A Data Science-based approach to Identify Social Determinants of Health Impacting Access to Pediatric Radiology

Background Research on healthcare disparities in pediatric radiology is limited, leading to the persistence of missed care opportunities (MCO). Objective Evaluate the social determinants of health and sociodemographic factors related to pediatric radiology MCO before, during, and after COVID-19 pandemic. Materials and Methods The study examined all outpatient pediatric radiology exams at a pediatric medical center and its affiliate centers from 03/08/19 to 06/07/21, to identify missed care opportunities. Logistic regression with LASSO and Classification and Regression Tree (CART) analysis were used to explore factors and visualize relationships between social determinants and missed care opportunities. Results A total of 62,009 orders were analyzed, 30,567 pre-pandemic, 3,205 pandemic, and 28,237 post-pandemic. Median age was 11.34 (IQR: 5.24–15.02), with 50.8% females. MCO increased during the pandemic (33.5%) compared to pre-pandemic (17.1%) and post-pandemic (16.5%). Logistic regression revealed higher odds of MCO in the pre-pandemic period for orders involving fluoroscopy (OR:1.675), MRI (OR:1.991), nuclear medicine studies (OR:1.505), and ultrasound (OR:1.211), along with patients residing outside the state (OR:1.658) and across all age groups compared to adolescents. During the pandemic, increased distance from the examination site (OR:1.1), residing outside the state (OR:1.571), Hispanic (OR:1.492), lower household income ($25,000–50,000 [OR:3.660] and $50,000–75,000 [OR:1.866]), orders for infants (OR:1.43), and fluoroscopy (OR:2.303) had higher odds. In the post-pandemic period, factors such as living outside the state (OR:1.189), orders for children (OR:0.787), and being Hispanic (OR:1.148) correlate with higher odds of MCO. Conclusion Applying basic data science-based techniques is a helpful approach to understanding complex relationships between sociodemographic characteristics and disparities.