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Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS)
We performed FMEA on the existing RRS with the help of routine users of the RRS who acted as subject matter experts and evaluated the failures for their criticality using the Risk Priority Number approach based on their experience of the RRS. The FMEA found 35 potential failure modes and 101 failure...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857483/ https://www.ncbi.nlm.nih.gov/pubmed/35243066 http://dx.doi.org/10.1016/j.heliyon.2022.e08944 |
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author | Ullah, Ehsan Baig, Mirza Mansoor GholamHosseini, Hamid Lu, Jun |
author_facet | Ullah, Ehsan Baig, Mirza Mansoor GholamHosseini, Hamid Lu, Jun |
author_sort | Ullah, Ehsan |
collection | PubMed |
description | We performed FMEA on the existing RRS with the help of routine users of the RRS who acted as subject matter experts and evaluated the failures for their criticality using the Risk Priority Number approach based on their experience of the RRS. The FMEA found 35 potential failure modes and 101 failure mode effects across 13 process steps of the RRS. The afferent limb of RRS was found to be more prone to these failures (62, 61.4%) than the efferent limb of the RRS (39, 38.6%). Modification of calling criteria (12, 11.9%) and calculation of New Zealand Early Warning Scores (NZEWS) calculation (11, 10.9%) steps were found to potentially give rise to the highest number of these failures. Causes of these failures include human error and related factors (35, 34.7%), staff workload/staffing levels (30, 29.7%) and limitations due to paper-based charts and organisational factors (n = 30, 29.7%). The demonstrated electronic system was found to potentially eliminate or reduce the likelihood of 71 (70.2%) failures. The failures not eliminated by the electronic RRS require targeted corrective measures including scenario-based training and education, and revised calling criteria to include triggers for hypothermia and high systolic blood pressure. |
format | Online Article Text |
id | pubmed-8857483 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88574832022-03-02 Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS) Ullah, Ehsan Baig, Mirza Mansoor GholamHosseini, Hamid Lu, Jun Heliyon Research Article We performed FMEA on the existing RRS with the help of routine users of the RRS who acted as subject matter experts and evaluated the failures for their criticality using the Risk Priority Number approach based on their experience of the RRS. The FMEA found 35 potential failure modes and 101 failure mode effects across 13 process steps of the RRS. The afferent limb of RRS was found to be more prone to these failures (62, 61.4%) than the efferent limb of the RRS (39, 38.6%). Modification of calling criteria (12, 11.9%) and calculation of New Zealand Early Warning Scores (NZEWS) calculation (11, 10.9%) steps were found to potentially give rise to the highest number of these failures. Causes of these failures include human error and related factors (35, 34.7%), staff workload/staffing levels (30, 29.7%) and limitations due to paper-based charts and organisational factors (n = 30, 29.7%). The demonstrated electronic system was found to potentially eliminate or reduce the likelihood of 71 (70.2%) failures. The failures not eliminated by the electronic RRS require targeted corrective measures including scenario-based training and education, and revised calling criteria to include triggers for hypothermia and high systolic blood pressure. Elsevier 2022-02-11 /pmc/articles/PMC8857483/ /pubmed/35243066 http://dx.doi.org/10.1016/j.heliyon.2022.e08944 Text en © 2022 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Ullah, Ehsan Baig, Mirza Mansoor GholamHosseini, Hamid Lu, Jun Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS) |
title | Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS) |
title_full | Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS) |
title_fullStr | Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS) |
title_full_unstemmed | Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS) |
title_short | Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS) |
title_sort | failure mode and effect analysis (fmea) to identify and mitigate failures in a hospital rapid response system (rrs) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857483/ https://www.ncbi.nlm.nih.gov/pubmed/35243066 http://dx.doi.org/10.1016/j.heliyon.2022.e08944 |
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