ArticleJournal of perinatology : official journal of the California Perinatal Association2019
Data electronically extracted from the electronic health record require validation.
Article in Journal of perinatology : official journal of the California Perinatal Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Comparison of Lactation Information from Electronic Health Records with Survey Data Across Five US Health Systems.Epidemiology (Cambridge, Mass.) · 2026Article
- Using electronic health record data to identify incident uterine fibroids and endometriosis within a large, urban academic medical center: a validation study.American journal of epidemiology · 2026Article
- A validated NICU database: recounting 50 years of clinical growth, quality improvement and research.Pediatric research · 2025Article
- An open-source framework for end-to-end analysis of electronic health record data.Nature medicine · 2024Article
- A Multifunctional, Low Cost and Sustainable Neonatal Database System.Children (Basel, Switzerland) · 2024Article
- The impact of the Baby Friendly Hospital Initiative on neonatal hypoglycemia.Journal of perinatology : official journal of the California Perinatal Association · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesDetermine sources of error in electronically extracted data from electronic health records. STUDY
designCategorical and continuous variables related to early-onset neonatal hypoglycemia were preselected and electronically extracted from records of 100 randomly selected neonates within 3479 births with laboratory-proven early-onset hypoglycemia. Extraction language was written by an information technologist and data validated by blinded manual chart review. Kappa coefficient assessed categorical variables and percent validity continuous variables.
results8/23 (35%) categorical variables had acceptable Κappa (1-0.81); 5/23 (22%) had fair-slight agreement, Κappa < 0.40. Notably, "hypoglycemia" had poor agreement, Κappa 0.16. In contrast, 6/8 continuous variables had validity ≥ 94%. After correcting extraction language, 6/9 variables were corrected and inter-rater validation improved. However, "hypoglycemia" was not corrected, remaining an issue.
conclusionsData extraction without validation procedures, especially categorical variables using International Classification of Diseases-9 (ICD-9) codes, often results in incorrect data identification. Electronically extracted data must incorporate built-in validating processes.
Indexed as
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Registered trials
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