Lauren Wilcox & Jimeng Sun
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. In this paper, we advocate 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 hope to outline the need and potential for patient-facing, clinical-similarity-based technologies to motivate health-related behavior change. We will share our understanding of relevant conceptual frameworks that can inform the design and evaluation of these technologies, identify open questions related to the use of these frameworks, and explore the experiences and insights of others working in related application domains.
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. In this paper, we advocate 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 hope to outline the need and potential for patient-facing, clinical-similarity-based technologies to motivate health-related behavior change. We will share our understanding of relevant conceptual frameworks that can inform the design and evaluation of these technologies, identify open questions related to the use of these frameworks, and explore the experiences and insights of others working in related application domains.