Evidence map›Paper›PMID 34817384›Full record

ArticleJournal of medical Internet research2021

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

Natasha Alvarado, Lynn McVey, Mai Elshehaly, Joanne Greenhalgh, Dawn Dowding, Roy Ruddle, Chris P Gale, Mamas Mamas, Patrick Doherty, Robert West and 2 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Natasha AlvaradoFaculty of Health Studies, University of Bradford, Bradford, United Kingdom.ORCID 0000-0001-9422-4483
Lynn McVeyFaculty of Health Studies, University of Bradford, Bradford, United Kingdom.ORCID 0000-0003-2009-7682
Mai ElshehalyWolfson Centre for Applied Health Research, Bradford, United Kingdom.ORCID 0000-0002-5867-6121
Joanne GreenhalghSchool of Sociology and Social Policy, University of Leeds, Leeds, United Kingdom.ORCID 0000-0003-2189-8879
Dawn DowdingSchool of Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID 0000-0001-5672-8605
Roy RuddleSchool of Computing, University of Leeds, Leeds, United Kingdom.ORCID 0000-0001-8662-8103
Chris P GaleLeeds Institute for Data Analytics, Leeds, United Kingdom.ORCID 0000-0003-4732-382X
Mamas MamasKeele Cardiovascular Group, School of Medicine, Keele University, Keele, United Kingdom.ORCID 0000-0001-9241-8890
Patrick DohertyDepartment of Health Sciences, University of York, York, United Kingdom.ORCID 0000-0002-1887-0237
Robert WestLeeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.ORCID 0000-0001-7305-3654
Richard FeltbowerLeeds Institute for Data Analytics, Leeds, United Kingdom.ORCID 0000-0002-1728-9408
Rebecca RandellFaculty of Health Studies, University of Bradford, Bradford, United Kingdom.ORCID 0000-0002-5856-4912

Funding

Department of Health 16/04/06
6 · The paper itself

Abstract

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.

Indexed as

Delivery of Health CareQuality ImprovementChildData CollectionEnglandHumansInternetauditdashboardsdataQualDashqualitysupport

Identifiers

PMID34817384
PMCPMC8663683

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.