ArticleApplied clinical informatics2020
Detection and Remediation of Misidentification Errors in Radiology Examination Ordering.
Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Wrong-side imaging orders: automated detection using electronic health record data - a retrospective cohort study.BMJ open quality · 2026Article
- Detecting Laterality Errors in Combined Radiographic Studies by Enhancing the Traditional Approach With GPT-4o: Algorithm Development and Multisite Internal Validation.JMIR formative research · 2025Article
- Blind spots in brain imaging: a pictorial essay.Quantitative imaging in medicine and surgery · 2025Review
- Article
- Diagnostic error and bias in the department of radiology: a pictorial essay.Insights into imaging · 2023Review
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundDespite progress in patient safety, misidentification errors in radiology such as ordering imaging on the wrong anatomic side persist. If undetected, these errors can cause patient harm for multiple reasons, in addition to producing erroneous electronic health records (EHR) data.
objectivesWe describe the pilot testing of a quality improvement methodology using electronic trigger tools and preimaging checklists to detect "wrong-side" misidentification errors in radiology examination ordering, and to measure staff adherence to departmental policy in error remediation.
methodsWe retrospectively applied and compared two methods for the detection of "wrong-side" misidentification errors among a cohort of all imaging studies ordered during a 1-year period (June 1, 2015-May 31, 2016) at our tertiary care hospital. Our methods included: (1) manual review of internal quality improvement spreadsheet records arising from the prospective performance of preimaging safety checklists, and (2) automated error detection via the development and validation of an electronic trigger tool which identified discrepant side indications within EHR imaging orders.
resultsOur combined methods detected misidentification errors in 6.5/1,000 of study cohort imaging orders. Our trigger tool retrospectively identified substantially more misidentification errors than were detected prospectively during preimaging checklist performance, with a high positive predictive value (PPV: 88.4%, 95% confidence interval: 85.4-91.4). However, two third of errors detected during checklist performance were not detected by the trigger tool, and checklist-detected errors were more often appropriately resolved (
conclusionOur trigger tool enabled the detection of substantially more imaging ordering misidentification errors than preimaging safety checklists alone, with a high PPV. Many errors were only detected by the preimaging checklist; however, suggesting that additional trigger tools may need to be developed and used in conjunction with checklist-based methods to ensure patient safety.
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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.