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The Effect of Blended Learning on the Rate of Medication Administration Errors of Nurses in Medical Wards
BACKGROUND: Medication error is one of the most important and most common events threatening patient safety. This study was conducted with the aim to determine the effect of asynchronous hybrid/blended learning on the rate of medication administration errors of nurses in medical wards. MATERIALS AND...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7968587/ https://www.ncbi.nlm.nih.gov/pubmed/33747843 http://dx.doi.org/10.4103/ijnmr.IJNMR_188_20 |
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author | Farzi, Kolsoum Mohammadipour, Fatemeh Toulabi, Tahereh Heidarizadeh, Khadijeh Heydari, Fardin |
author_facet | Farzi, Kolsoum Mohammadipour, Fatemeh Toulabi, Tahereh Heidarizadeh, Khadijeh Heydari, Fardin |
author_sort | Farzi, Kolsoum |
collection | PubMed |
description | BACKGROUND: Medication error is one of the most important and most common events threatening patient safety. This study was conducted with the aim to determine the effect of asynchronous hybrid/blended learning on the rate of medication administration errors of nurses in medical wards. MATERIALS AND METHODS: This quasi-experimental study was conducted with a pretest-posttest design in 2019. The participants of this study included 57 clinical nurses working in the medical wards of a selected educational hospital affiliated to Lorestan University of Medical Sciences, Khorramabad, Iran. The study participants were selected through census method. An asynchronous hybrid/blended learning program was used in this study. Data collection was performed using a two-section researcher-made checklist. The collected data were analyzed using descriptive [Mean (SD)] and inferential (paired sample t-test) statistics in SPSS software. A p value of less than 0.05 was considered statistically significant. RESULTS: The results showed that the mean score of total errors in medication administration in the medical wards after the intervention was significantly lower than before the intervention; the mean score of errors before and after the study was 61.67 and 50.09, respectively (t(56)= 11.41, p < 0.001). CONCLUSIONS: Asynchronous hybrid/blended learning as a type of e-learning, simple, relatively inexpensive, and new educational strategy can improve nurses' performance and reduce medication errors. |
format | Online Article Text |
id | pubmed-7968587 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-79685872021-03-19 The Effect of Blended Learning on the Rate of Medication Administration Errors of Nurses in Medical Wards Farzi, Kolsoum Mohammadipour, Fatemeh Toulabi, Tahereh Heidarizadeh, Khadijeh Heydari, Fardin Iran J Nurs Midwifery Res Original Article BACKGROUND: Medication error is one of the most important and most common events threatening patient safety. This study was conducted with the aim to determine the effect of asynchronous hybrid/blended learning on the rate of medication administration errors of nurses in medical wards. MATERIALS AND METHODS: This quasi-experimental study was conducted with a pretest-posttest design in 2019. The participants of this study included 57 clinical nurses working in the medical wards of a selected educational hospital affiliated to Lorestan University of Medical Sciences, Khorramabad, Iran. The study participants were selected through census method. An asynchronous hybrid/blended learning program was used in this study. Data collection was performed using a two-section researcher-made checklist. The collected data were analyzed using descriptive [Mean (SD)] and inferential (paired sample t-test) statistics in SPSS software. A p value of less than 0.05 was considered statistically significant. RESULTS: The results showed that the mean score of total errors in medication administration in the medical wards after the intervention was significantly lower than before the intervention; the mean score of errors before and after the study was 61.67 and 50.09, respectively (t(56)= 11.41, p < 0.001). CONCLUSIONS: Asynchronous hybrid/blended learning as a type of e-learning, simple, relatively inexpensive, and new educational strategy can improve nurses' performance and reduce medication errors. Wolters Kluwer - Medknow 2020-11-07 /pmc/articles/PMC7968587/ /pubmed/33747843 http://dx.doi.org/10.4103/ijnmr.IJNMR_188_20 Text en Copyright: © 2020 Iranian Journal of Nursing and Midwifery Research http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Farzi, Kolsoum Mohammadipour, Fatemeh Toulabi, Tahereh Heidarizadeh, Khadijeh Heydari, Fardin The Effect of Blended Learning on the Rate of Medication Administration Errors of Nurses in Medical Wards |
title | The Effect of Blended Learning on the Rate of Medication Administration Errors of Nurses in Medical Wards |
title_full | The Effect of Blended Learning on the Rate of Medication Administration Errors of Nurses in Medical Wards |
title_fullStr | The Effect of Blended Learning on the Rate of Medication Administration Errors of Nurses in Medical Wards |
title_full_unstemmed | The Effect of Blended Learning on the Rate of Medication Administration Errors of Nurses in Medical Wards |
title_short | The Effect of Blended Learning on the Rate of Medication Administration Errors of Nurses in Medical Wards |
title_sort | effect of blended learning on the rate of medication administration errors of nurses in medical wards |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7968587/ https://www.ncbi.nlm.nih.gov/pubmed/33747843 http://dx.doi.org/10.4103/ijnmr.IJNMR_188_20 |
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