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

Abstract

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.

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

“…(29) This possibility warrants further investigation, especially considering the growing emphasis on identifying and responding to the SDH during patient care. (30) While social risk assessment is increasingly upheld as a critical component of preventive patient care, no singular “right” way to assess (or intervene) has been established.…”

“…We previously showed significant correlations between area-level and family-reported measures of socioeconomic status within a cohort of children hospitalized with asthma. (33) Such area-level data, or “geomarkers,”(8, 29) could inform assessments and target interventions (eg, medication delivery, legal advocacy, care navigation, connection to community resources or agencies) in ways that warrant further evaluation. (20) The domains of the COI could also support the development and ongoing evaluation of cross-sector partnerships.…”

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

“…While immune‐ and nonimmune‐mediated allograft injury and complications from immunosuppression play a central role, ineffective self‐management increases risk for nonadherence and graft injury . Social determinants of health, including neighborhood context, influence self‐management capabilities in children with chronic conditions and are key contributors to health outcomes but have not been routinely collected by transplant registries or implicated directly in liver transplant outcomes . While transplant registries collect insurance status, this metric does not accurately reflect one's socioeconomic status (SES)—especially in the Affordable Care Act era where increasing percentages of children are covered by Medicaid .…”

“…Neighborhood‐level socioeconomic data (linked via home ZIP code) provide information that can contextualize a child's living environment, including the extent of neighborhood socioeconomic resources. These data might provide a more comprehensive understanding of the socioeconomic milieu in which a patient experiences and manages his or her chronic disease . Such geographic, place‐based data are associated with adverse health outcomes across diseases, and this knowledge has been used to improve other medical outcomes for children of low SES .…”

Neighborhood Commute to Work Times and Self-Reported Caregiver Health Behaviors and Food Access

“…24 For healthcare providers, understanding associations between the neighborhood environment and health behaviors may allow for environmentally-tailored counseling and interventions. 25 Due to its association with obesity in adults as well as potential associations with caregiver health behaviors, commute times in particular may be an important factor to consider when providing diet and lifestyle counseling. 8,9 Future research should include examining associations between family diet and activity and self-reported caregiver commute times.…”