Background: Present-day radiology departments have very high footfall of patients and are prone to patient safety errors. This study analyses such errors in our hospital.
Methods: Observational cross-sectional analysis of errors over the last 30 months was performed. These were classified using the Eindhoven classification model into technical, organizational, and human errors. Technical errors focused on equipment safety. Organizational errors related to policies. Human errors were subclassified as per the skill rule knowledge model. Root cause analysis was performed wherever necessary, and possible mitigation strategies for ensuring safety were suggested. Errors peculiar to the Armed Forces environment were specifically addressed.
Results: Seventy-seven errors were analyzed. Two were equipment based including faulty pressure injector syringes and radiation leakage from the computed tomography gantry. Of 44 skill-based errors, 09 involved dispatch of wrong reports to dependents owing to identifying patients with serving personnel's name. Four were due to scanning wrong sites. Eleven involved reporting abnormality on the wrong side. Six involved underreporting due to not viewing specific images. The rest were due to failure to omit conflicting elements in the report. Rule-based errors included wrong protocol selection (9 errors), omitting a particular sequence due to individual preference (6 errors), and so on. Knowledge-based errors were due to misinterpretation of findings (4 errors), reporting an abnormality as normal (3 errors), and selection of wrong modality (3 errors).
Conclusion: The findings of this study highlights the importance of voluntary reporting, diligent recording, and in-depth analysis of errors for understanding the causes and formulating possible mitigation strategies.
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http://dx.doi.org/10.1016/j.mjafi.2020.09.006 | DOI Listing |
Biomed Phys Eng Express
January 2025
Advanced Nuclear Medicine Science, National Institute of Radiological Sciences, 4-9-1 Anagawa, Inage-ku, Chiba 263-8555, JAPAN, Chiba, 263-8555, JAPAN.
For brain-dedicated positron emission tomography (PET) scanners, depth-of-interaction (DOI) information is essential to achieve uniform spatial resolution across the field-of-view (FOV) by minimizing parallax error. Time-of-flight (TOF) information can enhance the image quality. In this study, we proposed a novel monolithic U-shaped crystal design that had a tapered geometry to achieve good coincidence timing resolution (CTR) and DOI resolution simultaneously.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Department of Psychology, The University of Texas at San Antonio, San Antonio, TX, United States.
Background: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions of these search patterns, which involve the physician verbalizing or annotating the order he or she analyzes the image, can be unreliable due to discrepancies in what is reported versus the actual visual patterns.
View Article and Find Full Text PDFGenet Test Mol Biomarkers
January 2025
PTC Therapeutics Germany GmbH, Frankfurt, Germany.
The main objective of this prospective, multicenter study (REVEAL-CP) was to test children with cerebral palsy-like signs and symptoms for raised 3--methyldopa (3-OMD) blood levels, a biomarker for aromatic L-amino acid decarboxylase deficiency (AADCd). A secondary objective was to characterize the molecular basis for the defective aromatic L-amino acid decarboxylase (AADC) gene product. Patients were identified in pediatric secondary and tertiary care hospitals through database searches and personal communication.
View Article and Find Full Text PDFJ Phys Chem B
January 2025
School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
Hydration free energy (HFE) of molecules is a fundamental property having importance throughout chemistry and biology. Calculation of the HFE can be challenging and expensive with classical molecular dynamics simulation-based approaches. Machine learning (ML) models are increasingly being used to predict HFE.
View Article and Find Full Text PDFPurpose: The light adjustable lens (LAL) (RxSight, Aliso Viejo, CA) is a premium intraocular lens that allows for correction of residual refractive error and astigmatism following implantation. Herein, we describe the surgical approach and evaluate the visual outcomes of patients following scleral fixation of the LAL.
Methods: Retrospective, single-surgeon surgical case series of 3 patients (3 eyes) with intraocular lens complications, who underwent combined pars plana vitrectomy and sutureless needle assisted intrascleral haptic fixation of the LAL between April 2022, to August 2023.
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