An Augmented-Intelligence Machine Learning Approach to Curate and Recommend Videos on Health Conditions
The easy availability of a vast repository of user-generated health information on video sharing social media platforms, such as YouTube, offers an effective way to deliver medical information that may be more understandable for the public, with the potential to improve health literacy, patient-physician interactions, self-care and health outcomes.
Few studies have identified scalable and replicable technology-enabled solutions, delivered as evidence-backed digital therapeutics, to improve the ease with which patients and health professionals can retrieve understandable medical information encoded in videos to manage health conditions. This research proposes a machine learning-driven augmented-intelligence approach that combines annotations from domain experts with machine learning and natural language processing methods to retrieve and curate relevant YouTube videos with understandable medical information that domain experts can review for accuracy and credibility before recommending to consumers.
We further examine the impact of these criteria on several dimensions of collective engagement to quantify the nuanced effects in the specific context of understandability of complex medical information encoded in patient education videos found on YouTube, with implications for research and practice.
Presenter
Rema Padman, PhD
Rema Padman is the Trustees Professor of Management Science and Healthcare Informatics in the Heinz College of Information Systems and Public Policy at Carnegie Mellon University and Adjunct Professor of Biomedical Informatics at the University of Pittsburgh School of Medicine. She directs healthcare operations, informatics and analytics research at the Heinz College. Her research investigates predictive and prescriptive analytics for data-driven decision support in the context of clinical and consumer-facing information technology interventions in healthcare delivery and management, such as e-health, m-health, chronic and infectious disease management and workflow analysis. She is a fellow of the American Medical Informatics Association.