four case examples were selected from different health care organizations to illustrate strengths and limitations of using patient- or neighborhood-level social and economic needs data to inform a range of interventions. This work can guide health care investments in this rapidly evolving arena.

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.

Adding Social Determinant Data Changes Children's Hospitals' Readmissions Performance

OBJECTIVES

To determine whether social determinants of health (SDH) risk adjustment changes hospital-level performance on the 30-day Pediatric All-Condition Readmission (PACR) measure and improves fit and accuracy of discharge-level models.

STUDY DESIGN

We performed a retrospective cohort study of all hospital discharges meeting criteria for the PACR from 47 hospitals in the Pediatric Health Information database from January to December 2014. We built four nested regression models by sequentially adding risk adjustment factors as follows: chronic condition indicators (CCIs); PACR patient factors (age and sex); electronic health record-derived SDH (race, ethnicity, payer), and zip code-linked SDH (families below poverty level, vacant housing units, adults without a high school diploma, single-parent households, median household income, unemployment rate). For each model, we measured the change in hospitals' readmission decile-rank and assessed model fit and accuracy.

RESULTS

For the 458 686 discharges meeting PACR inclusion criteria, in multivariable models, factors associated with higher discharge-level PACR measure included age <1 year, female sex, 1 of 17 CCIs, higher CCI count, Medicaid insurance, higher median household income, and higher percentage of single-parent households. Adjustment for SDH made small but significant improvements in fit and accuracy of discharge-level PACR models, with larger effect at the hospital level, changing decile-rank for 17 of 47 hospitals.

CONCLUSIONS

We found that risk adjustment for SDH changed hospitals' readmissions rate rank order. Hospital-level changes in relative readmissions performance can have considerable financial implications; thus, for pay for performance measures calculated at the hospital level, and for research associated therewith, our findings support the inclusion of SDH variables in risk adjustment.