CRII: CHS: Enhancing Patient-Clinician Communication through Self-Monitoring Data Sharing

This research aims to understand the enablers and barriers in sharing self-monitoring data collected from the ever-evolving wearable sensing and mobile health technology. Self-monitoring data can provide good measures of everyday health behavior that are often not well captured by traditional methods such as regular visits to clinicians. However, self-monitoring data is largely underutilized by patients and clinicians due to many obstacles, including difficulty in data sharing. Current information technology is inadequate for patients to easily share their self-monitoring data with clinicians. Based on the understanding of current challenges and design opportunities, novel information technology will be designed for assisting patients and clinicians to effectively collaborate and communicate. The long-term goal is to help patients be active observers and participants in their own care, and assist clinicians leverage patients' self-monitoring data in their medical decision-making. Using human-centered design approaches, observations and interviews will be conducted with patients and clinicians to understand how they currently share self-monitoring data. The focus will be on workarounds and breakdowns. Based on the findings, participatory design and iterative design approaches will identify design opportunities that can meet patients' and clinicians' data sharing needs. These efforts will culminate in the design of lightweight technology probes that enhance our understanding of how self-monitoring data sharing should be incorporated into health care and clinical workflow. Successful completion of this research will provide: (1) a deeper understanding of patients' and clinicians' barriers toward personal health data sharing and a set of functional design and information requirements to address the barriers, (2) light-weight technology probes that embody these requirements based on participatory and iterative design approaches, and (3) a needs assessment with probes for learning receptiveness toward self-monitoring data sharing. This research will advance the field of human-computer interaction and health informatics by deepening our understanding of how self-monitoring data collected from wearable sensing and mobile health technology can be incorporated into clinical care.