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Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol

BACKGROUND: Medication errors are likely common in low- and middle-income countries (LMICs). In neonatal hospital care where the population with severe illness has a high mortality rate, around 14.9% of drug prescriptions have errors in LMICs settings. However, there is scant research on interventio...

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Autores principales: Tuti, Timothy, Aluvaala, Jalemba, Malla, Lucas, Irimu, Grace, Mbevi, George, Wainaina, John, Mumelo, Livingstone, Wairoto, Kefa, Mochache, Dolphine, Hagel, Christiane, Maina, Michuki, English, Mike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9109356/
https://www.ncbi.nlm.nih.gov/pubmed/35578243
http://dx.doi.org/10.1186/s13012-022-01203-w
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author Tuti, Timothy
Aluvaala, Jalemba
Malla, Lucas
Irimu, Grace
Mbevi, George
Wainaina, John
Mumelo, Livingstone
Wairoto, Kefa
Mochache, Dolphine
Hagel, Christiane
Maina, Michuki
English, Mike
author_facet Tuti, Timothy
Aluvaala, Jalemba
Malla, Lucas
Irimu, Grace
Mbevi, George
Wainaina, John
Mumelo, Livingstone
Wairoto, Kefa
Mochache, Dolphine
Hagel, Christiane
Maina, Michuki
English, Mike
author_sort Tuti, Timothy
collection PubMed
description BACKGROUND: Medication errors are likely common in low- and middle-income countries (LMICs). In neonatal hospital care where the population with severe illness has a high mortality rate, around 14.9% of drug prescriptions have errors in LMICs settings. However, there is scant research on interventions to improve medication safety to mitigate such errors. Our objective is to improve routine neonatal care particularly focusing on effective prescribing practices with the aim of achieving reduced gentamicin medication errors. METHODS: We propose to conduct an audit and feedback (A&F) study over 12 months in 20 hospitals with 12 months of baseline data. The medical and nursing leaders on their newborn units had been organised into a network that facilitates evaluating intervention approaches for improving quality of neonatal care in these hospitals and are receiving basic feedback generated from the baseline data. In this study, the network will (1) be expanded to include all hospital pharmacists, (2) include a pharmacist-only professional WhatsApp discussion group for discussing prescription practices, and (3) support all hospitals to facilitate pharmacist-led continuous medical education seminars on prescription practices at hospital level, i.e. default intervention package. A subset of these hospitals (n = 10) will additionally (1) have an additional hospital-specific WhatsApp group for the pharmacists to discuss local performance with their local clinical team, (2) receive detailed A&F prescription error reports delivered through mobile-based dashboard, and (3) receive a PDF infographic summarising prescribing performance circulated to the clinicians through the hospital-specific WhatsApp group, i.e. an extended package. Using interrupted time series analysis modelling changes in prescribing errors over time, coupled with process fidelity evaluation, and WhatsApp sentiment analysis, we will evaluate the success with which the A&F interventions are delivered, received, and acted upon to reduce prescribing error while exploring the extended package’s success/failure relative to the default intervention package. DISCUSSION: If effective, these theory-informed A&F strategies that carefully consider the challenges of LMICs settings will support the improvement of medication prescribing practices with the insights gained adapted for other clinical behavioural targets of a similar nature. TRIAL REGISTRATION: PACTR, PACTR202203869312307. Registered 17th March 2022. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13012-022-01203-w.
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spelling pubmed-91093562022-05-16 Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol Tuti, Timothy Aluvaala, Jalemba Malla, Lucas Irimu, Grace Mbevi, George Wainaina, John Mumelo, Livingstone Wairoto, Kefa Mochache, Dolphine Hagel, Christiane Maina, Michuki English, Mike Implement Sci Study Protocol BACKGROUND: Medication errors are likely common in low- and middle-income countries (LMICs). In neonatal hospital care where the population with severe illness has a high mortality rate, around 14.9% of drug prescriptions have errors in LMICs settings. However, there is scant research on interventions to improve medication safety to mitigate such errors. Our objective is to improve routine neonatal care particularly focusing on effective prescribing practices with the aim of achieving reduced gentamicin medication errors. METHODS: We propose to conduct an audit and feedback (A&F) study over 12 months in 20 hospitals with 12 months of baseline data. The medical and nursing leaders on their newborn units had been organised into a network that facilitates evaluating intervention approaches for improving quality of neonatal care in these hospitals and are receiving basic feedback generated from the baseline data. In this study, the network will (1) be expanded to include all hospital pharmacists, (2) include a pharmacist-only professional WhatsApp discussion group for discussing prescription practices, and (3) support all hospitals to facilitate pharmacist-led continuous medical education seminars on prescription practices at hospital level, i.e. default intervention package. A subset of these hospitals (n = 10) will additionally (1) have an additional hospital-specific WhatsApp group for the pharmacists to discuss local performance with their local clinical team, (2) receive detailed A&F prescription error reports delivered through mobile-based dashboard, and (3) receive a PDF infographic summarising prescribing performance circulated to the clinicians through the hospital-specific WhatsApp group, i.e. an extended package. Using interrupted time series analysis modelling changes in prescribing errors over time, coupled with process fidelity evaluation, and WhatsApp sentiment analysis, we will evaluate the success with which the A&F interventions are delivered, received, and acted upon to reduce prescribing error while exploring the extended package’s success/failure relative to the default intervention package. DISCUSSION: If effective, these theory-informed A&F strategies that carefully consider the challenges of LMICs settings will support the improvement of medication prescribing practices with the insights gained adapted for other clinical behavioural targets of a similar nature. TRIAL REGISTRATION: PACTR, PACTR202203869312307. Registered 17th March 2022. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13012-022-01203-w. BioMed Central 2022-05-16 /pmc/articles/PMC9109356/ /pubmed/35578243 http://dx.doi.org/10.1186/s13012-022-01203-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Study Protocol
Tuti, Timothy
Aluvaala, Jalemba
Malla, Lucas
Irimu, Grace
Mbevi, George
Wainaina, John
Mumelo, Livingstone
Wairoto, Kefa
Mochache, Dolphine
Hagel, Christiane
Maina, Michuki
English, Mike
Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol
title Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol
title_full Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol
title_fullStr Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol
title_full_unstemmed Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol
title_short Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol
title_sort evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (regent) in neonatal inpatient care in kenya: a controlled interrupted time series study protocol
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9109356/
https://www.ncbi.nlm.nih.gov/pubmed/35578243
http://dx.doi.org/10.1186/s13012-022-01203-w
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