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Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement
BACKGROUND: The COVID-19 pandemic represents an unprecedented challenge to healthcare systems and nations across the world. Particularly challenging are the lack of agreed-upon management guidelines and variations in practice. Our hospital is a large, secondary-care government hospital in Kuwait, wh...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670554/ https://www.ncbi.nlm.nih.gov/pubmed/33199287 http://dx.doi.org/10.1136/bmjoq-2020-001130 |
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author | Salem, Ahmed Elamir, Hossam Alfoudri, Huda Shamsah, Mohammed Abdelraheem, Shams Abdo, Ibtissam Galal, Mohammad Ali, Lamiaa |
author_facet | Salem, Ahmed Elamir, Hossam Alfoudri, Huda Shamsah, Mohammed Abdelraheem, Shams Abdo, Ibtissam Galal, Mohammad Ali, Lamiaa |
author_sort | Salem, Ahmed |
collection | PubMed |
description | BACKGROUND: The COVID-19 pandemic represents an unprecedented challenge to healthcare systems and nations across the world. Particularly challenging are the lack of agreed-upon management guidelines and variations in practice. Our hospital is a large, secondary-care government hospital in Kuwait, which has increased its capacity by approximately 28% to manage the care of patients with COVID-19. The surge in capacity has necessitated the redeployment of staff who are not well-trained to manage such conditions. There was a great need to develop a tool to help redeployed staff in decision-making for patients with COVID-19, a tool which could also be used for training. METHODS: Based on the best available clinical knowledge and best practices, an eight member multidisciplinary group of clinical and quality experts undertook the development of a clinical algorithm-based toolkit to guide training and practice for the management of patients with COVID-19. The team followed Horabin and Lewis’ seven-step approach in developing the algorithms and a five-step method in writing them. Moreover, we applied Rosenfeld et al’s five points to each algorithm. RESULTS: A set of seven clinical algorithms and one illustrative layout diagram were developed. The algorithms were augmented with documentation forms, data-collection online forms and spreadsheets and an indicators’ reference sheet to guide implementation and performance measurement. The final version underwent several revisions and amendments prior to approval. CONCLUSIONS: A large volume of published literature on the topic of COVID-19 pandemic was translated into a user-friendly, algorithm-based toolkit for the management of patients with COVID-19. This toolkit can be used for training and decision-making to improve the quality of care provided to patients with COVID-19. |
format | Online Article Text |
id | pubmed-7670554 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-76705542020-11-17 Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement Salem, Ahmed Elamir, Hossam Alfoudri, Huda Shamsah, Mohammed Abdelraheem, Shams Abdo, Ibtissam Galal, Mohammad Ali, Lamiaa BMJ Open Qual Quality Improvement Report BACKGROUND: The COVID-19 pandemic represents an unprecedented challenge to healthcare systems and nations across the world. Particularly challenging are the lack of agreed-upon management guidelines and variations in practice. Our hospital is a large, secondary-care government hospital in Kuwait, which has increased its capacity by approximately 28% to manage the care of patients with COVID-19. The surge in capacity has necessitated the redeployment of staff who are not well-trained to manage such conditions. There was a great need to develop a tool to help redeployed staff in decision-making for patients with COVID-19, a tool which could also be used for training. METHODS: Based on the best available clinical knowledge and best practices, an eight member multidisciplinary group of clinical and quality experts undertook the development of a clinical algorithm-based toolkit to guide training and practice for the management of patients with COVID-19. The team followed Horabin and Lewis’ seven-step approach in developing the algorithms and a five-step method in writing them. Moreover, we applied Rosenfeld et al’s five points to each algorithm. RESULTS: A set of seven clinical algorithms and one illustrative layout diagram were developed. The algorithms were augmented with documentation forms, data-collection online forms and spreadsheets and an indicators’ reference sheet to guide implementation and performance measurement. The final version underwent several revisions and amendments prior to approval. CONCLUSIONS: A large volume of published literature on the topic of COVID-19 pandemic was translated into a user-friendly, algorithm-based toolkit for the management of patients with COVID-19. This toolkit can be used for training and decision-making to improve the quality of care provided to patients with COVID-19. BMJ Publishing Group 2020-11-16 /pmc/articles/PMC7670554/ /pubmed/33199287 http://dx.doi.org/10.1136/bmjoq-2020-001130 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Quality Improvement Report Salem, Ahmed Elamir, Hossam Alfoudri, Huda Shamsah, Mohammed Abdelraheem, Shams Abdo, Ibtissam Galal, Mohammad Ali, Lamiaa Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement |
title | Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement |
title_full | Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement |
title_fullStr | Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement |
title_full_unstemmed | Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement |
title_short | Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement |
title_sort | improving management of hospitalised patients with covid-19: algorithms and tools for implementation and measurement |
topic | Quality Improvement Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670554/ https://www.ncbi.nlm.nih.gov/pubmed/33199287 http://dx.doi.org/10.1136/bmjoq-2020-001130 |
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