BACKGROUND: Until recently, the preparation of paediatric parenteral nutrition formulations in our institution included re-transcription and manual compounding of the mixture. Although no significant clinical problems have occurred, re-engineering of this high risk activity was undertaken to improve its safety. Several changes have been implemented including new prescription software, direct recording on a server, automatic printing of the labels, and creation of a file used to pilot a BAXA MM 12 automatic compounder. The objectives of this study were to compare the risks associated with the old and new processes, to quantify the improved safety with the new process, and to identify the major residual risks. METHODS: A failure modes, effects, and criticality analysis (FMECA) was performed by a multidisciplinary team. A cause-effect diagram was built, the failure modes were defined, and the criticality index (CI) was determined for each of them on the basis of the likelihood of occurrence, the severity of the potential effect, and the detection probability. The CIs for each failure mode were compared for the old and new processes and the risk reduction was quantified. RESULTS: The sum of the CIs of all 18 identified failure modes was 3415 for the old process and 1397 for the new (reduction of 59%). The new process reduced the CIs of the different failure modes by a mean factor of 7. The CI was smaller with the new process for 15 failure modes, unchanged for two, and slightly increased for one. The greatest reduction (by a factor of 36) concerned re-transcription errors, followed by readability problems (by a factor of 30) and chemical cross contamination (by a factor of 10). The most critical steps in the new process were labelling mistakes (CI 315, maximum 810), failure to detect a dosage or product mistake (CI 288), failure to detect a typing error during the prescription (CI 175), and microbial contamination (CI 126). CONCLUSIONS: Modification of the process resulted in a significant risk reduction as shown by risk analysis. Residual failure opportunities were also quantified, allowing additional actions to be taken to reduce the risk of labelling mistakes. This study illustrates the usefulness of prospective risk analysis methods in healthcare processes. More systematic use of risk analysis is needed to guide continuous safety improvement of high risk activities.
BACKGROUND: Until recently, the preparation of paediatric parenteral nutrition formulations in our institution included re-transcription and manual compounding of the mixture. Although no significant clinical problems have occurred, re-engineering of this high risk activity was undertaken to improve its safety. Several changes have been implemented including new prescription software, direct recording on a server, automatic printing of the labels, and creation of a file used to pilot a BAXA MM 12 automatic compounder. The objectives of this study were to compare the risks associated with the old and new processes, to quantify the improved safety with the new process, and to identify the major residual risks. METHODS: A failure modes, effects, and criticality analysis (FMECA) was performed by a multidisciplinary team. A cause-effect diagram was built, the failure modes were defined, and the criticality index (CI) was determined for each of them on the basis of the likelihood of occurrence, the severity of the potential effect, and the detection probability. The CIs for each failure mode were compared for the old and new processes and the risk reduction was quantified. RESULTS: The sum of the CIs of all 18 identified failure modes was 3415 for the old process and 1397 for the new (reduction of 59%). The new process reduced the CIs of the different failure modes by a mean factor of 7. The CI was smaller with the new process for 15 failure modes, unchanged for two, and slightly increased for one. The greatest reduction (by a factor of 36) concerned re-transcription errors, followed by readability problems (by a factor of 30) and chemical cross contamination (by a factor of 10). The most critical steps in the new process were labelling mistakes (CI 315, maximum 810), failure to detect a dosage or product mistake (CI 288), failure to detect a typing error during the prescription (CI 175), and microbial contamination (CI 126). CONCLUSIONS: Modification of the process resulted in a significant risk reduction as shown by risk analysis. Residual failure opportunities were also quantified, allowing additional actions to be taken to reduce the risk of labelling mistakes. This study illustrates the usefulness of prospective risk analysis methods in healthcare processes. More systematic use of risk analysis is needed to guide continuous safety improvement of high risk activities.
Authors: Werner Horn; Christian Popow; Silvia Miksch; Lieselotte Kirchner; Andreas Seyfang Journal: Artif Intell Med Date: 2002-03 Impact factor: 5.326
Authors: Adam G Dunn; Mei-Sing Ong; Johanna I Westbrook; Farah Magrabi; Enrico Coiera; Wayne Wobcke Journal: J Am Med Inform Assoc Date: 2011-05-01 Impact factor: 4.497
Authors: Peter C Wierenga; Loraine Lie-A-Huen; Sophia E de Rooij; Niek S Klazinga; Henk-Jan Guchelaar; Susanne M Smorenburg Journal: Drug Saf Date: 2009 Impact factor: 5.606