A Data Science Approach to Analyze the Association of Socioeconomic and Environmental Conditions With Disparities in Pediatric Surgery

TL;DR

This study investigates how socioeconomic and environmental factors contribute to racial disparities in preoperative health conditions among children, revealing that socioenvironmental influences affect clinical status but not surgical outcomes after adjustments.

Contribution

It introduces an integrated data approach and an unsupervised clustering method to analyze neighborhood quality and its impact on pediatric surgical disparities.

Findings

African American children have higher prevalence of poor preoperative conditions.

Neighborhood quality influences preoperative health status.

No significant difference in surgical outcomes after adjustments.

Abstract

Scientific evidence confirm that significant racial disparities exist in healthcare, including surgery outcomes. However, the causal pathway underlying disparities at preoperative physical condition of children is not well-understood. This research aims to uncover the role of socioeconomic and environmental factors in racial disparities at the preoperative physical condition of children through multidimensional integration of several data sources at the patient and population level. After the data integration process an unsupervised k-means algorithm on neighborhood quality metrics was developed to split 29 zip-codes from Memphis, TN into good and poor-quality neighborhoods. An unadjusted comparison of African Americans and white children showed that the prevalence of poor preoperative condition is significantly higher among African Americans compared to whites. No statistically significant difference in surgery outcome was present when adjusted by surgical severity and neighborhood quality. The socioenvironmental factors affect the preoperative clinical condition of children and their surgical outcomes.