Heart Error Producing Conditions
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the field of human reliability assessment (HRA), for the purposes of evaluating the probability of a human error occurring throughout the completion human error heart methodology of a specific task. From such analyses measures can then
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be taken to reduce the likelihood of errors occurring within a system and therefore lead to an human error analysis pdf improvement in the overall levels of safety. There exist three primary reasons for conducting an HRA; error identification, error quantification and error reduction. As there exist
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a number of techniques used for such purposes, they can be split into one of two classifications; first generation techniques and second generation techniques. First generation techniques work on the basis of the simple dichotomy of ‘fits/doesn’t fit’ in the matching of the error situation in context with related error identification and quantification and human error analysis examples second generation techniques are more theory based in their assessment and quantification of errors. ‘HRA techniques have been utilised in a range of industries including healthcare, engineering, nuclear, transportation and business sector; each technique has varying uses within different disciplines. HEART method is based upon the principle that every time a task is performed there is a possibility of failure and that the probability of this is affected by one or more Error Producing Conditions (EPCs) – for instance: distraction, tiredness, cramped conditions etc. – to varying degrees. Factors which have a significant effect on performance are of greatest interest. These conditions can then be applied to a “best-case-scenario” estimate of the failure probability under ideal conditions to then obtain a final error chance. This figure assists in communication of error chances with the wider risk analysis or safety case. By forcing consideration of the EPCs potentially affecting a given procedure, HEART also has the indirect effect of providing
DataSetsGEO ProfilesGSSGTRHomoloGeneMedGenMeSHNCBI Web SiteNLM CatalogNucleotideOMIMPMCPopSetProbeProteinProtein ClustersPubChem BioAssayPubChem CompoundPubChem SubstancePubMedPubMed HealthSNPSparcleSRAStructureTaxonomyToolKitToolKitAllToolKitBookToolKitBookghUniGeneSearch termSearch Browse Titles Limits Advanced Help NCBI Bookshelf. A service of
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the National Library of Medicine, National Institutes of Health.Henriksen
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K, Battles JB, Keyes MA, et al., editors. Advances in Patient Safety: New Directions and human error analysis definition Alternative Approaches (Vol. 3: Performance and Tools). Rockville (MD): Agency for Healthcare Research and Quality (US); 2008 Aug. Advances in Patient Safety: New Directions https://en.wikipedia.org/wiki/Human_error_assessment_and_reduction_technique and Alternative Approaches (Vol. 3: Performance and Tools).Show detailsHenriksen K, Battles JB, Keyes MA, et al., editors.Rockville (MD): Agency for Healthcare Research and Quality (US); 2008 Aug.ContentsSearch term < PrevNext > Error Producing Conditions in the Intensive Care UnitFrank A. Drews, PhD, Adrian Musters, BS, and Matthew H. Samore, https://www.ncbi.nlm.nih.gov/books/NBK43691/ MD.Author InformationFrank A. Drews, PhD, Adrian Musters, BS, and Matthew H. Samore, MD.*Department of Psychology, University of Utah, Salt Lake City, UT (Dr. Drews and Mr. Musters); Informatics, Decision-Enhancement, and Surveillance Center, VA Salt Lake City Health Care System, Salt Lake City, UT (Dr. Drews and Dr. Samore); Clinical Epidemiology, School of Medicine, University of Utah, Salt Lake City, UT (Dr. Samore)*Address correspondence to: Frank A. Drews, Department of Psychology, University of Utah, 380 S 1530 E, Rm 502, Salt Lake City, UT 84112; Email: ude.hatu.hcysp@swerd.knarf.Up to 98,000 patients die because of human error in U.S. hospitals each year. Among the areas where errors occur frequently is the intensive care unit (ICU). Despite the impact of these errors, little research has identified the human factors that contribute to errors in the ICU. The current study uses the error-producing conditions (EPC) approach to help identify devi
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