Reduction in alert fatigue in an assisted electronic prescribing system, through the Lean Six Sigma methodology
Objective: To reduce the alert fatigue in our Assisted Electronic Prescribing System (AEPS), through the Lean Six Sigma (LSS) methodology. Method: An observational (transversal) and retrospective study, in a general hospital with 850 beds and AEPS. The LSS methodology was followed in order to eva...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2017-01-01
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| Series: | Farmacia Hospitalaria |
| Subjects: | |
| Online Access: | http://www.aulamedica.es/fh/pdf/10434.pdf |
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| Summary: | Objective: To reduce the alert fatigue in our Assisted Electronic Prescribing System (AEPS), through the Lean Six Sigma (LSS)
methodology. Method: An observational (transversal) and retrospective study, in a general hospital with 850 beds and AEPS. The LSS methodology was followed in order to evaluate the alert fatigue situation in the AEPS system, to implement improvements, and to assess outcomes. The alerts generated during two trimesters studied (before and after the intervention) were analyzed. In order to measure the qualitative indicators, the most frequent alert types were analyzed, as well as the molecules responsible for over 50% of each type of alert. The action by the prescriber was analyzed in a sample of 496 prescriptions that generated such alerts. For each type of alert and molecule, there was a prioritization of the improvements to be implemented according to the alert generated and its quality. A second survey evaluated the pharmacist action for the alerts most highly valued by physicians. Results: The problem, the objective, the work team and the project schedule were defined. A survey was designed in order to understand the opinion of the client about the alert system in the program. Based on the
surveys collected (n = 136), the critical characteristics and the quanti/qualitative indicators were defined. Sixty (60) fields in the alert system were modified, corresponding to 32 molecules, and this led to a 28% reduction in the total number of alerts. Regarding quality indicators, false po sitive results were reduced by 25% (p < 0.05), 100% of those alerts ignored with justification were sustained, and there were no significant differences in user adherence to the system. The project improvements and outcomes were reviewed by the work team. Conclusions: LSS methodology has demonstrated being a valid tool for the quantitative and qualitative improvement of the alert system in an Assisted Electronic Prescription Program, thus reducing alert fatigue |
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| ISSN: | 1130-6343 2171-8695 |