Evidence map›Paper›PMID 39566038›Full record

ArticleOnline journal of public health informatics2024

Rank Ordered Design Attributes for Health Care Dashboards Including Artificial Intelligence: Usability Study.

Melina Malkani, Eesha Madan, Dillon Malkani, Arav Madan, Neel Singh, Tara Bamji, Harman Sabharwal

Abstract read
In one paragraph

Article in Online journal of public health informatics, 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. From Data to Decision: Design and Evaluation of a Patient Safety Dashboard.Medical journal of the Islamic Republic of Iran · 2025
    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.

Melina MalkaniBullis School, Potomac, MD, United States.ORCID https://orcid.org/0009-0003-6281-371X
Eesha MadanGeorge Washington University, Washington DC, DC, United States.ORCID https://orcid.org/0009-0005-5830-6648
Dillon MalkaniUniversity of Pennsylvania, Philadelphia, MD, United States.ORCID https://orcid.org/0009-0002-3561-8823
Arav MadanBasis Independent McLean, Vienna, VA, United States.ORCID https://orcid.org/0009-0006-5439-0835
Neel SinghDuke University, Durham, NC, United States.ORCID https://orcid.org/0009-0008-5827-1926
Tara BamjiScarsdale High School, Scarsdale, NY, United States.ORCID https://orcid.org/0009-0003-4058-6237
Harman SabharwalSt Stephens and St Agnes School, Alexandria, VA, United States.ORCID https://orcid.org/0009-0003-2072-8621

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOn average, people in the United States visit a doctor 4 times a year, and many of them have chronic illnesses. Because of the increased use of technology, people frequently rely on the internet to access health information and statistics. People use health care information to make better-educated decisions for themselves and others. Health care dashboards should provide pertinent and easily understood data, such as information on timely cancer screenings, so the public can make better-informed decisions. In order to enhance health outcomes, effective dashboards should provide precise data in an accessible and easily digestible manner.

objectiveThis study identifies the top 15 attributes of a health care dashboard. The objective of this research is to enhance health care dashboards to benefit the public by making better health care information available for more informed decisions by the public and to improve population-level health care outcomes.

methodsThe authors conducted a survey of health care dashboards with 218 individuals identifying the best practices to consider when creating a public health care dashboard. The data collection was conducted from June 2023 to August 2023. The analyses performed were descriptive statistics, frequencies, and a comparison to a prior study.

resultsFrom May 2023 to June 2023, we collected 3259 responses in multiple different states around the United States from 218 people aged 18 years or older. The features ranking in descending order of importance are as follows: (1) easy navigation, (2) historical data, (3) simplicity of design, (4) high usability, (5) use of clear descriptions, (6) consistency of data, (7) use of diverse chart types, (8) compliance with the Americans with Disabilities Act, (9) incorporated user feedback, (10) mobile compatibility, (11) comparison data with other entities, (12) storytelling, (13) predictive analytics with artificial intelligence, (14) adjustable thresholds, and (15) charts with tabulated data.

conclusionsFuture studies can extend the research to other types of dashboards such as bioinformatics, financial, and managerial dashboards as well as confirm these top 15 best practices for medical dashboards with further evidentiary support. The medical informatics community may benefit from standardization to improve efficiency and effectiveness as dashboards can communicate vital information to patients worldwide on critically prominent issues. Furthermore, health care professionals should use these best practices to help increase population health care outcomes by informing health care consumers to make better decisions with better data.

Indexed as

consumer decision-makingdashboardsdata visualizationhealth datainformed decisionspopulation healthpublic healthusability

Identifiers

PMID39566038
PMCPMC11618005

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.