Evidence map›Paper›PMID 33000430›Full record

ArticleJournal of racial and ethnic health disparities2021

Race, Ethnicity, and Insurance: the Association with Opioid Use in a Pediatric Hospital Setting.

Louis Ehwerhemuepha, Candice D Donaldson, Zeev N Kain, Vivian Luong, Michelle A Fortier, William Feaster, Michael Weiss, Daniel Tomaszewski, Sun Yang, Michael Phan and 1 more

Abstract read
In one paragraph

Article in Journal of racial and ethnic health disparities, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Observational
  2. The Association of Neighborhood Disadvantage with Surgical Outcomes and Follow-up Adherence in Patients with Cleft Palate.The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association · 2026
    Article
  3. Article
  4. The Cost of Opioid Use in High-Risk Hospitalized Infants.The Journal of surgical research · 2024
    Article
  5. Article
  6. Article
  7. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Louis EhwerhemuephaDepartment of Information Systems, Children's Hospital of Orange County, CA, 92868, Orange, USA.
Candice D DonaldsonDepartment of Psychology, Chapman University, Orange, CA, 92866, USA.
Zeev N KainCenter on Stress & Health, University of California Irvine, Orange, CA, 92868, USA.
Vivian LuongDepartment of Psychology, Chapman University, Orange, CA, 92866, USA.
Michelle A FortierCenter on Stress & Health, University of California Irvine, Orange, CA, 92868, USA.
William FeasterDepartment of Information Systems, Children's Hospital of Orange County, CA, 92868, Orange, USA.
Michael WeissPopulation Health, Children's Hospital of Orange County, Orange, CA, 92868, USA.
Daniel TomaszewskiSchool of Pharmacy Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA, 90089, USA.
Sun YangSchool of Pharmacy, Department of Pharmacy Practice, Chapman University, Orange, CA, 92868, USA.
Michael PhanSchool of Pharmacy, Department of Biomedical and Pharmaceutical Sciences, Chapman University, Orange, CA, 92868, USA.
Brooke N JenkinsDepartment of Psychology, Chapman University, Orange, CA, 92866, USA. bjenkins@chapman.edu.

Funding

The Development of Novel Mechanistically-based APE/Ref-1 Redox InhibitorsK08CA179084 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI YANG, SUN · 2014 to 2018
$569k
NCI NIH HHS K08 CA179084
6 · The paper itself

Abstract

backgroundThis study examined the association between race/ethnicity and health insurance payer type with pediatric opioid and non-opioid ordering in an inpatient hospital setting.

methodsCross-sectional inpatient encounter data from June 2013 to June 2018 was retrieved from a pediatric children's hospital in Southern California (N = 55,944), and statistical analyses were performed to determine associations with opioid ordering.

resultsThere was a significant main effect of race/ethnicity on opioid and non-opioid orders. Physicians ordered significantly fewer opioid medications, but a greater number of non-opioid medications, for non-Hispanic African American children than non-Hispanic Asian, Hispanic/Latinx, and non-Hispanic White pediatric patients. There was also a main effect of health insurance payer type on non-opioid orders. Patients with government-sponsored plans (e.g., Medi-Cal, Medicare) received fewer non-opioid prescriptions compared with patients with both HMO and PPO coverage. Additionally, there was a significant race/ethnicity by insurance interaction on opioid orders. Non-Hispanic White patients with "other" insurance coverage received the greatest number of opioid orders. In non-Hispanic African American patients, children with PPO coverage received fewer opioids than those with government-sponsored and HMO insurance. For non-Hispanic Asian patients, children with PPO were prescribed more opioids than those with government-sponsored and HMO coverage.

conclusionFindings suggest that the relationship between race/ethnicity, insurance type, and physician decisions opioid prescribing is complex and multifaceted. Given that consistency in opioid prescribing should be seen regardless of patient background characteristics, future studies should continue to assess and monitor unequitable differences in care.

Indexed as

Hospitals, PediatricAdolescentAnalgesics, OpioidCaliforniaChildChild, PreschoolCross-Sectional StudiesEthnicityFemaleHumansInfantInfant, NewbornInsurance, HealthMaleMedicareRacial GroupsAnalgesics, OpioidDisparitiesElectronic medical recordOpioidsPediatric painRace and ethnicity

Identifiers

PMID33000430
PMCPMC8552771

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.