ArticlePediatric quality & safety
Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality.
Article in Pediatric quality & safety. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 7 citations in OpenAlex.
- Profile of Chief Medical Officers and performance of health zones in crisis contexts: a cross-sectional study in three provinces of the Eastern Democratic Republic of Congo.Human resources for health · 2025Article
- Mentorship to strengthen health system leadership: A case study of the Walungu rural health zone in the eastern Democratic Republic of Congo.PLOS global public health · 2024Article
- Peripartum women's perspectives on research study participation in the OneFlorida Clinical Research Consortium during COVID-19 pandemic.Journal of clinical and translational science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors at 6 institutions in 1 country.
Funding
Abstract
introductionHealth systems spend $1.5 billion annually reporting data on quality, but efficacy and utility for benchmarking are limited due, in part, to limitations of data sources. Our objective was to implement and evaluate measures of pediatric quality for three conditions using electronic health record (EHR)-derived data.
methodsPCORnet networks standardized EHR-derived data to a common data model. In 13 health systems from 2 networks for 2015, we implemented the National Quality Forum measures: % children with sickle cell anemia who received a transcranial Doppler; % children on antipsychotics who had metabolic screening; and % pediatric acute otitis media with amoxicillin prescribed. Manual chart review assessed measure accuracy.
resultsOnly 39% (N = 2,923) of 7,278 children on antipsychotics received metabolic screening (range: 20%-54%). If the measure indicated screening was performed, the chart agreed 88% of the time [95% confidence interval (CI): 81%-94%]; if it indicated screening was not done, the chart agreed 86% (95% CI: 78%-93%). Only 69% (N = 793) of 1,144 children received transcranial Doppler screening (range across sites: 49%-88%). If the measure indicated screening was performed, the chart agreed 98% of the time (95% CI: 94%-100%); if it indicated screening was not performed, the chart agreed 89% (95% CI: 82%-95%). For acute otitis media, chart review identified many qualifying cases missed by the National Quality Forum measure, which excluded a common diagnostic code.
conclusionsMeasures of healthcare quality developed using EHR-derived data were valid and identified wide variation among network sites. This data can facilitate the identification and spread of best practices.
Identifiers
What OpenQuestion holds
Registered trials
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.