Observational studyBMC medical research methodology2024
Comparing Medical Record Abstraction (MRA) error rates in an observational study to pooled rates identified in the data quality literature.
Observational study in BMC medical research methodology, 2024. 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
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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.
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Who cites it
3 citing papers in PubMed.
- From Theory to Practice: GPT-Supported Data Extraction in Observational Studies on Transcatheter Aortic Valve Replacement.JACC. Advances · 2026Article
- Performance of large language models for extracting clinical data from breast cancer pathology reports: a systematic review.NPJ digital medicine · 2026Article
- Measuring the Coverage of the HL7® FHIR® Standard in Supporting Data Acquisition for 3 Public Health Registries.Journal of medical systems · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundMedical record abstraction (MRA) is a commonly used method for data collection in clinical research, but is prone to error, and the influence of quality control (QC) measures is seldom and inconsistently assessed during the course of a study. We employed a novel, standardized MRA-QC framework as part of an ongoing observational study in an effort to control MRA error rates. In order to assess the effectiveness of our framework, we compared our error rates against traditional MRA studies that had not reported using formalized MRA-QC methods. Thus, the objective of this study was to compare the MRA error rates derived from the literature with the error rates found in a study using MRA as the sole method of data collection that employed an MRA-QC framework.
methodsA comparison of the error rates derived from MRA-centric studies identified as part of a systematic literature review was conducted against those derived from an MRA-centric study that employed an MRA-QC framework to evaluate the effectiveness of the MRA-QC framework. An inverse variance-weighted meta-analytical method with Freeman-Tukey transformation was used to compute pooled effect size for both the MRA studies identified in the literature and the study that implemented the MRA-QC framework. The level of heterogeneity was assessed using the Q-statistic and Higgins and Thompson's I
resultsThe overall error rate from the MRA literature was 6.57%. Error rates for the study using our MRA-QC framework were between 1.04% (optimistic, all-field rate) and 2.57% (conservative, populated-field rate), 4.00-5.53% points less than the observed rate from the literature (p < 0.0001).
conclusionsReview of the literature indicated that the accuracy associated with MRA varied widely across studies. However, our results demonstrate that, with appropriate training and continuous QC, MRA error rates can be significantly controlled during the course of a clinical research study.
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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.