| Issue |
MATEC Web Conf.
Volume 192, 2018
The 4th International Conference on Engineering, Applied Sciences and Technology (ICEAST 2018) “Exploring Innovative Solutions for Smart Society”
|
|
|---|---|---|
| Article Number | 01051 | |
| Number of page(s) | 4 | |
| Section | Track 1: Industrial Engineering, Materials and Manufacturing | |
| DOI | https://doi.org/10.1051/matecconf/201819201051 | |
| Published online | 14 August 2018 | |
The performance improvement of look-alike sound-alike drug pre-dispensing
1
Department of Industrial Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand
2
Center for Innovation in Human Factors Engineering and Ergonomics (CIHFE^2), Department of Industrial Engineering, Faculty of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand
*
Corresponding author : kjmanutc@kmitl.ac.th
Medical dispensing errors are common and classic human errors in the hospitals. Look-alike, Sound-alike (LASA) drug is one of the main issues in pre-dispensing and dispensing processes. The data in this study were observed from one middle size hospital in Thailand. In 2017, there were two months that the medication errors KPI (0.065 and 0.061) were greater than the accepted error threshold (0.06). The SBAR (Situation, Background, Assessment, and Recommendation) solution and HOSxP software were applied for three months in the pre-dispensing process to reduce the medical dispensing errors. The results showed that the medication errors KPI (0.04, 0.03, and 0.02, respectively) were reduced dramatically. Therefore, implementation of the SBAR and HOSxP software is recommended as a fast and easy solution for medical dispensing errors.
Key words: LASA / Human errors / Pre-dispensing process
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.