Evidence map›Paper›PMID 30626622›Full record

ArticlePediatrics2019

Perinatal Risk Factors and Outcome Coding in Clinical and Administrative Databases.

Daniel S Tawfik, Jeffrey B Gould, Jochen Profit

Abstract read
In one paragraph

Article in Pediatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 4 pooled it
–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

23 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Why & where perinatal deaths: trends and determinants in Pakistan.Maternal health, neonatology and perinatology · 2026
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  7. Prenatal homelessness, food insecurity, and unemployment and adverse infant outcomes in a California cohort, 2007-2020.Journal of perinatology : official journal of the California Perinatal Association · 2025
    Article
  8. Article
  9. Are racial and ethnic disparities in brachial plexus birth injuries explained by known risk factors?Journal of perinatology : official journal of the California Perinatal Association · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. The validity of hospital diagnostic and procedure codes reflecting morbidity in preterm neonates born <32 weeks gestation.Journal of perinatology : official journal of the California Perinatal Association · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. Latent class analysis to characterize neonatal risk for neurodevelopmental differences.Journal of child psychology and psychiatry, and allied disciplines · 2023
    Article
  18. Seven years later: state neonatal risk-appropriate care policy consistency with the 2012 American Academy of Pediatrics Policy.Journal of perinatology : official journal of the California Perinatal Association · 2022
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Daniel S TawfikDepartments of Pediatric Critical Care Medicine, Pediatrics and dtawfik@stanford.edu.
Jeffrey B GouldDivisions of Perinatal Epidemiology and Health Outcomes Research Unit, Neonatology and.
Jochen ProfitDivisions of Perinatal Epidemiology and Health Outcomes Research Unit, Neonatology and.

Funding

A Dashboard of Racial/Ethnic Disparity in Care Provided by NICUsR01HD083368 · NICHD · STANFORD UNIVERSITY · PI PROFIT, JOCHEN · 2016 to 2020
$3.2M
Social Disparities in NICU CareR01HD084667 · NICHD · STANFORD UNIVERSITY · PI PROFIT, JOCHEN · 2016 to 2019
$2.4M
NICHD NIH HHS R01 HD083368NICHD NIH HHS R01 HD084667
6 · The paper itself

Abstract

BACKGROUND AND

objectivesAdministrative databases may allow true population-based studies and quality improvement endeavors, but the accuracy of billing codes for capturing key risk factors and outcomes needs to be assessed. We sought to describe the performance of a statewide administrative database and the clinical database from the California Perinatal Quality Care Collaborative (CPQCC).

methodsThis population-based retrospective cohort study linked key perinatal risk factors and outcomes from the 133-unit CPQCC database to relevant billing codes from administrative maternal and newborn inpatient discharge records, for 50 631 infants born from 2006 to 2012. Using the CPQCC record as the gold standard, we calculated the positive predictive value, negative predictive value, and Matthews correlation coefficient for each item, then evaluated comparative performance across units.

resultsThe Matthews correlation coefficient was highest (>0.7; strong positive correlation) for multiple delivery, Cesarean delivery, very low birth weight, maternal hypertension, maternal diabetes, patent ductus arteriosus, in-hospital death, patent ductus arteriosus and retinopathy of prematurity surgeries, extracorporeal life support, and intraventricular hemorrhage. Maternal chorioamnionitis, fetal distress, retinopathy of prematurity staging, chronic lung disease, and pneumothorax were the least reliably coded. Maternal factors and delivery details were more reliably coded in the maternal inpatient record than the newborn inpatient record.

conclusionsSeveral important perinatal risk factors and outcomes are highly congruent between these administrative and clinical databases. Several subjective risk factors and outcomes are appropriate targets for data improvement initiatives. The ability for timely extraction of administrative inpatient data will be key to their usefulness in quality metrics.

Indexed as

Cohort StudiesDatabases, FactualFemaleHumansHypertensionInfant, NewbornInfant, Very Low Birth WeightInternational Classification of DiseasesMaternal HealthPatient DischargePerinatal CarePregnancyRetrospective StudiesRisk FactorsTreatment Outcome

Identifiers

PMID30626622
PMCPMC6361352

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Registered trials

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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.