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Updated: Jun 24, 2025

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
Published on: January 2, 2011
Design of patient-facing immunization visualizations affects task performance: an experimental comparison of 4
Jenna Marquard1,2, Robin Austin1, Sripriya Rajamani1,2
1School of Nursing, University of Minnesota, Minneapolis, MN 55455, United States.
The design of electronic health record (EHR) immunization visualizations significantly impacts patient understanding and task completion. Epic MyChart resulted in longer task times and fewer correct dates compared to other formats like eLetters.
Area of Science:
- Health Informatics
- Human-Computer Interaction
- Patient Engagement
Background:
- Electronic health records (EHRs) are increasingly patient-facing.
- Effective visualization of immunization data is crucial for patient understanding and adherence.
- Existing EHR immunization visualizations vary in design and usability.
Purpose of the Study:
- To experimentally evaluate lay individuals' interpretation and use of four different EHR patient-facing immunization visualizations.
- To compare task performance across distinct visualization formats.
Main Methods:
- Sixty-nine participants completed an online survey.
- Participants interacted with one of four EHR immunization visualizations: Epic MyChart, eClinicWorks, a downloadable EHR record, or an eLetter.
- Task performance (time, accuracy) and subjective measures (workload, numeracy, health literacy) were assessed.
Main Results:
- Visualization design significantly impacted task performance.
- Epic MyChart users took longer and entered fewer correct dates compared to eLetter and eClinicWorks users.
- No significant performance differences were found based on numeracy, health literacy, or demographics.
Conclusions:
- Unique design elements of the tested visualizations led to performance variations.
- Practical design guidance for immunization visualizations is provided.
- Future research should explore context of use and the effectiveness of table-based visualizations.
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