Analysis of a Web-Based Dashboard to Support the Use of National Audit Data in Quality Improvement: Realist Evaluation.


Journal

Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882

Informations de publication

Date de publication:
23 11 2021
Historique:
received: 14 04 2021
accepted: 05 10 2021
revised: 15 07 2021
entrez: 24 11 2021
pubmed: 25 11 2021
medline: 15 12 2021
Statut: epublish

Résumé

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.

Sections du résumé

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.

Identifiants

pubmed: 34817384
pii: v23i11e28854
doi: 10.2196/28854
pmc: PMC8663683
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e28854

Subventions

Organisme : Department of Health
ID : 16/04/06
Pays : United Kingdom

Informations de 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.

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Auteurs

Natasha Alvarado (N)

Faculty of Health Studies, University of Bradford, Bradford, United Kingdom.
Wolfson Centre for Applied Health Research, Bradford, United Kingdom.

Lynn McVey (L)

Faculty of Health Studies, University of Bradford, Bradford, United Kingdom.
Wolfson Centre for Applied Health Research, Bradford, United Kingdom.

Mai Elshehaly (M)

Wolfson Centre for Applied Health Research, Bradford, United Kingdom.
Faculty of Engineering and Informatics, University of Bradford, Bradford, United Kingdom.

Joanne Greenhalgh (J)

School of Sociology and Social Policy, University of Leeds, Leeds, United Kingdom.

Dawn Dowding (D)

School of Health Sciences, University of Manchester, Manchester, United Kingdom.

Roy Ruddle (R)

School of Computing, University of Leeds, Leeds, United Kingdom.
Leeds Institute for Data Analytics, Leeds, United Kingdom.

Chris P Gale (CP)

Leeds Institute for Data Analytics, Leeds, United Kingdom.
Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom.

Mamas Mamas (M)

Keele Cardiovascular Group, School of Medicine, Keele University, Keele, United Kingdom.

Patrick Doherty (P)

Department of Health Sciences, University of York, York, United Kingdom.

Robert West (R)

Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.

Richard Feltbower (R)

Leeds Institute for Data Analytics, Leeds, United Kingdom.
School of Medicine, University of Leeds, Leeds, United Kingdom.

Rebecca Randell (R)

Faculty of Health Studies, University of Bradford, Bradford, United Kingdom.
Wolfson Centre for Applied Health Research, Bradford, United Kingdom.

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