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Visual analytics in precision medicine: Using mixed methods to support stakeholder data needs

Resource type
Thesis type
(Thesis) M.Sc.
Date created
Precision medicine solutions require health consumers to increasingly interact with digital interfaces to report their medical history and conditions. This is challenging since the symptoms of an illness can often be located to an activity or a body part and untrained health consumers struggle to communicate them clearly. To address this problem, I designed a mixed methods study, where I first conducted short-term ethnography in a precision medicine company to understand the data requirements of a set of health data analysts. This exploration led to methodological and design guidelines that translated into an interactive data-capture system that visually mapped a controlled vocabulary of human disease phenotypes to a graphical depiction of the body. Results showed that describing the experience of illness in a somatic representation gave health consumers a more accurate and descriptive understanding of their illness, and by doing so captured more reliable data for analysts. The representation can support health care workers to provide more accurate analyses, aid caregivers in managing health risks, and empower health consumers to take action to better their health.
Copyright statement
Copyright is held by the author.
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Fisher, Brian
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etd20921.pdf 3.06 MB

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