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BibTex
@inproceedings{Rajabiyazdi:2020:10.20380/GI2020.36,
author = {Rajabiyazdi, Fateme and Perin, Charles and Oehlberg, Lora and Carpendale, Sheelagh},
title = {Exploring the Design of Patient-Generated Data Visualizations},
booktitle = {Proceedings of Graphics Interface 2020},
series = {GI 2020},
year = {2020},
isbn = {978-0-9947868-5-2},
location = {University of Toronto},
pages = {362 -- 373},
numpages = {12},
doi = {10.20380/GI2020.36},
publisher = {Canadian Human-Computer Communications Society / Société canadienne du dialogue humain-machine},
}
Abstract
We were approached by a group of healthcare providers who are involved in the care of chronic patients looking for potential technologies to facilitate the process of reviewing patient-generated data during clinical visits. Aiming at understanding the healthcare providers' attitudes towards reviewing patient-generated data, we (1) conducted a focus group with a mixed group of healthcare providers. Next, to gain the patients' perspectives, we (2) interviewed eight chronic patients, collected a sample of their data and designed a series of visualizations representing patient data we collected. Last, we (3) sought feedback on the visualization designs from healthcare providers who requested this exploration. We found four factors shaping patient-generated data: data & context, patient's motivation, patient's time commitment, and patient's support circle. Informed by the results of our studies, we discussed the importance of designing patient-generated visualizations for individuals by considering both patient and healthcare provider rather than designing with the purpose of generalization and provided guidelines for designing future patient-generated data visualizations.