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

Bettenhausen, Jessica L.; Noelke, Clemens; Ressler, Robert W.; Hall, Matthew; Harris, Mitch; Peltz, Alon; Auger, Katherine A.; Teufel, Ronald J.; Lutmer, Jeffrey; Krager, Molly; Simon, Harold K.; Neuman, Mark I.; Pavuluri, Padmaja; Morse, Rustin B.; Eghtesady, Pirooz; Macy, Michelle L.; Shah, Samir S.; Synhorst, David C.; Gay, James C.

doi:10.1016/j.acap.2021.12.015

Cited by 57 publications

(33 citation statements)

References 32 publications

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“…In contrast, the census tract-based COI affords far greater granularity because neighborhood-level differences within specific geographic areas are more accurately captured. [14][15][16] More importantly, each of the aforementioned SES metrics likely provides only a partial explanation of the observed association between low SES and adverse outcomes, a consequence of the individual subcomponents used to derive the indices. In this regard, the COI is advantageous given that it has better predictive validity (more predictive of outcomes such as life expectancy and coronary heart disease), efficiency (29 metrics are combined into a single score), and content validity (more comprehensive measure of neighborhood quality or resources for children) than singular measures of SES.…”

Section: Discussionmentioning

confidence: 99%

“…In this regard, the COI is advantageous given that it has better predictive validity (more predictive of outcomes such as life expectancy and coronary heart disease), efficiency (29 metrics are combined into a single score), and content validity (more comprehensive measure of neighborhood quality or resources for children) than singular measures of SES. 14,15 In addition, the COI may better capture racial and ethnic inequalities in access to neighborhood opportunity (ie, greater equity validity) than contemporary SES measures. 12 Within the realm of congenital heart disease, the COI has particular utility for assessing the impact of SES on postoperative outcomes because it specifically focuses on child neighborhood opportunity rather than measures of socioeconomic disadvantage that are more appropriate for adult populations.…”

Section: Discussionmentioning

confidence: 99%

“…All neighborhoods nationwide were ranked by COI z-score, and weighted percentiles (corresponding to the total number of children in a given tract) were used to exactly define the cut points categorizing neighborhoods into groups that each contain 20% of the US child population. 14,15,19 Each patient in our cohort was thus assigned 1 of 5 nationally-normed, rank-ordered groups of childhood opportunity level: very low, low, moderate, high, and very high. 20…”

Section: Methodsmentioning

confidence: 99%

“…13 Comprising 29 indicators of child neighborhood opportunity across 3 domains (education, health and environment, and socioeconomic), the COI is a validated approach for quantifying contemporary barriers to the equitable distribution of opportunity across US neighborhoods. 14 While COI-derived measures of opportunity have been identified as predictors of adolescent cardiometabolic risk, 15 pediatric readmissions and emergency department revisits, 14 and access to primary care, 16 the multifaceted pathways through which a child's environment impacts outcomes in the congenital heart disease population remain poorly studied. We therefore sought to evaluate the association between childhood opportunity level and important outcomes after congenital cardiac surgery while adjusting for established risk factors of adverse postoperative outcomes, including residual lesion severity and case complexity.…”

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confidence: 99%

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Contemporary Socioeconomic and Childhood Opportunity Disparities in Congenital Heart Surgery

et al. 2022

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Background: While singular measures of socioeconomic status have been associated with outcomes after surgery for congenital heart disease, the multifaceted pathways through which a child’s environment impacts similar outcomes remain incompletely characterized. We sought to evaluate the association between childhood opportunity level and adverse outcomes after congenital heart surgery. Methods: Data from patients undergoing congenital cardiac surgery from January 2011 to January 2020 at a quaternary referral center were retrospectively reviewed. Outcomes of interest included predischarge (early) mortality or transplant, postoperative hospital length-of-stay, inpatient cost of hospitalization, postdischarge (late) mortality or transplant, and late unplanned reintervention. The primary predictor was a US census tract–based, nationally-normed composite metric of contemporary child neighborhood opportunity comprising 29 indicators across 3 domains (education, health and environment, and socioeconomic), categorized as very low, low, moderate, high, and very high. Associations between childhood opportunity level and outcomes were evaluated using logistic regression (early mortality), generalized linear (length-of-stay and cost), Cox proportional hazards (late mortality), or competing risk (late reintervention) models, adjusting for baseline patient-related factors, case complexity, and residual lesion severity. Results: Of 6133 patients meeting entry criteria, the median age was 2.0 years (interquartile range, 3.6 months–8.3 years). There were 124 (2.0%) early deaths or transplants, the median postoperative length-of-stay was 7 days (interquartile range, 5–13 days), and the median inpatient cost was $76 000 (interquartile range, $50 000–130 000). No significant association between childhood opportunity level and early mortality or transplant was observed ( P =0.21). On multivariable analysis, children with very low and low opportunity had significantly longer length-of-stay and incurred higher costs compared with those with very high opportunity (all P <0.05). Of 6009 transplant-free survivors of hospital discharge, there were 175 (2.9%) late deaths or transplants, and 1008 (16.8%) reinterventions at up to 10.5 years of follow-up. Patients with very low opportunity had a significantly greater adjusted risk of late death or transplant (hazard ratio, 1.7 [95% CI, 1.1–2.6]; P =0.030) and reintervention (subdistribution hazard ratio, 1.9 [95% CI, 1.5–2.3]; P <0.001), versus those with very high opportunity. Conclusions: Childhood opportunity level is independently associated with adverse outcomes after congenital heart surgery. Children from resource-limited settings thus constitute an especially high-risk cohort that warrants closer surveillance and tailored interventions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

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Contemporary Socioeconomic and Childhood Opportunity Disparities in Congenital Heart Surgery

et al. 2022

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“…New tools based on geocoding allow specific access to the wider range of community variables associated with SDOH. For example, the Childhood Opportunity Index is a scale based on linkages at the level of the Census tract related to dozens of community level factors, including the quality, availability, and uptake of education services, access to supermarkets, local greenspace, housing vacancy, air quality, health insurance coverage, and employment rate . The study by Alfaro Hudak and colleagues could not directly assess community-level SDOH because these national data sets do not allow this level of granular linkage to community conditions in order to maintain confidentiality.…”

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confidence: 99%

A Vision for Addressing Social Needs and Social Determinants of Health

2023

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Alfaro Hudak and colleagues 1 describe the association between vision loss in adolescents and adults and social determinants of health (SDOH) in a cross-sectional analysis of 3 nationally representative data sets.Although there was variability in how vision loss was categorized, including only 1 data set that directly assessed visual acuity, and variability in how SDOH was measured, the findings were consistent: adverse social risk factors were associated with worse vision. This is an important finding, but also expected. It is hard to identify a health outcome that is not influenced by social risk factors. The real question is how these results can be used to improve population health. We suspect that many readers of the article by Alfaro Hudak and colleagues, 1 while aware of the challenges related to SDOH, engage with their patients to help improve access to timely and high-quality ophthalmologic care. This is commendable but will not be successful in addressing the fundamental problems created by disparate social factors.Alfaro Hudak and colleagues reference the World Health Organization definition of SDOH. A more complete definition is that SDOH "are the non-medical factors that influence health outcomes. They are the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life." 2 Many clinics and other health centers have adopted screening for social needs (eg, food insecurity, housing insecurity, energy insecurity, and transportation problems). The degree to which social needs screening is effective depends on how well the questions are asked and the degree to which follow-up services are provided. Regardless, it is important to not conflate social needs screening with evaluating SDOH. Individuals might not identify a particular social need in a given visit but still live in a community with little green space, community-level underemployment, or with social exclusion. Direct evidence supports the impact of these kinds of environmental exposures and vision. For example, regular outdoor exercise, which relies on access to safe spaces, decreases the risk of myopia in school-aged children. 3 Social needs screening also only provides insight into what is going on at a moment in time, while SDOH affects individuals, families, and communities over a lifetime and across many domains. Addressing social needs for individuals in a visit can be valuable, and it is something that can be embedded into clinical practice. Such work also helps address gaps where social determinants of health in the local community are not being meaningfully addressed. They are best addressed by health care systems in partnership with other community-based organizations and with community members.Many of the SDOH factors considered by Alfaro Hudak and colleagues are personal-level factors (eg, income, employment, food security, education, marital status, health care access, and high-speed Internet) that are likely to be associated

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Racial and Ethnic Differences in Insurer Classification of Nonemergent Pediatric Emergency Department Visits

et al. 2023

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ImportanceGovernment and commercial health insurers have recently enacted policies to discourage nonemergent emergency department (ED) visits by reducing or denying claims for such visits using retrospective claims algorithms. Low-income Black and Hispanic pediatric patients often experience worse access to primary care services necessary for preventing some ED visits, raising concerns about the uneven impact of these policies.ObjectiveTo estimate potential racial and ethnic disparities in outcomes of Medicaid policies for reducing ED professional reimbursement based on a retrospective diagnosis-based claims algorithm.Design, Setting, and ParticipantsThis simulation study used a retrospective cohort of pediatric ED visits (aged 0-18 years) for Medicaid-insured children and adolescents appearing in the Market Scan Medicaid database between January 1, 2016, and December 31, 2019. Visits missing date of birth, race and ethnicity, professional claims data, and Current Procedural Terminology codes of billing level of complexity were excluded, as were visits that result in admission. Data were analyzed from October 2021 to June 2022.Main Outcomes and MeasuresProportion of ED visits algorithmically classified as nonemergent and simulated per-visit professional reimbursement after applying a current reimbursement reduction policy for potentially nonemergent ED visits. Rates were calculated overall and compared by race and ethnicity.ResultsThe sample included 8 471 386 unique ED visits (43.0% by patients aged 4-12 years; 39.6% Black, 7.7% Hispanic, and 48.7% White), of which 47.7% were algorithmically identified as potentially nonemergent and subject to reimbursement reduction, resulting in a 37% reduction in ED professional reimbursement across the study cohort. More visits by Black (50.3%) and Hispanic (49.0%) children were algorithmically identified as nonemergent when compared with visits by White children (45.3%; P &lt; .001). Modeling the impact of the reimbursement reductions across the cohort resulted in expected per-visit reimbursement that was 6% lower for visits by Black children and 3% lower for visits by Hispanic children relative to visits by White children.Conclusions and RelevanceIn this simulation study of over 8 million unique ED visits, algorithmic approaches for classifying pediatric ED visits that used diagnosis codes identified proportionately more visits by Black and Hispanic children as nonemergent. Insurers applying financial adjustments based on these algorithmic outputs risk creating uneven reimbursement policies across racial and ethnic groups.

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

Cited by 57 publications

References 32 publications

Contemporary Socioeconomic and Childhood Opportunity Disparities in Congenital Heart Surgery

Contemporary Socioeconomic and Childhood Opportunity Disparities in Congenital Heart Surgery

A Vision for Addressing Social Needs and Social Determinants of Health

Racial and Ethnic Differences in Insurer Classification of Nonemergent Pediatric Emergency Department Visits

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