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How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation
INTRODUCTION: National audits are used to monitor care quality and safety and are anticipated to reduce unexplained variations in quality by stimulating quality improvement (QI). However, variation within and between providers in the extent of engagement with national audits means that the potential...
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/PMC7044920/ https://www.ncbi.nlm.nih.gov/pubmed/32102812 http://dx.doi.org/10.1136/bmjopen-2019-033208 |
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author | Randell, Rebecca Alvarado, Natasha McVey, Lynn Greenhalgh, Joanne West, Robert M Farrin, Amanda Gale, Chris Parslow, Roger Keen, Justin Elshehaly, Mai Ruddle, Roy A Lake, Julia Mamas, Mamas Feltbower, Richard Dowding, Dawn |
author_facet | Randell, Rebecca Alvarado, Natasha McVey, Lynn Greenhalgh, Joanne West, Robert M Farrin, Amanda Gale, Chris Parslow, Roger Keen, Justin Elshehaly, Mai Ruddle, Roy A Lake, Julia Mamas, Mamas Feltbower, Richard Dowding, Dawn |
author_sort | Randell, Rebecca |
collection | PubMed |
description | INTRODUCTION: National audits are used to monitor care quality and safety and are anticipated to reduce unexplained variations in quality by stimulating quality improvement (QI). However, variation within and between providers in the extent of engagement with national audits means that the potential for national audit data to inform QI is not being realised. This study will undertake a feasibility evaluation of QualDash, a quality dashboard designed to support clinical teams and managers to explore data from two national audits, the Myocardial Ischaemia National Audit Project (MINAP) and the Paediatric Intensive Care Audit Network (PICANet). METHODS AND ANALYSIS: Realist evaluation, which involves building, testing and refining theories of how an intervention works, provides an overall framework for this feasibility study. Realist hypotheses that describe how, in what contexts, and why QualDash is expected to provide benefit will be tested across five hospitals. A controlled interrupted time series analysis, using key MINAP and PICANet measures, will provide preliminary evidence of the impact of QualDash, while ethnographic observations and interviews over 12 months will provide initial insight into contexts and mechanisms that lead to those impacts. Feasibility outcomes include the extent to which MINAP and PICANet data are used, data completeness in the audits, and the extent to which participants perceive QualDash to be useful and express the intention to continue using it after the study period. ETHICS AND DISSEMINATION: The study has been approved by the University of Leeds School of Healthcare Research Ethics Committee. Study results will provide an initial understanding of how, in what contexts, and why quality dashboards lead to improvements in care quality. These will be disseminated to academic audiences, study participants, hospital IT departments and national audits. If the results show a trial is feasible, we will disseminate the QualDash software through a stepped wedge cluster randomised trial. |
format | Online Article Text |
id | pubmed-7044920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-70449202020-03-09 How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation Randell, Rebecca Alvarado, Natasha McVey, Lynn Greenhalgh, Joanne West, Robert M Farrin, Amanda Gale, Chris Parslow, Roger Keen, Justin Elshehaly, Mai Ruddle, Roy A Lake, Julia Mamas, Mamas Feltbower, Richard Dowding, Dawn BMJ Open Health Informatics INTRODUCTION: National audits are used to monitor care quality and safety and are anticipated to reduce unexplained variations in quality by stimulating quality improvement (QI). However, variation within and between providers in the extent of engagement with national audits means that the potential for national audit data to inform QI is not being realised. This study will undertake a feasibility evaluation of QualDash, a quality dashboard designed to support clinical teams and managers to explore data from two national audits, the Myocardial Ischaemia National Audit Project (MINAP) and the Paediatric Intensive Care Audit Network (PICANet). METHODS AND ANALYSIS: Realist evaluation, which involves building, testing and refining theories of how an intervention works, provides an overall framework for this feasibility study. Realist hypotheses that describe how, in what contexts, and why QualDash is expected to provide benefit will be tested across five hospitals. A controlled interrupted time series analysis, using key MINAP and PICANet measures, will provide preliminary evidence of the impact of QualDash, while ethnographic observations and interviews over 12 months will provide initial insight into contexts and mechanisms that lead to those impacts. Feasibility outcomes include the extent to which MINAP and PICANet data are used, data completeness in the audits, and the extent to which participants perceive QualDash to be useful and express the intention to continue using it after the study period. ETHICS AND DISSEMINATION: The study has been approved by the University of Leeds School of Healthcare Research Ethics Committee. Study results will provide an initial understanding of how, in what contexts, and why quality dashboards lead to improvements in care quality. These will be disseminated to academic audiences, study participants, hospital IT departments and national audits. If the results show a trial is feasible, we will disseminate the QualDash software through a stepped wedge cluster randomised trial. BMJ Publishing Group 2020-02-25 /pmc/articles/PMC7044920/ /pubmed/32102812 http://dx.doi.org/10.1136/bmjopen-2019-033208 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/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 | Health Informatics Randell, Rebecca Alvarado, Natasha McVey, Lynn Greenhalgh, Joanne West, Robert M Farrin, Amanda Gale, Chris Parslow, Roger Keen, Justin Elshehaly, Mai Ruddle, Roy A Lake, Julia Mamas, Mamas Feltbower, Richard Dowding, Dawn How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation |
title | How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation |
title_full | How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation |
title_fullStr | How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation |
title_full_unstemmed | How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation |
title_short | How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation |
title_sort | how, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? protocol for a realist feasibility evaluation |
topic | Health Informatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7044920/ https://www.ncbi.nlm.nih.gov/pubmed/32102812 http://dx.doi.org/10.1136/bmjopen-2019-033208 |
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