SynthesisInternational journal of medical informatics2025
Error rates of data processing methods in clinical research: A systematic review and meta-analysis of manuscripts identified through PubMed.
Synthesis in International journal of medical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Family Health Conversations-A Short-Term Supportive Intervention to Improve Family Well-Being, Functioning, and Involvement in Care After Open-Heart Surgery: A Multicenter, Randomized, Parallel-Group Superiority Trial.Journal of family nursing · 2026Trial
- From Theory to Practice: GPT-Supported Data Extraction in Observational Studies on Transcatheter Aortic Valve Replacement.JACC. Advances · 2026Article
- Retracted Publications Related to Statistics: A Scopus-Based Bibliometric Analysis.Journal of Korean medical science · 2026Article
- A Computational Approach to Evaluating Empirical Antibiotic Coverage for Gram-Negative Bloodstream Infections in Pediatric Febrile Neutropenia.Antibiotics (Basel, Switzerland) · 2026Article
- Automated abstraction of clinical parameters of multiple myeloma from real-world clinical notes using large language models.BMC medical informatics and decision making · 2026Article
- Human level information extraction from clinical reports with finetuned language models.Scientific reports · 2025Article
- Large Language Model Versus Manual Review for Clinical Data Curation in Breast Cancer: Retrospective Comparative Study.JMIR medical informatics · 2025Article
- Article
- MedVidDeID: Protecting privacy in clinical encounter video recordings.Journal of biomedical informatics · 2025Article
- Automated structured data extraction from intraoperative echocardiography reports using large language models.British journal of anaesthesia · 2025Article
- Quality of registration of antenatal, intrapartum, and newborn information in the Georgian birth registry.Archives of public health = Archives belges de sante publique · 2024Article
- Comparing Medical Record Abstraction (MRA) error rates in an observational study to pooled rates identified in the data quality literature.BMC medical research methodology · 2024Observational
- Comparing Medical Record Abstraction (MRA) Error Rates in an Observational Study to Pooled Rates Identified in the Data Quality Literature.Research square · 2023Article
- Moving toward the digitalization of neuropsychological tests: An exploratory study on usability and operator perception.Digital healthArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundIn clinical research, prevention of data errors is paramount to ensuring reproducibility of trial results and the safety and efficacy of the resulting interventions. Over the last 40 years, empirical assessments of data accuracy in clinical research have been reported, however, there has been little systematic synthesis of these results. Although notable exceptions exist, little evidence exists regarding the relative accuracy of different data processing methods.
methodsA systematic review of the literature identified through PubMed was performed to identify studies that evaluated the quality of data obtained through data processing methods typically used in clinical trials. Quantitative information on data accuracy was abstracted from the manuscripts and pooled. Meta-analysis of single proportions based on the Freeman-Tukey transformation method and the generalized linear mixed model approach were used to derive an overall estimate of error rates across data processing methods used in each study for comparison.
resultsA total of 93 papers (published from 1978 to 2008) meeting our inclusion criteria were categorized according to their data processing methods. The accuracy associated with data processing methods varied widely, with error rates ranging from 2 errors per 10,000 fields to 2,784 errors per 10,000 fields. MRA was associated with both high and highly variable error rates, having a pooled error rate of 6.57% (95% CI: 5.51, 7.72). In comparison, the pooled error rates for optical scanning, single-data entry, and double-data entry methods were 0.74% (0.21, 1.60), 0.29% (0.24, 0.35) and 0.14% (0.08, 0.20), respectively.
conclusionsData processing methods may explain a significant amount of the variability in data accuracy. MRA error rates, for example, were high enough to impact decisions made using the data and could necessitate increases in sample sizes to preserve statistical power. Thus, the choice of data processing methods can likely impact process capability and, ultimately, the validity of trial results.
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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.