Breaking down neighborhood data reveals targeted pathways to reduce pediatric asthma ED visits

Asthma remains a leading driver of pediatric emergency department (ED) utilization, with outcomes shaped by social and environmental context. Data presented at the Pediatric Academic Societies 2026 Meeting evaluated 4,693 children with asthma receiving care at the Children’s Hospital at Montefiore Einstein and examined how neighborhood opportunity influences utilization patterns.

Although higher overall neighborhood opportunity was not associated with reductions in ED visits, hospitalizations, or hospital days, improvements in specific subdomains—health resources, housing, and wealth—were linked to meaningful reductions in ED visits.

In an interview with Contemporary Pediatrics, Jonathan Gabbay, MD, pediatric hospitalist and researcher, discussed how these findings can inform clinical care, health system design, and policy.

Why composite indices may obscure clinical insight

Gabbay emphasized that the apparent disconnect between overall neighborhood scores and outcomes is clinically meaningful.

“The disconnect is actually the most important finding of the study,” he said. “Composite indices, while useful for describing disparities, can actually obscure signals from specific drivers when you roll everything into a single score.”

He explained that neighborhoods may perform differently across domains, and aggregating them into a single score can mask clinically relevant variation.

“The composite is a starting point for identifying where disparities exist. The subdomains are where you start to understand why and what to do about it.”

For clinicians, this suggests that relying solely on summary indices may limit the ability to target interventions effectively.

Translating subdomains into actionable interventions

The interview highlighted how 3 domains—health resources, housing, and wealth—map to specific intervention pathways.

For health resources, Gabbay pointed to expanding access to consistent care:
“Things like school-based health centers, co-located asthma specialists within primary care clinics and community health workers…help families navigate the system and stay connected to care between visits.”

Housing-related drivers include environmental triggers such as mold and pests. He noted, “Interventions like healthy home programs, which pair home assessments with remediation, have decent evidence for reducing asthma morbidity.”

Wealth, while more difficult to modify directly, remains a powerful determinant. Policy-level interventions—including tax credits and housing subsidies—can influence downstream child health outcomes.

Gabbay added that clinical systems help connect families to these resources.
“Medical legal partnerships, community health workers and benefit navigators are a concrete way to do that.”

Role of machine learning in identifying heterogeneous effects

The study used causal forests, a machine learning approach, to better understand variability in neighborhood effects.

“Causal forests…handle confounding very flexibly,” Gabbay explained, noting their ability to model complex, nonlinear relationships between variables.

More importantly, the method allows for the identification of heterogeneous treatment effects.
“We’re not asking just, ‘Does this matter on average?’ We’re asking, ‘Who does it matter most to and under what conditions?’”

This aligns with the concept of “precision social medicine,” which seeks to tailor interventions based on individual and contextual factors.

Integrating social context into asthma management

Gabbay outlined 2 practical shifts for pediatricians.

First, clinicians should treat the social history as a clinical tool.
“The questions that really matter are very specific….Is there visible mold, pests, or…secondhand smoke? Is the family able to fill prescriptions consistently?”

He emphasized that these factors directly influence treatment success.
“Medication alone may not close the gap, and addressing the context in which the child lives is a critical part of the treatment.”

Second, screening must be paired with action.
“Screening for social needs is crucial and is valuable only if there’s something to do about that need.”

This requires building referral pathways that connect families to community-based resources and support systems.

Implications for research and health system design

Looking forward, Gabbay stressed the importance of linking neighborhood-level data with individual-level needs to avoid ecological fallacies.

“We need to pair neighborhood context data to individual social needs data, because the two can diverge in important ways.”

He also highlighted the need for investment in data infrastructure and interdisciplinary care models.
“The goal is to build tiered data-informed models…to direct limited resources to where they’ll have the most impact.”

These approaches may be particularly relevant in high-need communities, where targeted interventions can improve both efficiency and equity.

Reference

Gabbay J, Fazzari MJ, Bajaj BVM, et al. Effect of improving neighborhood resources on pediatric asthma outcomes: insights for targeted pathways. Presented at: 2026 Pediatric Academic Societies Meeting; April 24-27, 2026; Boston, MA.