ArticleBMJ open2013
Error rates in a clinical data repository: lessons from the transition to electronic data transfer--a descriptive study.
Article in BMJ open, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Trial
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- A Computational Approach to Evaluating Empirical Antibiotic Coverage for Gram-Negative Bloodstream Infections in Pediatric Febrile Neutropenia.Antibiotics (Basel, Switzerland) · 2026Article
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- Comparison of precision of a paperless electronic input method versus the conventional paper form in an andrology laboratory: a prospective study.Basic and clinical andrology · 2025Article
- Rakeiora Genomics Platform: a pathfinder for genomic medicine research in Aotearoa New Zealand.Journal of the Royal Society of New Zealand · 2025Article
- A pragmatic methodology to extract anesthetic and physiological data from the electronic health record.Paediatric anaesthesia · 2024Article
- Local Validation of a National Orthopaedic Registry.Cureus · 2024Article
- Clinical Data Warehousing: A Scoping Review.Journal of the Society for Clinical Data Management · 2024Article
- Impact of Clinical Data Veracity on Cancer Genomic Research.JNCI cancer spectrum · 2022Article
- Inaccurate recording of routinely collected data items influences identification of COVID-19 patients.International journal of medical informatics · 2022Article
- Determining a minimum set of variables for machine learning cardiovascular event prediction: results from REFINE SPECT registry.Cardiovascular research · 2022Article
- Proximal humerus fractures: epidemiology and trends in surgical management of hospital-admitted patients in Portugal.JSES international · 2022Article
- Digital media archive for gross pathology images based on open-source tools and Fast Healthcare Interoperability Resources (FHIR).Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveData errors are a well-documented part of clinical datasets as is their potential to confound downstream analysis. In this study, we explore the reliability of manually transcribed data across different pathology fields in a prostate cancer database and also measure error rates attributable to the source data.
designDescriptive study.
settingSpecialist urology service at a single centre in metropolitan Victoria in Australia.
participantsBetween 2004 and 2011, 1471 patients underwent radical prostatectomy at our institution. In a large proportion of these cases, clinicopathological variables were recorded by manual data-entry. In 2011, we obtained electronic versions of the same printed pathology reports for our cohort. The data were electronically imported in parallel to any existing manual entry record enabling direct comparison between them. OUTCOME MEASURES: Error rates of manually entered data compared with electronically imported data across clinicopathological fields.
results421 patients had at least 10 comparable pathology fields between the electronic import and manual records and were selected for study. 320 patients had concordant data between manually entered and electronically populated fields in a median of 12 pathology fields (range 10-13), indicating an outright accuracy in manually entered pathology data in 76% of patients. Across all fields, the error rate was 2.8%, while individual field error ranges from 0.5% to 6.4%. Fields in text formats were significantly more error-prone than those with direct measurements or involving numerical figures (p<0.001). 971 cases were available for review of error within the source data, with figures of 0.1-0.9%.
conclusionsWhile the overall rate of error was low in manually entered data, individual pathology fields were variably prone to error. High-quality pathology data can be obtained for both prospective and retrospective parts of our data repository and the electronic checking of source pathology data for error is feasible.
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