Evidence mapPaperPMID 39574106Full record

ArticleBMC medical informatics and decision making2024

Healthcare dashboard technologies and data visualization for lipid management: A scoping review.

Mahnaz Samadbeik, Teyl Engstrom, Elton H Lobo, Karem Kostner, Jodie A Austin, Jason D Pole, Clair Sullivan

Abstract readScoping Review
In one paragraph

Article in BMC medical informatics and decision making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
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

7 authors.

Mahnaz SamadbeikCentre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia. m.samadbeik@uq.edu.au.
Teyl EngstromCentre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Elton H LoboCentre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Karem KostnerMater Hospital, University of Queensland, Brisbane, Australia.
Jodie A AustinCentre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Jason D PoleCentre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Clair SullivanCentre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLipid disorders significantly increase cardiovascular disease (CVD) risk, the leading cause of mortality worldwide. Effective lipid management is critical for improving health outcomes. Traditional screening methods face challenges due to data complexity and the need for timely decision-making. Data visualization and dashboard technologies offer clear, actionable insights and supporting informed decision-making. This study investigates the use of these technologies in lipid management and their impacts on the quadruple aim of healthcare.

methodsThis scoping review followed the Joanna Briggs Institute (JBI) approach, focusing on studies involving dashboard technologies or data visualization in lipid management. A comprehensive search across multiple databases (Embase, Web of Science, PubMed, Scopus, CINAHL) and gray literature was conducted, including English-language publications from 2014 to 2024. Data were analyzed using quantitative descriptive and qualitative content analysis to evaluate the key features, clinical applications, and outcomes.

resultsTwenty-seven studies met the inclusion criteria, primarily focusing on dashboard utilization by physicians for managing diabetes and CVD, utilizing electronic medical records and clinical guidelines. Key analysis methods included comparing key performance indicators (KPIs) (85.2%) and trend analysis (74.1%). Lipid management workflows emphasized prevention (88.9%) and treatment planning (77.8%). Interventions included care packages (comprehensive sets of interventions for patient care), decision support systems, web-based tools, and mobile health solutions. Regarding Quadruple Aim outcomes: 12 studies focused on improving population health (8 positive, 4 no change), 9 on clinical outcomes (5 positive, 4 no change), 6 on provider work life (5 positive), 5 on patient experience (positive changes in education and time management), and 2 on cost reduction (1 positive, 1 negative).

conclusionsDashboards are important tools in managing lipid disorders in managing lipid disorders, integrating with educational tools, collaborative care models, and decision support systems. Although they are effective in enhancing population health and clinical experiences, their impact on patient outcomes and cost reduction requires further exploration. Future research should focus on detailed evaluations of dashboard impacts on patient outcomes and cost-effectiveness, emphasizing precision prevention of chronic diseases.

Indexed as

Data VisualizationCardiovascular DiseasesElectronic Health RecordsHumansDashboard technologiesData visualizationLipid managementRoutinely collected health dataScoping review

Identifiers

PMID39574106
PMCPMC11583543

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.