Racial and ethnic differences in hospital‐based low‐value pediatric care
Elisha McCoy, Megan E. Collins, Jillian M. Cotter, Natalie Grills, Matt Hall, Jessica Markham, Matthew J. Molloy, Michelle Polich, Michael J. Steiner, John R. Stephens, Michael J. Tchou, Ronald Teufel, Irma Ugalde, Andrew Yu, Samantha A. HouseAbstract
Background
Low‐value care (LVC), or care in which potential risk outweighs perceived benefits, continues to impact pediatric populations. While pediatric healthcare delivery is known to vary across racial and ethnic groups, little is known about the relationship between race and ethnicity and LVC. We sought to evaluate this relationship among hospitalized children.
Methods
This cross‐sectional study applied the Pediatric Health Information System LVC Calculator to encounters from July 1, 2022 to June 30, 2024. We used generalized estimating equation models to analyze differences in LVC across seven groups (Non‐Hispanic White, Non‐Hispanic Black, Hispanic, Asian, American Indian or Alaska Native, Native Hawaiian or Pacific Islander, and Other or Multiracial). For measures with across‐group differences, we performed pairwise comparisons to assess differential odds of LVC receipt with the Non‐Hispanic White group as a referent. We then performed a subanalysis applying these methods to only the largest groups.
Results
Of 14 eligible measures, LVC varied across racial and ethnic groups for seven. Patterns varied by measure, with no group demonstrating consistently high or low LVC. Measures with the greatest variation across groups included head computed tomography for first seizure, concurrent use of antipsychotics, and broad‐spectrum antibiotics for uncomplicated community‐acquired pneumonia. Our subanalysis demonstrated similar findings, with across‐group differences noted for eight measures.
Conclusions
We identified differences in LVC receipt by race and ethnicity for some services among hospitalized patients, without consistency in patterns across measures. Further evaluation of drivers and outcomes associated with these patterns is needed; our findings may assist in prioritizing deimplementation efforts.