Risk assessment of look‒alike, sound‒alike (LASA) medication errors in an Italian hospital pharmacy: A model based on the ‘Failure Mode and Effect Analysis’
Journal Title: Journal of Health and Social Sciences - Year 2017, Vol 2, Issue 1
Abstract
Introduction: Look alike/sound alike (LASA) drugs errors can take place in hospital wards, and they can place patients at risk for adverse events and death. This study was aimed to realize a risk assessment model for preventing LASA drugs distribution errors by the ‘S.Giovanni di Dio e Ruggi d’Aragona’ hospital pharmacy, in Salerno, Italy. Methods: We used the ‘Failure Mode and Effect Analysis’ (FMEA) technique in combination with the Recommendations released by the Italian Ministry of Health in 2010. Our analysis led to the identification of the potential failure modes, together with their causes and effects, using the risk priority number (RPN) scoring system. A paired T test was used to compare means of RPN 1 and RPN 2, respectively before and after their application, in order to evaluate the effectiveness of corrective actions. Results: In total, 6 phases, 16 steps, and 13 different potential failure modes were identified. The highest ranked failure modes, with an RPN score of 48 pertained to wrong drug dosage selection. Some of the critical failure modes in sample processing (phases n.1, 2, 3, and 4) were improved by 69.7% in the RPN by focusing on automated technology systems. T test showed that the difference between RPN 1 and RPN 2 was statistically significant for all corrective measures provided by our action plan. Conclusions: Our study showed a lot of potential failure modes related to LASA drugs distribution system provided by the hospital pharmacy. Information technology solutions can be effective to reduce this risk, but the potential for error will remain unless these systems are carefully implemented.
Authors and Affiliations
Nestor Ciociano, Lucilla Grisi, Lucia Bagnasco, Maria Giovanna Elberti, Marcello Mazzarella
Keywords
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- EP ID EP216266
- DOI 10.19204/2017/rsks4
- Views 119
- Downloads 0
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