Objective: Our objective was to determine the extent surgical disciplines categorize, define, and study errors, then use this information to provide recommendations for both current practice and future study.
Summary Of Background Data: The report "To Err is Human" brought the ubiquity of medical errors to public attention. Variability in subsequent literature suggests the true prevalence of error remains unknown.
Methods: In January 2020, PubMed, the Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials were searched. Only studies with Oxford Level of Evidence Level 3 or higher were included.
Results: Of 3064 studies, 92 met inclusion criteria: 6 randomized controlled trials, 4 systematic reviews, 24 cohort, 10 before-after, 35 outcome/audit, 5 cross sectional and 8 case-control studies. Over 15,933,430 patients and 162,113 errors were represented. There were 6 broad error categories, 13 different definitions of error, and 14 study methods.
Conclusions: Reported prevalence of error varied widely due to a lack of standardized categorization, definitions, and study methods. Future research should focus on immediately recognizing errors to minimize harm.
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http://dx.doi.org/10.1097/SLA.0000000000005351 | DOI Listing |
BMC Pediatr
January 2025
Department of Research, School of Graduate studies, Research and Innovations, Clarke International University, Kampala, P.O. Box 7782, Uganda.
Background: Anaemia is a major cause of morbidity among children under five years in Uganda. However, its magnitude among refugee populations is marginally documented. In this study, the prevalence and contributors to anaemia among children 6 to 59 months in Kyangwali refugee settlement in Western Uganda was determined.
View Article and Find Full Text PDFAm J Geriatr Psychiatry
December 2024
Department of Clinical and Experimental Sciences (DA, BB), University of Brescia, Brescia, Italy; Molecular Markers Laboratory (BB), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address:
Objectives: The present study aims to assess the prevalence, associated clinical symptoms, longitudinal changes, and imaging correlates of Loss of Insight (LOI), which is still unexplored in syndromes associated with Frontotemporal Lobar Degeneration (FTLD).
Design: Retrospective longitudinal cohort study, from Oct 2009 to Feb 2023.
Setting: Tertiary Frontotemporal Dementia research clinic.
BMJ Open Qual
December 2024
School of Medicine, Saint Joseph University School of Medical Science, Beirut, Lebanon.
Objective: The aim of this study is to identify the key barriers that prevent medication administration errors (MAEs) from being reported by nurses in Lebanese hospitals.
Methods: A quantitative cross-sectional study was conducted at Hotel-Dieu de France Hospital using a self-administered questionnaire. A total of 275 responses were recorded and analysed using the IBM SPSS software V.
BMJ Open Ophthalmol
December 2024
Ophthalmology, Royal Hospital for Children, Glasgow, UK.
Background: Very premature infants screened for retinopathy of prematurity (ROP) that do not develop ROP still experience serious visual developmental challenges, and while it is recommended that all children in the UK are offered preschool visual screening, we aimed to explore whether this vulnerable group requires dedicated follow-up.
Methods: We performed a real-world retrospective observational cohort study of children previously screened for ROP in NHS Greater Glasgow and Clyde (Scotland) between 2013 and 2015. We excluded those with any severity of ROP identified during screening.
Clin Chem
January 2025
Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States.
Background: Multianalyte machine learning (ML) models can potentially identify previously undetectable wrong blood in tube (WBIT) errors, improving upon current single-analyte delta check methodology. However, WBIT detection model performance has not been assessed in a real-world, low-prevalence context. To estimate real-world positive predictive values, we propose a methodology to assess WBIT detection models by evaluating the impact of missing data and by using a "low prevalence" validation data set.
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