ReviewInternational journal of preventive medicine2023
Application of "Human Factor Analysis and Classification System" (HFACS) Model to the Prevention of Medical Errors and Adverse Events: A Systematic Review.
Review in International journal of preventive medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Health Information Technology-Related Loss of Central Surveillance Data in a Heart Intensive Care Unit: Multi-Framework Case Report.JMIR human factors · 2026Article
- Artificial intelligence-based incident analysis and learning system to enhance patient safety and improve treatment quality.NPJ digital medicine · 2026Article
- Patient misidentification and data integrity risks in ultrasound imaging: a case report using multi-framework incident analysis.Frontiers in health services · 2026Article
- A potentially lifesaving error: unintentional high-dose adrenaline administration in anaphylaxis-induced cardiac arrest; a case report.International journal of emergency medicine · 2024Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hospitals, as one of most important subsectors in human societies, are responsible for providing safe and effective medical services to clients. But sometimes these hospitals are the source of injury and death in patients by creating medical errors. In this systematic review study, the application of human factor analysis and classification system (HFACS) method in the classification of medical errors was investigated. Major electronic databases including Scopus, Web of Science, and MEDLINE were searched. All studies that investigated the application of HFACS method for coding, causation, and classification of medical errors and adverse events conducted from 2001 until February 2021 were included. A total of 108 articles were found. Due to duplication, 18 studies were removed from the review list. After reading the titles and abstracts, 50 of these publications were excluded because they had objectives different from this review. The remaining 40 publications were retrieved for further assessment. Of these, 28 publications were excluded because it did not meet the inclusion criteria. Finally, 12 articles remained for the final systematic review. We found that in 65% of the selected studies, preconditions for unsafe acts have been the major causal level of medical errors and adverse events. In the majority of the studies, communication and coordination, adverse mental states, physical environment, crew resource management, and technological environment have also been recognized as the most important causal categories in this study. As a result, to prevent medical errors and adverse events, the main focus should be on controlling the preconditions for unsafe acts including personnel factors, operator conditions, and environmental factors.
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Registered trials
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