ArticleEGEMS (Washington, DC)2018
A Systematic Method for Exploring Data Attributes in Preparation for Designing Tailored Infographics of Patient Reported Outcomes.
Article in EGEMS (Washington, DC), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Information visualizations of symptom information for patients and providers: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- A Practical Guide to Participatory Design Sessions for the Development of Information Visualizations: Tutorial.Journal of participatory medicine · 2024Article
- Seeing things the same way: perspectives and lessons learned from research-design collaborations.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Feedback of patient-reported outcomes to healthcare professionals for comparing health service performance: a scoping review.BMJ open · 2020Article
- Visual analogies, not graphs, increase patients' comprehension of changes in their health status.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Best practices for data visualization: creating and evaluating a report for an evidence-based fall prevention program.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Leveraging Patient-Reported Outcomes Using Data Visualization.Applied clinical informatics · 2018Article
- Development and Validation of Self-Management Infographics for Patients With Type 2 Diabetes Mellitus in Rural Kenya.Public health nursing (Boston, Mass.)Article
- Redesigning culturally tailored intervention in the precision health era: Self-management science context.Nursing outlookArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
contextTailored visualizations of patient reported outcomes (PROs) are valuable health communication tools to support shared decision making, health self-management, and engagement with research participants, such as cohorts in the NIH Precision Medicine Initiative. The automation of visualizations presents some unique design challenges. Efficient design processes depend upon gaining a thorough understanding of the data prior to prototyping. CASE DESCRIPTION: We present a systematic method to exploring data attributes, with a specific focus on application to self-reported health data. The method entails a) determining the meaning of the variable to be visualized, b) identifying the possible and likely values, and c) understanding how values are interpreted.
findingsWe present two case studies to illustrate how this method affected our design decisions particularly with respect to outlier and non-missing zero values. MAJOR THEMES: The use of a systematic method made our process of exploring data attributes easily manageable. The limitations of the data can narrow design options but can also prompt creative solutions and innovative design opportunities.
conclusionA systematic method of exploration of data contributes to an efficient design process, uncovers design opportunities, and alerts the designer to design challenges.
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.