Evidence map›Paper›PMID 39488428›Full record

SynthesisBMJ open2024

Impact of visualising healthcare quality performance: a systematic review.

Zijing Yang, Edward Alveyn, Mrinalini Dey, Nikita Arumalla, Mark D Russell, Sam Norton, James B Galloway

Abstract readSystematic Review
In one paragraph

Synthesis in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Zijing YangCentre for Rheumatic Diseases, King's College London, London, UK.ORCID 0000-0001-7041-459X
Edward AlveynCentre for Rheumatic Diseases, King's College London, London, UK.
Mrinalini DeyCentre for Rheumatic Diseases, King's College London, London, UK.
Nikita ArumallaCentre for Rheumatic Diseases, King's College London, London, UK.
Mark D RussellCentre for Rheumatic Diseases, King's College London, London, UK.ORCID 0000-0001-8171-7772
Sam NortonCentre for Rheumatic Diseases, King's College London, London, UK.
James B GallowayCentre for Rheumatic Diseases, King's College London, London, UK james.galloway@kcl.ac.uk.ORCID 0000-0002-1230-2781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePerformance visualisation tools are increasingly being applied in healthcare to enhance decision-making and improve quality of care. However, there is a lack of comprehensive synthesis of their overall effectiveness and the contextual factors that influence their success in different clinical settings. This study aims to provide a broad synthesis of visualisation interventions not limited to a specific department.

designSystematic review. DATA SOURCES: MEDLINE and Embase were searched until December 2022. ELIGIBILITY CRITERIA: Randomised controlled trials (RCTs) and observational studies in English involving a visualisation intervention, either alone or as a core intervention, that reported quantitative outcomes including process and outcome indicators. DATA EXTRACTION AND SYNTHESIS: Data on study characteristics, intervention characteristics, outcome measures and results were extracted. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation approach, and risk of bias was evaluated with Risk of Bias 2 for RCTs and Risk of Bias in Non-randomised Studies - of Interventions for non-randomised studies.

resultsOf the 12 studies included, 2 were RCTs and 10 were observational studies, including 1 before-after study and 1 interrupted time series study. Five studies (42%) were conducted in teaching hospital settings. Compared with the control group or baseline, 10 studies reported a statistically significant change in at least one of their outcome measures. A majority of the studies reported a positive impact, including prescription adherence (6/10), screening tests (3/10) and monitoring (3/10). Visualisation tool factors like type, clinical setting, workflow integration and clinician engagement, may have some influence on the effectiveness of the intervention, but no reliable evidence was identified.

conclusionPerformance visualisation tools have the potential to improve clinical performance indicators. More studies with standardised outcome measures and integrating qualitative methods are needed to understand the contextual factors that influence the effectiveness of these interventions.

Indexed as

Quality of Health CareHumansQuality ImprovementQuality Indicators, Health CareHealth ServicesHEALTH SERVICES ADMINISTRATION & MANAGEMENTQuality ImprovementQuality in health care

Identifiers

PMID39488428
PMCPMC11535674

What OpenQuestion holds

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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 OpenQuestion graph.