Enhancing Patient-Clinician Communication through Self-Monitoring Data Sharing

Enhancing Patient-Clinician Communication through Self-Monitoring Data Sharing

People are tracking massive health data outside the clinic due to an explosion of wearable sensing and mobile health (mHealth) apps that support collecting self-monitoring data. The types of self-monitoring data people collect are diverse ranging from physical activity, sleep, food, and stress to weight, heart rate, blood glucose, cholesterol, and even brain activity. The potential usefulness of these data is enormous as they can provide good measures of everyday behavior and lifestyle, which is often not captured well in traditional data collection from periodic office visits. Self-monitoring data could provide great insights into individuals’ health management, diagnosis, prevention, and treatment plan. However, self-monitoring data is largely underutilized by patients and clinicians due to many obstacles, including difficulty in data sharing. Current information technology does not provide adequate support for patients to easily share their self-monitoring data with clinicians. Enabling self-monitoring data sharing between patients and clinicians has the opportunity to help through engaging and empowering patients, informing clinicians to provide better care, and enhancing the quality of patient-clinician communication, which have significant impact on patient health outcomes. This proposal outlines a 2-year, exploratory research agenda, in which I aim to understand, design, and evaluate novel information technology approaches for supporting self-monitoring data sharing between patients and clinicians. In particular, I explore this topic in the context of sharing sleep-tracking data, building upon my previous work. The long-term goals of this research are to understand the enablers and barriers toward self-monitoring data sharing, help patients be active observers and participants in their care, and inform clinicians of patient-collected health data to be able to provide better care. Using human-centered design approaches, I will conduct observations and interviews with patients and clinicians. Based on the findings, I will explore ways to meet patients’ and clinicians’ needs surrounding self-monitoring data sharing using participatory design and iterative design approaches. These efforts will culminate in the design of technology probes that will further enhance our understanding of how self-monitoring data sharing can be incorporated into a current approach to care. The results from this project will inform the design of systems that support patients and clinicians in utilizing self-monitoring data in an exam room.

 

Successful completion of this research will result in the following:

-A deep understanding of patients’ and clinicians’ barriers toward personal health data sharing and a set of design requirements and information needs to address the barriers

-Technology probes that embody these functional requirements designed based on iterative, participatory design study

-Needs assessment with the probes to learn patients’ and clinicians’ receptiveness toward self-monitoring data sharing.

 
Duration: 
August 2017 - May 2018
Research Area: 
Funder: 
National Science Foundation
Total Award Amount: 
98,731

Principal Investigator: