Discovering Patient Portal Features Critical to User Satisfaction: A Systematic Analysis

Abstract

Patient portals are consumer-centric tools that can strengthen consumers’ ability to actively manage their own health and healthcare. The incorporation of patient portals provides the promise to deliver quality, low costs services to the patient population. However, patient portal adoption in large part is based on patient satisfaction. In pertaining literature, little is known about which portal features are associated with higher patient satisfaction. In this article, we extend existing literature by discovering features related to patient portal user satisfaction based on a systematic analysis of user feedback. Using MyChart, a mobile patient portal, we use text mining, N-Gram-based approach, to discover satisfaction features from online user reviews. We then demonstrate the performance of the features selected in predicting user satisfaction using different classifiers. Overall, the results extend existing research and highlight opportunities to improve and to enhance the design of current basic portals to improve users’ satisfaction and adherence.