Health Care Disparities in Children:
A Joint Article Collection from Journal of Pediatric Health Care and The Journal of Pediatrics
The COVID-19 pandemic has highlighted the effects of toxic stresses in our society that stem from systematic and structural racism and inequities. Such stresses include poverty, homelessness, disabilities, unemployment, civil unrest, food insecurity, substance abuse, social isolation and limited access to care. The purpose of this virtual issue compiled by The Journal of Pediatrics and the Journal of Pediatric Health Care is to further name and explicate health care disparities in children and youth associated with toxic stress, and to highlight approaches to reduce such inequities.
- Machine learning holds the possibility of improving racial health inequalities by compensating for human bias and structural racism. However, unanticipated racial biases may enter during model design, training, or implementation and perpetuate or worsen racial inequalities if ignored. Pre-existing racial health inequalities could be codified into medical care by machine learning without clinicians being aware. To illustrate the importance of a commitment to antiracism at all stages of machine learning, we examine machine learning in predicting severe sepsis in Black children, focusing on the impacts of structural racism that may be perpetuated by machine learning and difficult to discover.
- To evaluate how race, ethnicity, and social determinants of health (SDOH) are reported and discussed in 3 pediatrics journals.
- To examine the association of age-appropriate maternal educational attainment in teenage and young mothers on infant health outcomes across racial/ethnic groups.
- To characterize associations between living in primary care shortage areas and graft failure/death for children after liver transplantation.
- In epidemiologic research, race is considered often as a covariate of an outcome because such is customary practice, is seemingly easy to measure, is stable over time, and often is associated with variation in the outcome.1 The complexities and limitations in using race, a socially constructed way of grouping people for these purposes, however, perceptively elaborated 20 years ago,1 unmasks a dogma and challenges the neutrality of the traditional rationale for using race as a covariate. Jones underscores the points that definition and delineation of race are highly heterogeneous, contextually based, and subject to change over time, and race's association with outcome is difficult to distinguish from a broad2 range of underlying racist policies and practices.
- To develop a tool for quantifying health disparity (Health Disparity Index[HDI]) and explore hospital variation measured by this index using chest radiography (CXR) in asthma as the proof of concept.
- To determine if racial/ethnic differences exist in the diagnosis and mechanism of injury among children and adolescents visiting the emergency department (ED) for concussion and minor head trauma (MHT).
- To determine the associations of social and physical neighborhood conditions with recurrent emergency department (ED) utilization by children in the US.