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What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system
OBJECTIVES: To (i) compare medication errors identified at audit and observation with medication incident reports; (ii) identify differences between two hospitals in incident report frequency and medication error rates; (iii) identify prescribing error detection rates by staff. DESIGN: Audit of 3291...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4340271/ https://www.ncbi.nlm.nih.gov/pubmed/25583702 http://dx.doi.org/10.1093/intqhc/mzu098 |
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author | Westbrook, Johanna I. Li, Ling Lehnbom, Elin C. Baysari, Melissa T. Braithwaite, Jeffrey Burke, Rosemary Conn, Chris Day, Richard O. |
author_facet | Westbrook, Johanna I. Li, Ling Lehnbom, Elin C. Baysari, Melissa T. Braithwaite, Jeffrey Burke, Rosemary Conn, Chris Day, Richard O. |
author_sort | Westbrook, Johanna I. |
collection | PubMed |
description | OBJECTIVES: To (i) compare medication errors identified at audit and observation with medication incident reports; (ii) identify differences between two hospitals in incident report frequency and medication error rates; (iii) identify prescribing error detection rates by staff. DESIGN: Audit of 3291patient records at two hospitals to identify prescribing errors and evidence of their detection by staff. Medication administration errors were identified from a direct observational study of 180 nurses administering 7451 medications. Severity of errors was classified. Those likely to lead to patient harm were categorized as ‘clinically important’. SETTING: Two major academic teaching hospitals in Sydney, Australia. MAIN OUTCOME MEASURES: Rates of medication errors identified from audit and from direct observation were compared with reported medication incident reports. RESULTS: A total of 12 567 prescribing errors were identified at audit. Of these 1.2/1000 errors (95% CI: 0.6–1.8) had incident reports. Clinically important prescribing errors (n = 539) were detected by staff at a rate of 218.9/1000 (95% CI: 184.0–253.8), but only 13.0/1000 (95% CI: 3.4–22.5) were reported. 78.1% (n = 421) of clinically important prescribing errors were not detected. A total of 2043 drug administrations (27.4%; 95% CI: 26.4–28.4%) contained ≥1 errors; none had an incident report. Hospital A had a higher frequency of incident reports than Hospital B, but a lower rate of errors at audit. CONCLUSIONS: Prescribing errors with the potential to cause harm frequently go undetected. Reported incidents do not reflect the profile of medication errors which occur in hospitals or the underlying rates. This demonstrates the inaccuracy of using incident frequency to compare patient risk or quality performance within or across hospitals. New approaches including data mining of electronic clinical information systems are required to support more effective medication error detection and mitigation. |
format | Online Article Text |
id | pubmed-4340271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-43402712015-03-10 What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system Westbrook, Johanna I. Li, Ling Lehnbom, Elin C. Baysari, Melissa T. Braithwaite, Jeffrey Burke, Rosemary Conn, Chris Day, Richard O. Int J Qual Health Care Papers OBJECTIVES: To (i) compare medication errors identified at audit and observation with medication incident reports; (ii) identify differences between two hospitals in incident report frequency and medication error rates; (iii) identify prescribing error detection rates by staff. DESIGN: Audit of 3291patient records at two hospitals to identify prescribing errors and evidence of their detection by staff. Medication administration errors were identified from a direct observational study of 180 nurses administering 7451 medications. Severity of errors was classified. Those likely to lead to patient harm were categorized as ‘clinically important’. SETTING: Two major academic teaching hospitals in Sydney, Australia. MAIN OUTCOME MEASURES: Rates of medication errors identified from audit and from direct observation were compared with reported medication incident reports. RESULTS: A total of 12 567 prescribing errors were identified at audit. Of these 1.2/1000 errors (95% CI: 0.6–1.8) had incident reports. Clinically important prescribing errors (n = 539) were detected by staff at a rate of 218.9/1000 (95% CI: 184.0–253.8), but only 13.0/1000 (95% CI: 3.4–22.5) were reported. 78.1% (n = 421) of clinically important prescribing errors were not detected. A total of 2043 drug administrations (27.4%; 95% CI: 26.4–28.4%) contained ≥1 errors; none had an incident report. Hospital A had a higher frequency of incident reports than Hospital B, but a lower rate of errors at audit. CONCLUSIONS: Prescribing errors with the potential to cause harm frequently go undetected. Reported incidents do not reflect the profile of medication errors which occur in hospitals or the underlying rates. This demonstrates the inaccuracy of using incident frequency to compare patient risk or quality performance within or across hospitals. New approaches including data mining of electronic clinical information systems are required to support more effective medication error detection and mitigation. Oxford University Press 2015-02 2015-01-12 /pmc/articles/PMC4340271/ /pubmed/25583702 http://dx.doi.org/10.1093/intqhc/mzu098 Text en © The Author 2015. Published by Oxford University Press in association with the International Society for Quality in Health Care. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Papers Westbrook, Johanna I. Li, Ling Lehnbom, Elin C. Baysari, Melissa T. Braithwaite, Jeffrey Burke, Rosemary Conn, Chris Day, Richard O. What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system |
title | What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system |
title_full | What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system |
title_fullStr | What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system |
title_full_unstemmed | What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system |
title_short | What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system |
title_sort | what are incident reports telling us? a comparative study at two australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system |
topic | Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4340271/ https://www.ncbi.nlm.nih.gov/pubmed/25583702 http://dx.doi.org/10.1093/intqhc/mzu098 |
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