May 2014 Archives

     At Pervasive Health 2014, we presented results of our study with patients and domain experts who used the Remedy technology probe to search the web for inpatient medication information. 

Paper: Patient-Centered Tools for Medication Information Search
Lauren Wilcox, Steven Feiner, Noemie Elhadad, David Vawdrey, Tran Tran

(click on image to view more information on the project and links to slides and published paper)
commons-drop.png I am looking forward to participating in the 2014 NIH mHealth Training Institute.  The institute brings together scientists from diverse fields focusing on the use of mobile technologies to enhance personal health.
Patients' accurate assessment of health-related risk plays an important role in self-protective motivation and behavior change. Recent theories of behavior change treat risk perception in depth; however, less research has focused on how to draw on these theories to create convincing but intuitive explanations of risk to patients. 

At the CHI 2014 workshop on Personalizing Behavior Change Technologies, we advocated a new, personalized approach for presenting health-related risk to individuals, based on concrete information from similar patients. 

Advances in large-scale healthcare analytics have demonstrated the feasibility of computing inter-patient similarity through both knowledge-based and data-driven approaches. While originally designed based on physician use of patient data, analytics platforms could be designed to support compelling patient use cases as well.

At the workshop, we outlined the need and potential for patient-facing, clinical-similarity-based technologies to motivate health-related behavior change. We explored relevant conceptual frameworks that can inform the design and evaluation of these technologies, identified open questions related to the use of these frameworks, and explored the experiences and insights of others working in related application domains.

Lauren Wilcox & Jimeng Sun. Supporting Patient Assessment of Risk using Patient Similarity: Implications for Behavior Change.