Literature DB >> 21050197

Classifying nursing errors in clinical management within an Australian hospital.

D T Tran1, M Johnson.   

Abstract

BACKGROUND: Although many classification systems relating to patient safety exist, no taxonomy was identified that classified nursing errors in clinical management. AIMS: To develop a classification system for nursing errors relating to clinical management (NECM taxonomy) and to describe contributing factors and patient consequences.
METHODS: We analysed 241 (11%) self-reported incidents relating to clinical management in nursing in a metropolitan hospital. Descriptive analysis of numeric data and content analysis of text data were undertaken to derive the NECM taxonomy, contributing factors and consequences for patients.
RESULTS: Clinical management incidents represented 1.63 incidents per 1000 occupied bed days. The four themes of the NECM taxonomy were nursing care process (67%), communication (22%), administrative process (5%), and knowledge and skill (6%). Half of the incidents did not cause any patient harm. Contributing factors (n=111) included the following: patient clinical, social conditions and behaviours (27%); resources (22%); environment and workload (18%); other health professionals (15%); communication (13%); and nurse's knowledge and experience (5%).
CONCLUSION: The NECM taxonomy provides direction to clinicians and managers on areas in clinical management that are most vulnerable to error, and therefore, priorities for system change management. Any nurses who wish to classify nursing errors relating to clinical management could use these types of errors. This study informs further research into risk management behaviour, and self-assessment tools for clinicians. Globally, nurses need to continue to monitor and act upon patient safety issues.
© 2010 The Authors. International Nursing Review © 2010 International Council of Nurses.

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Year:  2010        PMID: 21050197     DOI: 10.1111/j.1466-7657.2010.00846.x

Source DB:  PubMed          Journal:  Int Nurs Rev        ISSN: 0020-8132            Impact factor:   2.871


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