ReviewInternational journal of preventive medicine2021
Need for Interactive Data Visualization in Public Health Practice: Examples from India.
Review in International journal of preventive medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Using artificial intelligence for the development of a living evidence map: The pharmacopuncture example.Integrative medicine research · 2025Article
- Data Dashboard Acceptability, Use, and Perceived Effectiveness in Disseminating Local Overdose Data and Resources in a Rural New York State County: A Cross-Sectional Study.Online journal of public health informatics · 2025Article
- Design, Application, and Actionability of US Public Health Data Dashboards: Scoping Review.Journal of medical Internet research · 2025Article
- National Public Health Dashboards: Protocol for a Scoping Review.JMIR research protocols · 2024Article
- Lessons learnt from the implementation of the Covid-19 vaccination programme in the Southwest of England.PloS one · 2024Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The world is full of data which is increasing by leaps and bounds. In health care, big data is becoming common with increased electronic health data accumulation and/or accessibility to public data previously held under lock and key. At the same time, health data visualization applications have become popular over recent years. Against this background, a review was done to summarize the application of data visualization in public health & the challenges faced. Peer-reviewed original research articles and review articles searched in Google Scholar and Pubmed databases that were indexed in the last ten years period, using the keywords "Big data" or "data visualization" or "Interactive visualization techniques." Other related information in books, blogs, and published documents were searched in Google search engine using the same keywords. Contents from the downloaded documents were presented and discussed under three headings viz. (a) the visualizations that are still current and how they have evolved further, (b) tools or methods that can be used by end-users to make their own modifications, (c) the platforms to disseminate them. Usage of different plots in public health is explained with suitable examples using the data from public health datasets. From the discussion it can be understood that when big data is visualized well, it can identify implementation gaps and disparities and accelerate implementation strategies to reach the population groups in most need for interventions. As health administrator may come from diverse specialties, robust training and career development for big data in public health is the need of the hour.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.