Background: This report provides a comprehensive analysis of transfusion errors occurring at a large teaching hospital and aims to determine key errors that are threatening transfusion safety, despite implementation of safety measures.
Study Design And Methods: Errors were prospectively identified from 2005 to 2010. Error data were coded on a secure online database called the Transfusion Error Surveillance System. Errors were defined as any deviation from established standard operating procedures. Errors were identified by clinical and laboratory staff. Denominator data for volume of activity were used to calculate rates.
Results: A total of 15,134 errors were reported with a median number of 215 errors per month (range, 85-334). Overall, 9083 (60%) errors occurred on the transfusion service and 6051 (40%) on the clinical services. In total, 23 errors resulted in patient harm: 21 of these errors occurred on the clinical services and two in the transfusion service. Of the 23 harm events, 21 involved inappropriate use of blood. Errors with no harm were 657 times more common than events that caused harm. The most common high-severity clinical errors were sample labeling (37.5%) and inappropriate ordering of blood (28.8%). The most common high-severity error in the transfusion service was sample accepted despite not meeting acceptance criteria (18.3%). The cost of product and component loss due to errors was $593,337.
Conclusion: Errors occurred at every point in the transfusion process, with the greatest potential risk of patient harm resulting from inappropriate ordering of blood products and errors in sample labeling.
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http://dx.doi.org/10.1111/trf.12240 | DOI Listing |
BMC Public Health
January 2025
Al-Barkaat Institute of Management Studies, Aligarh 202122, Dr. A. P. J. Abdul Kalam Technical University, Lucknow 226010, India.
Cardiovascular disease (CVD) is a leading cause of death and disability worldwide, and its incidence and prevalence are increasing in many countries. Modeling of CVD plays a crucial role in understanding the trend of CVD death cases, evaluating the effectiveness of interventions, and predicting future disease trends. This study aims to investigate the modeling and forecasting of CVD mortality, specifically in the Sindh province of Pakistan.
View Article and Find Full Text PDFSurg Endosc
January 2025
Surgery Department, Meander Medical Centre, Maatweg, Amersfoort, 3818 TZ, Utrecht, The Netherlands.
Background: Specific pelvic bone dimensions have been identified as predictors of total mesorectal excision (TME) difficulty and outcomes. However, manual measurement of these dimensions (pelvimetry) is labor intensive and thus, anatomic criteria are not included in the pre-operative difficulty assessment. In this work, we propose an automated workflow for pelvimetry based on pre-operative magnetic resonance imaging (MRI) volumes.
View Article and Find Full Text PDFCardiovasc Eng Technol
January 2025
Transonic Systems Inc., 34 Dutch Mill Road, Ithaca, New York, 14850, USA.
Purpose: Over time, transit time flow measurement (TTFM) has proven itself as a simple and effective tool for intra-operative evaluation of coronary artery bypass grafts (CABGs). However, metrics used to screen for possible technical error show considerable spread, preventing the definition of sharp cut-off values to distinguish between patent, questionable, and failed grafts. The simulation study presented in this paper aims to quantify this uncertainty for commonly used patency metrics, and to identify the most important physiological parameters influencing it.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Signal Theory and Communications, Universidad de Valladolid, 47002, Valladolid, Spain.
Sound-based uroflowmetry (SU) offers a non-invasive alternative to traditional uroflowmetry (UF) for evaluating lower urinary tract dysfunctions, enabling home-based testing and reducing the need for clinic visits. This study compares SU and UF in estimating urine flow rate and voided volume in 50 male volunteers (aged 18-60), with UF results from a Minze uroflowmeter as the reference standard. Audio signals recorded during voiding were segmented and machine learning algorithms (gradient boosting, random forest, and support vector machine) estimated flow parameters from three devices: Ultramic384k, Mi A1 smartphone, and Oppo smartwatch.
View Article and Find Full Text PDFJ Cancer Surviv
January 2025
School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.
Purpose: This study aimed to evaluate the prevalence and predictors of frailty and the association between frailty and neurocognitive impairments among Chinese survivors of childhood cancer.
Methods: A total of 185 survivors of childhood cancer were recruited from a long-term follow-up clinic in Hong Kong (response rate: 94.4%; 48.
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