ArticleJMIR human factors2018
Data Visualizations to Support Health Practitioners' Provision of Personalized Care for Patients With Cancer and Multiple Chronic Conditions: User-Centered Design Study.
Article in JMIR human factors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advanced applications in chronic disease monitoring using IoT mobile sensing device data, machine learning algorithms and frame theory: a systematic review.Frontiers in public health · 2025Pooled it
- Developing a data visualization tool for adults with disorders of consciousness: Qualitative analysis of user perspectives.Learning health systems · 2025Article
- Review and Comparative Evaluation of Mobile Apps for Cardiovascular Risk Estimation: Usability Evaluation Using mHealth App Usability Questionnaire.JMIR mHealth and uHealth · 2025Review
- Patterns of symptom deterioration can support multimorbidity management in COPD: Perspectives of patients and healthcare professionals.PloS one · 2025Article
- Augmenting clinicians' analytical workflow through task-based integration of data visualizations and algorithmic insights: a user-centered design study.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review.JMIR public health and surveillance · 2024Article
- Development and usability of an EHR-driven hypertension disparities dashboard in primary care: A qualitative study.Journal of clinical hypertension (Greenwich, Conn.) · 2024Article
- Improving pain communication between limited English-speaking Hmong patients, medical interpreters, and health care providers in primary care: A pilot study.Research in nursing & health · 2024Article
- Personalized, disease-stage specific, rapid identification of immunosuppression in sepsis.Frontiers in immunology · 2024Article
- A tool to assist rheumatologists to engage their lupus patients: the Purple Butterfly.Rheumatology advances in practice · 2024Article
- Exocentric and Egocentric Views for Biomedical Data Analytics in Virtual Environments-A Usability Study.Journal of imaging · 2023Article
- Visualization of Patient-Generated Health Data: A Scoping Review of Dashboard Designs.Applied clinical informatics · 2023Article
- Toward Enhanced Clinical Decision Support for Patients Undergoing a Hip or Knee Replacement: Focus Group and Interview Study With Surgeons.JMIR perioperative medicine · 2023Article
- Recommendations for the Quality Management of Patient-Generated Health Data in Remote Patient Monitoring: Mixed Methods Study.JMIR mHealth and uHealth · 2023Article
- From precision medicine to precision care: Choosing and using precision medicine in the context of multimorbidity.Cambridge prisms. Precision medicine · 2023Review
- Challenges and Opportunities in Designing and Deploying Remote Health Monitoring Technology for Older Adults With Cancer.Innovation in aging · 2022Article
- Feasibility of collecting patient-generated health data to enhance cancer registry surveillance.Journal of cancer survivorship : research and practice · 2021Article
- Advancing clinical genomics and precision medicine with GVViZ: FAIR bioinformatics platform for variable gene-disease annotation, visualization, and expression analysis.Human genomics · 2021Article
- A Digital Platform for Facilitating Personalized Dementia Care in Nursing Homes: Formative Evaluation Study.JMIR formative research · 2021Article
- Know-Me: A Toolkit for Designing Personalised Dementia Care.International journal of environmental research and public health · 2021Article
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
backgroundThere exists a challenge of understanding and integrating various types of data collected to support the health of individuals with multiple chronic conditions engaging in cancer care. Data visualization has the potential to address this challenge and support personalized cancer care.
objectiveThe aim of the study was to assess the health care practitioners' perceptions of and feedback regarding visualizations developed to support the care of individuals with multiple chronic conditions engaging in cancer care.
methodsMedical doctors (n=4) and registered nurses (n=4) providing cancer care at an academic medical center in the western United States provided feedback on visualization mock-ups. Mock-up designs were guided by current health informatics and visualization literature and the Munzner Nested Model for Visualization Design. User-centered design methods, a mock patient persona, and a scenario were used to elicit insights from participants. Directed content analysis was used to identify themes from session transcripts. Means and SDs were calculated for health care practitioners' rankings of overview visualizations.
resultsThemes identified were data elements, supportive elements, confusing elements, interpretation, and use of visualization. Overall, participants found the visualizations useful and with the potential to provide personalized care. Use of color, reference lines, and familiar visual presentations (calendars, line graphs) were noted as helpful in interpreting data.
conclusionsVisualizations guided by a framework and literature can support health care practitioners' understanding of data for individuals with multiple chronic conditions engaged in cancer care. This understanding has the potential to support the provision of personalized care.
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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.