Evidence map›Paper›PMID 25601974›Full record

ArticlePediatrics2015

Regional variation in antenatal corticosteroid use: a network-level quality improvement study.

J Profit, B A Goldstein, J Tamaresis, P Kan, H C Lee

Abstract read
In one paragraph

Article in Pediatrics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Observational
  2. Observational
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Disparities in the use of antenatal corticosteroids among women with hypertension in North Carolina.Journal of perinatology : official journal of the California Perinatal Association · 2020
    Article
  9. Article
  10. Observational
  11. Variation in quality report viewing by providers and correlation with NICU quality metrics.Journal of perinatology : official journal of the California Perinatal Association · 2017
    Observational
  12. Observational
  13. Article
  14. Article
  15. Article
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

5 authors.

J ProfitPerinatal Epidemiology and Health Outcomes Research Unit, Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine and Lucile Packard Children's Hospital, Palo Alto, California; California Perinatal Quality Care Collaborative, Palo Alto, California; profit@stanford.edu.
B A GoldsteinDepartment of Biostatistics & Bioinformatics, Duke University, Durham, North Carolina; and.
J TamaresisDepartment of Pediatrics, Stanford University School of Medicine, Palo Alto, California.
P KanPerinatal Epidemiology and Health Outcomes Research Unit, Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine and Lucile Packard Children's Hospital, Palo Alto, California;
H C LeePerinatal Epidemiology and Health Outcomes Research Unit, Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine and Lucile Packard Children's Hospital, Palo Alto, California; California Perinatal Quality Care Collaborative, Palo Alto, California;

Funding

Understanding and predicting cardiac events in HD using real-time EHRsK25DK097279 · NIDDK · STANFORD UNIVERSITY · PI GOLDSTEIN, BENJAMIN ALAN · 2013 to 2017
$797k
Maternal, Clinician & Hospital Factors in Breastmilk for Premature InfantsK23HD068400 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LEE, HENRY CHONG · 2012 to 2015
$520k
NICHD NIH HHS K23 HD068400NICHD NIH HHS K23HD068400NIDDK NIH HHS K25 DK097279
6 · The paper itself

Abstract

BACKGROUND AND

objectivesExamination of regional care patterns in antenatal corticosteroid use (ACU) rates may be salient for the development of targeted interventions. Our objective was to assess network-level variation using California perinatal care regions as a proxy. We hypothesized that (1) significant variation in ACU exists within and between California perinatal care regions, and (2) lower performing regions exhibit greater NICU-level variability in ACU than higher performing regions.

methodsWe undertook cross-sectional analysis of 33,610 very low birth weight infants cared for at 120 hospitals in 11 California perinatal care regions from 2005 to 2011. We computed risk-adjusted median ACU rates and interquartile ranges (IQR) for each perinatal care region. The degree of variation was assessed using hierarchical multivariate regression analysis with NICU as a random effect and region as a fixed effect.

resultsFrom 2005 to 2011, mean ACU rates across California increased from 82% to 87.9%. Regional median (IQR) ACU rates ranged from 68.4% (24.3) to 92.9% (4.8). We found significant variation in ACU rates among regions (P < .0001). Compared with Level IV NICUs, care in a lower level of care was a strongly significant predictor of lower odds of receiving antenatal corticosteroids in a multilevel model (Level III, 0.65 [0.45-0.95]; Level II, 0.39 [0.24-0.64]; P < .001). Regions with lower performance in ACU exhibited greater variability in performance.

conclusionsWe found significant variation in ACU rates among California perinatal regions. Regional quality improvement approaches may offer a new avenue to spread best practice.

Indexed as

Infant, Very Low Birth WeightQuality ImprovementAdrenal Cortex HormonesAdultCaliforniaDrug UtilizationFemaleHumansInfant, NewbornIntensive Care Units, NeonatalMaleMaternal AgePregnancyPrenatal Exposure Delayed EffectsQuality Assurance, Health CareRegional Medical ProgramsAdrenal Cortex Hormonesantenatal corticosteroidsneonatal intensive carequality of carevariation

Identifiers

PMID25601974
PMCPMC4306799

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.