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Exploring the Design of Patient-Generated Data Visualizations

Fateme Rajabiyazdi (McGill University), Charles Perin (University of Victoria), Lora Oehlberg (University of Calgary), Sheelagh Carpendale (Simon Fraser University)


Proceedings of Graphics Interface 2020:
University of Toronto,
28 – 29 May 2020, pp. 362 – 373

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.

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