Often when people get sick or need health information, they turn to the Internet for answers, with health searches being one of the most popular uses of the Internet today. This high demand for health information, coupled with the rising popularity in social networking, has resulted in the creation of many online health communities that offer users the opportunity to interact with others who are dealing with the same disease or health issues.
These peer-patient conversations can be helpful for learning about patients' personal experiences managing their illness, but what they currently lack are clinical moderators and the insight from clinical experts on more clinically oriented information.
Jina Huh, Assistant Professor in the Department of Media and Information, is working to solve this issue and has been awarded a National Institutes of Health (NIH) National Library of Medicine Career Development Award (K01) to develop a semi-automated system that would infuse clinical expertise into peer-patient conversations in online health communities. The system will aid patient self-management by delivering balanced information from patients' personal experiences and clinical expertise. The three-year, $467,801 grant began in October 2014.
"In face-to-face patient support groups, clinicians moderate patients who share their experiences so they can clarify clinical questions and answer any questions patients might have," Huh said. "From the patient's perspective, they not only get other peer-patient experiences, but also clinical expertise from the clinical moderators. But in the online community setting, that sort of support group dynamic between patients and moderators is missing.
"My proposal is to develop a system that would enable that social dynamic present in face-to-face settings to be augmented in online settings."
Huh has conducted a number of studies with health professionals looking at when such a system should step in.
"They just want the system to interject when there are medical terms being used that indicate any symptoms or treatments, such as 'numbness' or 'severe pain,'" Huh said.
During the first year of the grant, Huh will develop the training data set to train the machine to learn how to classify the patients' posts and find out when the machine can intervene. The second year, she will work on the user interface and develop a feedback mechanism so users can give feedback to the machine's results and the way the machine works with users. Over the third year, Huh plans to deploy a working prototype.
Huh serves as a Trifecta Intellectual Leader (TIL) for the Trifecta initiative, which fosters interdisciplinary research by building relationships among experts in three MSU colleges – Communication Arts and Sciences, Engineering, and Nursing – to collaboratively advance the delivery of health services to underserved populations.
"The grant reviewers really liked that MSU offers this Trifecta initiative and that I am a Trifecta faculty. They noted this as part of the positive reviews for the grant," Huh said. "Because of this, they thought that MSU is a very good environment for me to conduct this research."
Huh's mentors on the project include Professor Wanda Pratt, the Information School, University of Washington (mentor chair); University Distinguished Professor Barbara Given, MSU College of Nursing; and Professor Joyce Chai, Department of Computer Science and Engineering, MSU College of Engineering. Consultants on the project are Associate Professor Marianne Huebner, Department of Statistics and Probability, MSU College of Natural Science; Associate Professor of Nursing Amber Vermeesch, University of Portland, Oregon; and John Crowley, Vice President of Consumer Marketing an Online Communities, Alliance Health.Share via these networks: