Description
Online portals enable patients to exchanging messages with healthcare providers. After discharge, patients message providers to ask questions and report problems. Care providers read and respond accordingly, which requires a non-trivial amount of human effort and is unlikely to scale up as portals become more popular. Automatically detecting when a message indicates a worsening in a patient’s condition can assist providers to identify patients at risk of readmission. We investigated the association between messages that patients, diagnosed with ischemic heart disease, sent after discharge and the risk of readmission. We studied 4,052 messages sent after discharge for 1,552 patients. We represented messages using inferred latent topics, linguistic features (e.g. emotions, activities), and clusters of medical terms. Our analysis indicates that mentioning medication dosage and additional procedures are associated with readmission. Moreover, patients who were readmitted rarely mentioned leisurely activities or described their insights about their health information.
Learning Objective: 1- Identifying the indications of readmission risk and the content of patients portal messages that ischemic heart patients sent after discharge and their
2- Identifying the significant text features and message patterns that are associated with higher risk of readmission
Authors:
Lina Sulieman (Presenter)
Vanderbilt University
Zhijun Yin, Vanderbilt University
Bradley Malin, Vanderbilt University
Presentation Materials: