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Data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: Protocol for a process evaluation

BACKGROUND: Practice-level quality improvement initiatives using rapidly advancing technology offers a multidimensional approach to reduce cardiovascular disease burden. For the “QUality improvement in primary care to prevent hospitalisations and improve Effectiveness and efficiency of care for peop...

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Autores principales: Hafiz, Nashid, Hyun, Karice, Tu, Qiang, Knight, Andrew, Hespe, Charlotte, Chow, Clara K., Briffa, Tom, Gallagher, Robyn, Reid, Christopher M., Hare, David L., Zwar, Nicholas, Woodward, Mark, Jan, Stephen, Atkins, Emily R., Laba, Tracey-Lea, Halcomb, Elizabeth, Johnson, Tracey, Usherwood, Timothy, Redfern, Julie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110058/
https://www.ncbi.nlm.nih.gov/pubmed/35589026
http://dx.doi.org/10.1016/j.cct.2022.106794
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author Hafiz, Nashid
Hyun, Karice
Tu, Qiang
Knight, Andrew
Hespe, Charlotte
Chow, Clara K.
Briffa, Tom
Gallagher, Robyn
Reid, Christopher M.
Hare, David L.
Zwar, Nicholas
Woodward, Mark
Jan, Stephen
Atkins, Emily R.
Laba, Tracey-Lea
Halcomb, Elizabeth
Johnson, Tracey
Usherwood, Timothy
Redfern, Julie
author_facet Hafiz, Nashid
Hyun, Karice
Tu, Qiang
Knight, Andrew
Hespe, Charlotte
Chow, Clara K.
Briffa, Tom
Gallagher, Robyn
Reid, Christopher M.
Hare, David L.
Zwar, Nicholas
Woodward, Mark
Jan, Stephen
Atkins, Emily R.
Laba, Tracey-Lea
Halcomb, Elizabeth
Johnson, Tracey
Usherwood, Timothy
Redfern, Julie
author_sort Hafiz, Nashid
collection PubMed
description BACKGROUND: Practice-level quality improvement initiatives using rapidly advancing technology offers a multidimensional approach to reduce cardiovascular disease burden. For the “QUality improvement in primary care to prevent hospitalisations and improve Effectiveness and efficiency of care for people Living with heart disease” (QUEL) cluster randomised controlled trial, a 12-month quality improvement intervention was designed for primary care practices to use data and implement progressive changes using “Plan, Do, Study, Act” cycles within their practices with training in a series of interactive workshops. This protocol aims to describe the systematic methods to conduct a process evaluation of the data-driven intervention within the QUEL study. METHODS: A mixed-method approach will be used to conduct the evaluation. Quantitative data collected throughout the intervention period, via surveys and intervention materials, will be used to (1) identify the key elements of the intervention and how, for whom and in what context it was effective; (2) determine if the intervention is delivered as intended; and (3) describe practice engagement, commitment and capacity associated with various intervention components. Qualitative data, collected via semi-structured interviews and open-ended questions, will be used to gather in-depth understanding of the (1) satisfaction, utility, barriers and enablers; (2) acceptability, uptake and feasibility, and (3) effect of the COVID-19 pandemic on the implementation of the intervention. CONCLUSION: Findings from the evaluation will provide new knowledge on the implementation of a complex, multi-component intervention at practice-level using their own electronic patient data to enhance secondary prevention of cardiovascular disease. Trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12619001790134.
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spelling pubmed-91100582022-05-17 Data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: Protocol for a process evaluation Hafiz, Nashid Hyun, Karice Tu, Qiang Knight, Andrew Hespe, Charlotte Chow, Clara K. Briffa, Tom Gallagher, Robyn Reid, Christopher M. Hare, David L. Zwar, Nicholas Woodward, Mark Jan, Stephen Atkins, Emily R. Laba, Tracey-Lea Halcomb, Elizabeth Johnson, Tracey Usherwood, Timothy Redfern, Julie Contemp Clin Trials Article BACKGROUND: Practice-level quality improvement initiatives using rapidly advancing technology offers a multidimensional approach to reduce cardiovascular disease burden. For the “QUality improvement in primary care to prevent hospitalisations and improve Effectiveness and efficiency of care for people Living with heart disease” (QUEL) cluster randomised controlled trial, a 12-month quality improvement intervention was designed for primary care practices to use data and implement progressive changes using “Plan, Do, Study, Act” cycles within their practices with training in a series of interactive workshops. This protocol aims to describe the systematic methods to conduct a process evaluation of the data-driven intervention within the QUEL study. METHODS: A mixed-method approach will be used to conduct the evaluation. Quantitative data collected throughout the intervention period, via surveys and intervention materials, will be used to (1) identify the key elements of the intervention and how, for whom and in what context it was effective; (2) determine if the intervention is delivered as intended; and (3) describe practice engagement, commitment and capacity associated with various intervention components. Qualitative data, collected via semi-structured interviews and open-ended questions, will be used to gather in-depth understanding of the (1) satisfaction, utility, barriers and enablers; (2) acceptability, uptake and feasibility, and (3) effect of the COVID-19 pandemic on the implementation of the intervention. CONCLUSION: Findings from the evaluation will provide new knowledge on the implementation of a complex, multi-component intervention at practice-level using their own electronic patient data to enhance secondary prevention of cardiovascular disease. Trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12619001790134. The Authors. Published by Elsevier Inc. 2022-07 2022-05-17 /pmc/articles/PMC9110058/ /pubmed/35589026 http://dx.doi.org/10.1016/j.cct.2022.106794 Text en © 2022 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Hafiz, Nashid
Hyun, Karice
Tu, Qiang
Knight, Andrew
Hespe, Charlotte
Chow, Clara K.
Briffa, Tom
Gallagher, Robyn
Reid, Christopher M.
Hare, David L.
Zwar, Nicholas
Woodward, Mark
Jan, Stephen
Atkins, Emily R.
Laba, Tracey-Lea
Halcomb, Elizabeth
Johnson, Tracey
Usherwood, Timothy
Redfern, Julie
Data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: Protocol for a process evaluation
title Data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: Protocol for a process evaluation
title_full Data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: Protocol for a process evaluation
title_fullStr Data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: Protocol for a process evaluation
title_full_unstemmed Data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: Protocol for a process evaluation
title_short Data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: Protocol for a process evaluation
title_sort data-driven quality improvement program to prevent hospitalisation and improve care of people living with coronary heart disease: protocol for a process evaluation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110058/
https://www.ncbi.nlm.nih.gov/pubmed/35589026
http://dx.doi.org/10.1016/j.cct.2022.106794
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