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Scientific evidence confirm that significant racial disparities exist inhealthcare, including surgery outcomes. However, the causal pathway underlyingdisparities at preoperative physical condition of children is notwell-understood. This research aims to uncover the role of socioeconomic andenvironmental factors in racial disparities at the preoperative physicalcondition of children through multidimensional integration of several datasources at the patient and population level. After the data integration processan unsupervised k-means algorithm on neighborhood quality metrics was developedto split 29 zip-codes from Memphis, TN into good and poor-qualityneighborhoods. An unadjusted comparison of African Americans and white childrenshowed that the prevalence of poor preoperative condition is significantlyhigher among African Americans compared to whites. No statistically significantdifference in surgery outcome was present when adjusted by surgical severityand neighborhood quality. The socioenvironmental factors affect thepreoperative clinical condition of children and their surgical outcomes.

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