Observational studyHealth services research2014
Using computer-extracted data from electronic health records to measure the quality of adolescent well-care.
Observational study in Health services research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Process analysis of the patient pathway for automated data collection: an exemplar using pituitary surgery.Frontiers in endocrinology · 2023Article
- Comparison of electronic versus manual abstraction for 2 standardized perinatal care measures.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Comparison of Performance on ADHD Quality of Care Indicators: Practitioner Self-Report Versus Chart Review.Journal of attention disorders · 2020Article
- Using Clinical Data Standards to Measure Quality: A New Approach.Applied clinical informatics · 2018Article
- A new era of quality measurement in rheumatology: electronic clinical quality measures and national registries.Current opinion in rheumatology · 2017Review
- Calculations of Financial Incentives for Providers in a Pay-for-Performance Program: Manual Review Versus Data From Structured Fields in Electronic Health Records.Medical care · 2015Article
- Statewide Hospital Discharge Data: Collection, Use, Limitations, and Improvements.Health services research · 2015Article
- "Salt in the Wound": Safety Net Clinician Perspectives on Performance Feedback Derived From EHR Data.The Journal of ambulatory care managementArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectiveTo determine whether quality measures based on computer-extracted EHR data can reproduce findings based on data manually extracted by reviewers. DATA SOURCES: We studied 12 measures of care indicated for adolescent well-care visits for 597 patients in three pediatric health systems. STUDY
designObservational study. DATA COLLECTION/EXTRACTION
methodsManual reviewers collected quality data from the EHR. Site personnel programmed their EHR systems to extract the same data from structured fields in the EHR according to national health IT standards. PRINCIPAL
findingsOverall performance measured via computer-extracted data was 21.9 percent, compared with 53.2 percent for manual data. Agreement measures were high for immunizations. Otherwise, agreement between computer extraction and manual review was modest (Kappa = 0.36) because computer-extracted data frequently missed care events (sensitivity = 39.5 percent). Measure validity varied by health care domain and setting. A limitation of our findings is that we studied only three domains and three sites.
conclusionsThe accuracy of computer-extracted EHR quality reporting depends on the use of structured data fields, with the highest agreement found for measures and in the setting that had the greatest concentration of structured fields. We need to improve documentation of care, data extraction, and adaptation of EHR systems to practice workflow.
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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.