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Prioritising recommendations following analyses of adverse events in healthcare: a systematic review

PURPOSE: The purpose of this systematic review was to identify an appropriate method—a user-friendly and validated method—that prioritises recommendations following analyses of adverse events (AEs) based on objective features. DATA SOURCES: The electronic databases PubMed/MEDLINE, Embase (Ovid), Coc...

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Autores principales: Bos, Kelly, van der Laan, Maarten J, Dongelmans, Dave A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549482/
https://www.ncbi.nlm.nih.gov/pubmed/33037042
http://dx.doi.org/10.1136/bmjoq-2019-000843
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author Bos, Kelly
van der Laan, Maarten J
Dongelmans, Dave A
author_facet Bos, Kelly
van der Laan, Maarten J
Dongelmans, Dave A
author_sort Bos, Kelly
collection PubMed
description PURPOSE: The purpose of this systematic review was to identify an appropriate method—a user-friendly and validated method—that prioritises recommendations following analyses of adverse events (AEs) based on objective features. DATA SOURCES: The electronic databases PubMed/MEDLINE, Embase (Ovid), Cochrane Library, PsycINFO (Ovid) and ERIC (Ovid) were searched. STUDY SELECTION: Studies were considered eligible when reporting on methods to prioritise recommendations. DATA EXTRACTION: Two teams of reviewers performed the data extraction which was defined prior to this phase. RESULTS OF DATA SYNTHESIS: Eleven methods were identified that are designed to prioritise recommendations. After completing the data extraction, none of the methods met all the predefined criteria. Nine methods were considered user-friendly. One study validated the developed method. Five methods prioritised recommendations based on objective features, not affected by personal opinion or knowledge and expected to be reproducible by different users. CONCLUSION: There are several methods available to prioritise recommendations following analyses of AEs. All these methods can be used to discuss and select recommendations for implementation. None of the methods is a user-friendly and validated method that prioritises recommendations based on objective features. Although there are possibilities to further improve their features, the ‘Typology of safety functions’ by de Dianous and Fiévez, and the ‘Hierarchy of hazard controls’ by McCaughan have the most potential to select high-quality recommendations as they have only a few clearly defined categories in a well-arranged ordinal sequence.
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spelling pubmed-75494822020-10-19 Prioritising recommendations following analyses of adverse events in healthcare: a systematic review Bos, Kelly van der Laan, Maarten J Dongelmans, Dave A BMJ Open Qual Systematic Review PURPOSE: The purpose of this systematic review was to identify an appropriate method—a user-friendly and validated method—that prioritises recommendations following analyses of adverse events (AEs) based on objective features. DATA SOURCES: The electronic databases PubMed/MEDLINE, Embase (Ovid), Cochrane Library, PsycINFO (Ovid) and ERIC (Ovid) were searched. STUDY SELECTION: Studies were considered eligible when reporting on methods to prioritise recommendations. DATA EXTRACTION: Two teams of reviewers performed the data extraction which was defined prior to this phase. RESULTS OF DATA SYNTHESIS: Eleven methods were identified that are designed to prioritise recommendations. After completing the data extraction, none of the methods met all the predefined criteria. Nine methods were considered user-friendly. One study validated the developed method. Five methods prioritised recommendations based on objective features, not affected by personal opinion or knowledge and expected to be reproducible by different users. CONCLUSION: There are several methods available to prioritise recommendations following analyses of AEs. All these methods can be used to discuss and select recommendations for implementation. None of the methods is a user-friendly and validated method that prioritises recommendations based on objective features. Although there are possibilities to further improve their features, the ‘Typology of safety functions’ by de Dianous and Fiévez, and the ‘Hierarchy of hazard controls’ by McCaughan have the most potential to select high-quality recommendations as they have only a few clearly defined categories in a well-arranged ordinal sequence. BMJ Publishing Group 2020-10-09 /pmc/articles/PMC7549482/ /pubmed/33037042 http://dx.doi.org/10.1136/bmjoq-2019-000843 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Systematic Review
Bos, Kelly
van der Laan, Maarten J
Dongelmans, Dave A
Prioritising recommendations following analyses of adverse events in healthcare: a systematic review
title Prioritising recommendations following analyses of adverse events in healthcare: a systematic review
title_full Prioritising recommendations following analyses of adverse events in healthcare: a systematic review
title_fullStr Prioritising recommendations following analyses of adverse events in healthcare: a systematic review
title_full_unstemmed Prioritising recommendations following analyses of adverse events in healthcare: a systematic review
title_short Prioritising recommendations following analyses of adverse events in healthcare: a systematic review
title_sort prioritising recommendations following analyses of adverse events in healthcare: a systematic review
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549482/
https://www.ncbi.nlm.nih.gov/pubmed/33037042
http://dx.doi.org/10.1136/bmjoq-2019-000843
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