Background: Despite 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.

Objectives: We 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.

Methods: We 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.

Results: Our 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 ( < 0.00001, 95% confidence interval: 2.0-6.9; odds ratio: 3.6).

Conclusion: Our 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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989264PMC
http://dx.doi.org/10.1055/s-0039-3402730DOI Listing

Publication Analysis

Top Keywords

misidentification errors
24
errors radiology
12
trigger tool
12
errors
9
radiology examination
8
examination ordering
8
quality improvement
8
electronic trigger
8
"wrong-side" misidentification
8
cohort imaging
8

Similar Publications

Objectives: Artificial intelligence (AI) software including Brainomix "e-CTA" which detect large vessel occlusions (LVO) have clinical potential. We hypothesised that in real world use where prevalence is low, its clinical utility may be overstated.

Methods: In this single centre retrospective service evaluation project, data sent to Brainomix from a medium size acute National Health Service (NHS) Trust hospital between 1/3/2022-1/3/2023 was reviewed.

View Article and Find Full Text PDF

Optimizing automated photo identification for population assessments.

Conserv Biol

January 2025

Marine Mammal Research Program, Hawai'i Institute of Marine Biology, University of Hawai'i at Mānoa, Kāne'ohe, Hawai'i, USA.

Several legal acts mandate that management agencies regularly assess biological populations. For species with distinct markings, these assessments can be conducted noninvasively via capture-recapture and photographic identification (photo-ID), which involves processing considerable quantities of photographic data. To ease this burden, agencies increasingly rely on automated identification (ID) algorithms.

View Article and Find Full Text PDF

Checklist for the insect fauna of two East Sea Islands (Ulleungdo Is. and Dokdo Is.) in the Republic of Korea.

Biodivers Data J

December 2024

Department of Biology, College of Natural Sciences, Kyungpook National University, Daegu, Republic of Korea Department of Biology, College of Natural Sciences, Kyungpook National University Daegu Republic of Korea.

Background: Ulleungdo and Dokdo, located in the East Sea, are volcanic islands with high ecological value due to their unique biodiversity. Although research on the insect fauna on these two Islands has been conducted from the early 19 century to recent times, limitations exist due to several issues, including misidentifications and historical errors. This study addresses these issues by conducting a comprehensive insect survey from 2020 to 2023, re-identifying misidentified specimens and compiling references to create an updated and accurate checklist of insect species for Ulleungdo and Dokdo.

View Article and Find Full Text PDF

Nudges may improve hazard perception in a contextual manner.

Accid Anal Prev

March 2025

Department of Management, Bar Ilan University, Ramat-Gan 52900, Israel.

This research investigates the effectiveness of nudge presentation on Hazard Perception (HP) during a computerized Hazard Perception Test (HPT). Three types of nudges were examined: Reminder, Social Norm, and Negative Reinforcement. Their effects on drivers' reaction times, hazard misidentifications (errors), and hazard recognition failures (misses) were analyzed.

View Article and Find Full Text PDF

Resolving severely overlapping ion mobility peaks using enhanced Fourier self-deconvolution.

Anal Methods

January 2025

State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190, P. R. China.

Fourier self-deconvolution is an effective method for resolving overlapping spectra. However, the selection of the half-width for the deconvolving function is often subjective, which can lead to either excessive convolution or insufficient resolution enhancement. Additionally, ion mobility peaks exhibit tailing effects, which may be misinterpreted as new peaks when the deconvolving function is modelled with a Gaussian function.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!