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A data science-based analysis of socioeconomic determinants impacting pediatric diagnostic radiology utilization during the COVID-19 pandemic

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Abstract

Background

Research on healthcare disparities in pediatric radiology is limited, leading to the persistence of missed care opportunities (MCO). We hypothesize that the COVID-19 pandemic exacerbated existing health disparities in access to pediatric radiology services.

Objective

Evaluate the social determinants of health and sociodemographic factors related to pediatric radiology MCO before, during, and after the 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 the least absolute shrinkage and selection operator (LASSO) method 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 initial recovery phase. Median age was 11.34 years (IQR 5.24–15.02), with 50.8% females (31,513/62,009). MCO increased during the pandemic (1,075/3,205; 33.5%) compared to pre-pandemic (5,235/30,567; 17.1%) and initial recovery phase (4,664/28,237; 16.5%). The CART analysis identified changing predictors of missed care opportunities across different periods. Pre-pandemic, these were driven by exam-specific factors and patient age. During the pandemic, social determinants like income, distance, and ethnicity became key. In the initial recovery phase, the focus returned to exam-specific factors and age, but ethnicity continued to influence missed care, particularly in neurological exams for Hispanic patients. Logistic regression revealed similar results: during the pandemic, increased distance from the examination site (OR 1.1), residing outside the state (OR 1.57), Hispanic (OR 1.45), 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 2.3) had higher odds. In the initial recovery phase, factors such as living outside the state (OR 1.19), orders for children (OR 0.79), and being Hispanic (OR 1.15) correlate with higher odds of MCO.

Conclusion

The application of basic data science techniques is a valuable tool in uncovering complex relationships between sociodemographic factors and disparities in pediatric radiology, offering crucial insights into addressing inequalities in care.

Graphical Abstract

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Data availability

No datasets were generated or analysed during the current study.

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Authors and Affiliations

  1. Massachusetts General Hospital, 55 Fruit St, Austen 250, Boston, MA, 02114, USA

    Sebastian Gallo-Bernal, Valeria Peña-Trujillo, Daniel Briggs, Fedel Machado-Rivas, Oleg S. Pianykh, Efren J. Flores & Michael S. Gee

  2. Harvard University, Cambridge, MA, USA

    Sebastian Gallo-Bernal, Valeria Peña-Trujillo, Daniel Briggs, Fedel Machado-Rivas, Oleg S. Pianykh, Efren J. Flores & Michael S. Gee

Authors
  1. Sebastian Gallo-Bernal
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  2. Valeria Peña-Trujillo
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  3. Daniel Briggs
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  4. Fedel Machado-Rivas
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  5. Oleg S. Pianykh
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  6. Efren J. Flores
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  7. Michael S. Gee
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Contributions

S.G.B: wrote the main manuscript, prepared figures, helped with data analysis, and reviewed the manuscript. V.P.T: wrote specific parts of the manuscript, prepared figures, and reviewed the manuscript. F.M.R: wrote specific parts of the manuscript and reviewed the manuscript. O.l.P: data collection and analysis. D.B: data collection and analysis. E.F: significantly enhanced the manuscript's intellectual content through his meticulous revision. M.G: Oversaw all steps of the manuscript preparation, conceived the presented idea, and reviewed the final manuscript version.

Corresponding author

Correspondence to Michael S. Gee.

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Gallo-Bernal, S., Peña-Trujillo, V., Briggs, D. et al. A data science-based analysis of socioeconomic determinants impacting pediatric diagnostic radiology utilization during the COVID-19 pandemic. Pediatr Radiol 54, 1831–1841 (2024). https://doi.org/10.1007/s00247-024-06039-8

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  • DOI: https://doi.org/10.1007/s00247-024-06039-8

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