Evidence map›Paper›PMID 39289213›Full record

ArticlePediatric radiology2024

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

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

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Article in Pediatric radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Sebastian Gallo-BernalMassachusetts General Hospital, 55 Fruit St, Austen 250, Boston, MA, 02114, USA.
Valeria Peña-TrujilloMassachusetts General Hospital, 55 Fruit St, Austen 250, Boston, MA, 02114, USA.
Daniel BriggsMassachusetts General Hospital, 55 Fruit St, Austen 250, Boston, MA, 02114, USA.
Fedel Machado-RivasMassachusetts General Hospital, 55 Fruit St, Austen 250, Boston, MA, 02114, USA.
Oleg S PianykhMassachusetts General Hospital, 55 Fruit St, Austen 250, Boston, MA, 02114, USA.
Efren J FloresMassachusetts General Hospital, 55 Fruit St, Austen 250, Boston, MA, 02114, USA.
Michael S GeeMassachusetts General Hospital, 55 Fruit St, Austen 250, Boston, MA, 02114, USA. msgee@mgh.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResearch 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.

objectiveEvaluate the social determinants of health and sociodemographic factors related to pediatric radiology MCO before, during, and after the COVID-19 pandemic. MATERIALS AND

methodsThe 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.

resultsA 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.

conclusionThe 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.

Indexed as

COVID-19Healthcare DisparitiesAdolescentChildChild, PreschoolFemaleHealth Services AccessibilityHumansMalePandemicsRetrospective StudiesSARS-CoV-2Social Determinants of HealthSocioeconomic FactorsChildCOVID-19Data scienceEthnicityHealthcare disparitiesLogistic modelsPandemicsSocial determinants of healthSociodemographic factors

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PMID39289213

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