Senior Clinical Informatics Fellow Daniel Liu, M.D., presented his research on using a machine learning predictive model to improve telehealth delivery at two conferences in fall 2021.
Dr. Liu presented posters on “Using Machine Learning to Advance Telehealth” at the SEARCH 2021 National Telehealth Research Symposium, Nov. 8-10, and the fall meeting for the Arkansas Chapter of the American Academy of Pediatrics, Aug. 27-28. Both conferences met virtually. The SEARCH symposium was organized by the Society for Education and the Advancement of Research in Connected Health.
Dr. Liu’s research is exploring whether his model could help better match pediatric patients and their families with telemedicine visits. The aim is for the telemedicine visit to be: 1) suitable for the medical situation; and 2) welcomed by the patient.
The model aims to provide a recommendation to clinic schedulers, prompting them to offer the visit via telemedicine at the time of scheduling. If successful, the matches could improve patient and provider satisfaction and the aid in the sustainable expansion of telemedicine.
Dr. Liu is using electronic health record data to help “teach” his model to make the telemedicine suggestions, using indicators of previous successful matches to help the model “learn” what factors are at play.