Racial and Ethnic Differences in Emergency Department Diagnostic Imaging at US Children’s Hospitals, 2016-2019
Bibliographic record
Abstract
Importance: Diagnostic imaging is frequently performed as part of the emergency department (ED) evaluation of children. Whether imaging patterns differ by race and ethnicity is unknown. Objective: To evaluate racial and ethnic differences in the performance of common ED imaging studies and to examine patterns across diagnoses. Design, Setting, and Participants: This cross-sectional study evaluated visits by patients younger than 18 years to 44 US children's hospital EDs from January 1, 2016, through December 31, 2019. Exposures: Non-Hispanic Black and Hispanic compared with non-Hispanic White race/ethnicity. Main Outcomes and Measures: The primary outcome was the proportion of visits for each race/ethnicity group with at least 1 diagnostic imaging study, defined as plain radiography, computed tomography, ultrasonography, and magnetic resonance imaging. The major diagnostic categories classification system was used to examine race/ethnicity differences in imaging rates by diagnoses. Results: A total of 13 087 522 visits by 6 230 911 children and adolescents (mean [SD] age, 5.8 [5.2] years; 52.7% male) occurred during the study period. Diagnostic imaging was performed during 3 689 163 visits (28.2%). Imaging was performed in 33.5% of visits by non-Hispanic White patients compared with 24.1% of visits by non-Hispanic Black patients (odds ratio [OR], 0.60; 95% CI, 0.60-0.60) and 26.1% of visits by Hispanic patients (OR, 0.66; 95% CI, 0.66-0.67). Adjusting for confounders, visits by non-Hispanic Black (adjusted OR, 0.82; 95% CI, 0.82-0.83) and Hispanic (adjusted OR, 0.87; 95% CI, 0.87-0.87) patients were less likely to include any imaging study compared with visits by non-Hispanic White patients. Limiting the analysis to only visits by nonhospitalized patients, the adjusted OR for imaging was 0.79 (95% CI, 0.79-0.80) for visits by non-Hispanic Black patients and 0.84 (95% CI, 0.84-0.85) for visits by Hispanic patients. Results were consistent in analyses stratified by public and private insurance groups and did not materially differ by diagnostic category. Conclusions and Relevance: In this study, non-Hispanic Black and Hispanic children were less likely to receive diagnostic imaging during ED visits compared with non-Hispanic White children. Further investigation is needed to understand and mitigate these potential disparities in health care delivery and to evaluate the effect of these differential imaging patterns on patient outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".