Analysis of a Web-Based Dashboard to Support the Use of National Audit Data in Quality Improvement: Realist Evaluation
Dashboards can support data-driven quality improvements in health care. They visualize data in ways intended to ease cognitive load and support data comprehension, but how they are best integrated into working practices needs further investigation. This paper reports the findings of a realist evalua...
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| Published in: | Journal of medical Internet research Vol. 23; no. 11; p. e28854 |
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| Main Authors: | , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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Canada
Gunther Eysenbach MD MPH, Associate Professor
23.11.2021
JMIR Publications |
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| ISSN: | 1438-8871, 1439-4456, 1438-8871 |
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| Abstract | Dashboards can support data-driven quality improvements in health care. They visualize data in ways intended to ease cognitive load and support data comprehension, but how they are best integrated into working practices needs further investigation.
This paper reports the findings of a realist evaluation of a web-based quality dashboard (QualDash) developed to support the use of national audit data in quality improvement.
QualDash was co-designed with data users and installed in 8 clinical services (3 pediatric intensive care units and 5 cardiology services) across 5 health care organizations (sites A-E) in England between July and December 2019. Champions were identified to support adoption. Data to evaluate QualDash were collected between July 2019 and August 2021 and consisted of 148.5 hours of observations including hospital wards and clinical governance meetings, log files that captured the extent of use of QualDash over 12 months, and a questionnaire designed to assess the dashboard's perceived usefulness and ease of use. Guided by the principles of realist evaluation, data were analyzed to understand how, why, and in what circumstances QualDash supported the use of national audit data in quality improvement.
The observations revealed that variation across sites in the amount and type of resources available to support data use, alongside staff interactions with QualDash, shaped its use and impact. Sites resourced with skilled audit support staff and established reporting systems (sites A and C) continued to use existing processes to report data. A number of constraints influenced use of QualDash in these sites including that some dashboard metrics were not configured in line with user expectations and staff were not fully aware how QualDash could be used to facilitate their work. In less well-resourced services, QualDash automated parts of their reporting process, streamlining the work of audit support staff (site B), and, in some cases, highlighted issues with data completeness that the service worked to address (site E). Questionnaire responses received from 23 participants indicated that QualDash was perceived as useful and easy to use despite its variable use in practice.
Web-based dashboards have the potential to support data-driven improvement, providing access to visualizations that can help users address key questions about care quality. Findings from this study point to ways in which dashboard design might be improved to optimize use and impact in different contexts; this includes using data meaningful to stakeholders in the co-design process and actively engaging staff knowledgeable about current data use and routines in the scrutiny of the dashboard metrics and functions. In addition, consideration should be given to the processes of data collection and upload that underpin the quality of the data visualized and consequently its potential to stimulate quality improvement.
RR2-10.1136/bmjopen-2019-033208. |
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| AbstractList | BackgroundDashboards can support data-driven quality improvements in health care. They visualize data in ways intended to ease cognitive load and support data comprehension, but how they are best integrated into working practices needs further investigation. ObjectiveThis paper reports the findings of a realist evaluation of a web-based quality dashboard (QualDash) developed to support the use of national audit data in quality improvement. MethodsQualDash was co-designed with data users and installed in 8 clinical services (3 pediatric intensive care units and 5 cardiology services) across 5 health care organizations (sites A-E) in England between July and December 2019. Champions were identified to support adoption. Data to evaluate QualDash were collected between July 2019 and August 2021 and consisted of 148.5 hours of observations including hospital wards and clinical governance meetings, log files that captured the extent of use of QualDash over 12 months, and a questionnaire designed to assess the dashboard’s perceived usefulness and ease of use. Guided by the principles of realist evaluation, data were analyzed to understand how, why, and in what circumstances QualDash supported the use of national audit data in quality improvement. ResultsThe observations revealed that variation across sites in the amount and type of resources available to support data use, alongside staff interactions with QualDash, shaped its use and impact. Sites resourced with skilled audit support staff and established reporting systems (sites A and C) continued to use existing processes to report data. A number of constraints influenced use of QualDash in these sites including that some dashboard metrics were not configured in line with user expectations and staff were not fully aware how QualDash could be used to facilitate their work. In less well-resourced services, QualDash automated parts of their reporting process, streamlining the work of audit support staff (site B), and, in some cases, highlighted issues with data completeness that the service worked to address (site E). Questionnaire responses received from 23 participants indicated that QualDash was perceived as useful and easy to use despite its variable use in practice. ConclusionsWeb-based dashboards have the potential to support data-driven improvement, providing access to visualizations that can help users address key questions about care quality. Findings from this study point to ways in which dashboard design might be improved to optimize use and impact in different contexts; this includes using data meaningful to stakeholders in the co-design process and actively engaging staff knowledgeable about current data use and routines in the scrutiny of the dashboard metrics and functions. In addition, consideration should be given to the processes of data collection and upload that underpin the quality of the data visualized and consequently its potential to stimulate quality improvement. International Registered Report Identifier (IRRID)RR2-10.1136/bmjopen-2019-033208 Dashboards can support data-driven quality improvements in health care. They visualize data in ways intended to ease cognitive load and support data comprehension, but how they are best integrated into working practices needs further investigation.BACKGROUNDDashboards can support data-driven quality improvements in health care. They visualize data in ways intended to ease cognitive load and support data comprehension, but how they are best integrated into working practices needs further investigation.This paper reports the findings of a realist evaluation of a web-based quality dashboard (QualDash) developed to support the use of national audit data in quality improvement.OBJECTIVEThis paper reports the findings of a realist evaluation of a web-based quality dashboard (QualDash) developed to support the use of national audit data in quality improvement.QualDash was co-designed with data users and installed in 8 clinical services (3 pediatric intensive care units and 5 cardiology services) across 5 health care organizations (sites A-E) in England between July and December 2019. Champions were identified to support adoption. Data to evaluate QualDash were collected between July 2019 and August 2021 and consisted of 148.5 hours of observations including hospital wards and clinical governance meetings, log files that captured the extent of use of QualDash over 12 months, and a questionnaire designed to assess the dashboard's perceived usefulness and ease of use. Guided by the principles of realist evaluation, data were analyzed to understand how, why, and in what circumstances QualDash supported the use of national audit data in quality improvement.METHODSQualDash was co-designed with data users and installed in 8 clinical services (3 pediatric intensive care units and 5 cardiology services) across 5 health care organizations (sites A-E) in England between July and December 2019. Champions were identified to support adoption. Data to evaluate QualDash were collected between July 2019 and August 2021 and consisted of 148.5 hours of observations including hospital wards and clinical governance meetings, log files that captured the extent of use of QualDash over 12 months, and a questionnaire designed to assess the dashboard's perceived usefulness and ease of use. Guided by the principles of realist evaluation, data were analyzed to understand how, why, and in what circumstances QualDash supported the use of national audit data in quality improvement.The observations revealed that variation across sites in the amount and type of resources available to support data use, alongside staff interactions with QualDash, shaped its use and impact. Sites resourced with skilled audit support staff and established reporting systems (sites A and C) continued to use existing processes to report data. A number of constraints influenced use of QualDash in these sites including that some dashboard metrics were not configured in line with user expectations and staff were not fully aware how QualDash could be used to facilitate their work. In less well-resourced services, QualDash automated parts of their reporting process, streamlining the work of audit support staff (site B), and, in some cases, highlighted issues with data completeness that the service worked to address (site E). Questionnaire responses received from 23 participants indicated that QualDash was perceived as useful and easy to use despite its variable use in practice.RESULTSThe observations revealed that variation across sites in the amount and type of resources available to support data use, alongside staff interactions with QualDash, shaped its use and impact. Sites resourced with skilled audit support staff and established reporting systems (sites A and C) continued to use existing processes to report data. A number of constraints influenced use of QualDash in these sites including that some dashboard metrics were not configured in line with user expectations and staff were not fully aware how QualDash could be used to facilitate their work. In less well-resourced services, QualDash automated parts of their reporting process, streamlining the work of audit support staff (site B), and, in some cases, highlighted issues with data completeness that the service worked to address (site E). Questionnaire responses received from 23 participants indicated that QualDash was perceived as useful and easy to use despite its variable use in practice.Web-based dashboards have the potential to support data-driven improvement, providing access to visualizations that can help users address key questions about care quality. Findings from this study point to ways in which dashboard design might be improved to optimize use and impact in different contexts; this includes using data meaningful to stakeholders in the co-design process and actively engaging staff knowledgeable about current data use and routines in the scrutiny of the dashboard metrics and functions. In addition, consideration should be given to the processes of data collection and upload that underpin the quality of the data visualized and consequently its potential to stimulate quality improvement.CONCLUSIONSWeb-based dashboards have the potential to support data-driven improvement, providing access to visualizations that can help users address key questions about care quality. Findings from this study point to ways in which dashboard design might be improved to optimize use and impact in different contexts; this includes using data meaningful to stakeholders in the co-design process and actively engaging staff knowledgeable about current data use and routines in the scrutiny of the dashboard metrics and functions. In addition, consideration should be given to the processes of data collection and upload that underpin the quality of the data visualized and consequently its potential to stimulate quality improvement.RR2-10.1136/bmjopen-2019-033208.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)RR2-10.1136/bmjopen-2019-033208. Dashboards can support data-driven quality improvements in health care. They visualize data in ways intended to ease cognitive load and support data comprehension, but how they are best integrated into working practices needs further investigation. This paper reports the findings of a realist evaluation of a web-based quality dashboard (QualDash) developed to support the use of national audit data in quality improvement. QualDash was co-designed with data users and installed in 8 clinical services (3 pediatric intensive care units and 5 cardiology services) across 5 health care organizations (sites A-E) in England between July and December 2019. Champions were identified to support adoption. Data to evaluate QualDash were collected between July 2019 and August 2021 and consisted of 148.5 hours of observations including hospital wards and clinical governance meetings, log files that captured the extent of use of QualDash over 12 months, and a questionnaire designed to assess the dashboard's perceived usefulness and ease of use. Guided by the principles of realist evaluation, data were analyzed to understand how, why, and in what circumstances QualDash supported the use of national audit data in quality improvement. The observations revealed that variation across sites in the amount and type of resources available to support data use, alongside staff interactions with QualDash, shaped its use and impact. Sites resourced with skilled audit support staff and established reporting systems (sites A and C) continued to use existing processes to report data. A number of constraints influenced use of QualDash in these sites including that some dashboard metrics were not configured in line with user expectations and staff were not fully aware how QualDash could be used to facilitate their work. In less well-resourced services, QualDash automated parts of their reporting process, streamlining the work of audit support staff (site B), and, in some cases, highlighted issues with data completeness that the service worked to address (site E). Questionnaire responses received from 23 participants indicated that QualDash was perceived as useful and easy to use despite its variable use in practice. Web-based dashboards have the potential to support data-driven improvement, providing access to visualizations that can help users address key questions about care quality. Findings from this study point to ways in which dashboard design might be improved to optimize use and impact in different contexts; this includes using data meaningful to stakeholders in the co-design process and actively engaging staff knowledgeable about current data use and routines in the scrutiny of the dashboard metrics and functions. In addition, consideration should be given to the processes of data collection and upload that underpin the quality of the data visualized and consequently its potential to stimulate quality improvement. RR2-10.1136/bmjopen-2019-033208. Background: Dashboards can support data-driven quality improvements in health care. They visualize data in ways intended to ease cognitive load and support data comprehension, but how they are best integrated into working practices needs further investigation. Objective: This paper reports the findings of a realist evaluation of a web-based quality dashboard (QualDash) developed to support the use of national audit data in quality improvement. Methods: QualDash was co-designed with data users and installed in 8 clinical services (3 pediatric intensive care units and 5 cardiology services) across 5 health care organizations (sites A-E) in England between July and December 2019. Champions were identified to support adoption. Data to evaluate QualDash were collected between July 2019 and August 2021 and consisted of 148.5 hours of observations including hospital wards and clinical governance meetings, log files that captured the extent of use of QualDash over 12 months, and a questionnaire designed to assess the dashboard’s perceived usefulness and ease of use. Guided by the principles of realist evaluation, data were analyzed to understand how, why, and in what circumstances QualDash supported the use of national audit data in quality improvement. Results: The observations revealed that variation across sites in the amount and type of resources available to support data use, alongside staff interactions with QualDash, shaped its use and impact. Sites resourced with skilled audit support staff and established reporting systems (sites A and C) continued to use existing processes to report data. A number of constraints influenced use of QualDash in these sites including that some dashboard metrics were not configured in line with user expectations and staff were not fully aware how QualDash could be used to facilitate their work. In less well-resourced services, QualDash automated parts of their reporting process, streamlining the work of audit support staff (site B), and, in some cases, highlighted issues with data completeness that the service worked to address (site E). Questionnaire responses received from 23 participants indicated that QualDash was perceived as useful and easy to use despite its variable use in practice. Conclusions: Web-based dashboards have the potential to support data-driven improvement, providing access to visualizations that can help users address key questions about care quality. Findings from this study point to ways in which dashboard design might be improved to optimize use and impact in different contexts; this includes using data meaningful to stakeholders in the co-design process and actively engaging staff knowledgeable about current data use and routines in the scrutiny of the dashboard metrics and functions. In addition, consideration should be given to the processes of data collection and upload that underpin the quality of the data visualized and consequently its potential to stimulate quality improvement. International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2019-033208 |
| Author | Elshehaly, Mai Greenhalgh, Joanne Dowding, Dawn Feltbower, Richard Mamas, Mamas Ruddle, Roy Gale, Chris P McVey, Lynn Doherty, Patrick West, Robert Alvarado, Natasha Randell, Rebecca |
| AuthorAffiliation | 9 Department of Cardiology Leeds Teaching Hospitals NHS Trust Leeds United Kingdom 12 Leeds Institute of Health Sciences University of Leeds Leeds United Kingdom 10 Keele Cardiovascular Group School of Medicine Keele University Keele United Kingdom 8 Leeds Institute of Cardiovascular and Metabolic Medicine University of Leeds Leeds United Kingdom 2 Wolfson Centre for Applied Health Research Bradford United Kingdom 7 Leeds Institute for Data Analytics Leeds United Kingdom 13 School of Medicine University of Leeds Leeds United Kingdom 3 Faculty of Engineering and Informatics University of Bradford Bradford United Kingdom 4 School of Sociology and Social Policy University of Leeds Leeds United Kingdom 5 School of Health Sciences University of Manchester Manchester United Kingdom 1 Faculty of Health Studies University of Bradford Bradford United Kingdom 6 School of Computing University of Leeds Leeds United Kingdom 11 Department of Health Sciences University of York York United Kingdom |
| AuthorAffiliation_xml | – name: 8 Leeds Institute of Cardiovascular and Metabolic Medicine University of Leeds Leeds United Kingdom – name: 1 Faculty of Health Studies University of Bradford Bradford United Kingdom – name: 12 Leeds Institute of Health Sciences University of Leeds Leeds United Kingdom – name: 4 School of Sociology and Social Policy University of Leeds Leeds United Kingdom – name: 5 School of Health Sciences University of Manchester Manchester United Kingdom – name: 10 Keele Cardiovascular Group School of Medicine Keele University Keele United Kingdom – name: 2 Wolfson Centre for Applied Health Research Bradford United Kingdom – name: 11 Department of Health Sciences University of York York United Kingdom – name: 6 School of Computing University of Leeds Leeds United Kingdom – name: 13 School of Medicine University of Leeds Leeds United Kingdom – name: 3 Faculty of Engineering and Informatics University of Bradford Bradford United Kingdom – name: 7 Leeds Institute for Data Analytics Leeds United Kingdom – name: 9 Department of Cardiology Leeds Teaching Hospitals NHS Trust Leeds United Kingdom |
| Author_xml | – sequence: 1 givenname: Natasha orcidid: 0000-0001-9422-4483 surname: Alvarado fullname: Alvarado, Natasha – sequence: 2 givenname: Lynn orcidid: 0000-0003-2009-7682 surname: McVey fullname: McVey, Lynn – sequence: 3 givenname: Mai orcidid: 0000-0002-5867-6121 surname: Elshehaly fullname: Elshehaly, Mai – sequence: 4 givenname: Joanne orcidid: 0000-0003-2189-8879 surname: Greenhalgh fullname: Greenhalgh, Joanne – sequence: 5 givenname: Dawn orcidid: 0000-0001-5672-8605 surname: Dowding fullname: Dowding, Dawn – sequence: 6 givenname: Roy orcidid: 0000-0001-8662-8103 surname: Ruddle fullname: Ruddle, Roy – sequence: 7 givenname: Chris P orcidid: 0000-0003-4732-382X surname: Gale fullname: Gale, Chris P – sequence: 8 givenname: Mamas orcidid: 0000-0001-9241-8890 surname: Mamas fullname: Mamas, Mamas – sequence: 9 givenname: Patrick orcidid: 0000-0002-1887-0237 surname: Doherty fullname: Doherty, Patrick – sequence: 10 givenname: Robert orcidid: 0000-0001-7305-3654 surname: West fullname: West, Robert – sequence: 11 givenname: Richard orcidid: 0000-0002-1728-9408 surname: Feltbower fullname: Feltbower, Richard – sequence: 12 givenname: Rebecca orcidid: 0000-0002-5856-4912 surname: Randell fullname: Randell, Rebecca |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34817384$$D View this record in MEDLINE/PubMed |
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| Copyright | Natasha Alvarado, Lynn McVey, Mai Elshehaly, Joanne Greenhalgh, Dawn Dowding, Roy Ruddle, Chris P Gale, Mamas Mamas, Patrick Doherty, Robert West, Richard Feltbower, Rebecca Randell. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.11.2021. 2021. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Natasha Alvarado, Lynn McVey, Mai Elshehaly, Joanne Greenhalgh, Dawn Dowding, Roy Ruddle, Chris P Gale, Mamas Mamas, Patrick Doherty, Robert West, Richard Feltbower, Rebecca Randell. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.11.2021. 2021 |
| Copyright_xml | – notice: Natasha Alvarado, Lynn McVey, Mai Elshehaly, Joanne Greenhalgh, Dawn Dowding, Roy Ruddle, Chris P Gale, Mamas Mamas, Patrick Doherty, Robert West, Richard Feltbower, Rebecca Randell. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.11.2021. – notice: 2021. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: Natasha Alvarado, Lynn McVey, Mai Elshehaly, Joanne Greenhalgh, Dawn Dowding, Roy Ruddle, Chris P Gale, Mamas Mamas, Patrick Doherty, Robert West, Richard Feltbower, Rebecca Randell. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.11.2021. 2021 |
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| License | Natasha Alvarado, Lynn McVey, Mai Elshehaly, Joanne Greenhalgh, Dawn Dowding, Roy Ruddle, Chris P Gale, Mamas Mamas, Patrick Doherty, Robert West, Richard Feltbower, Rebecca Randell. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.11.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
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| Publisher | Gunther Eysenbach MD MPH, Associate Professor JMIR Publications |
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| References | ref13 ref35 ref34 ref14 ref36 ref31 ref30 ref11 ref33 ref10 Dowding, D (ref12) 2018; 2018 ref32 ref2 Sittig, D (ref21) 2015 ref1 ref17 ref16 ref19 Srivastava, A (ref27) 2009; 4 (ref15) 2021 ref18 ref24 ref26 ref25 Ritchie, J (ref28) 1994 ref20 ref22 ref29 ref8 ref7 ref9 ref4 ref3 ref6 ref5 Pawson, R (ref23) 1997 |
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| Title | Analysis of a Web-Based Dashboard to Support the Use of National Audit Data in Quality Improvement: Realist Evaluation |
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