Article ID: | iaor2016755 |
Volume: | 5 |
Issue: | 1 |
Start Page Number: | 66 |
End Page Number: | 79 |
Publication Date: | Mar 2016 |
Journal: | Health Systems |
Authors: | Trapp Andrew C, Tulu Bengisu, Strong Diane M, Johnson Sharon A, Hoque Muyeedul, Trudel John, Garber Lawrence |
Keywords: | e-commerce, behaviour, internet, datamining |
This paper presents a study of online patient portal utilization through the analysis of system logs. We analyze click data generated between August 2009 and July 2011 by 1886 users of an online patient portal. We investigate variations in utilization for Login and the top five system features (Appointment Review, Lab Tests, Medical Advice Request, Messaging and Result Component Graphing), and examine how age and gender influence these variations. Our findings indicate that the effects of age and gender on system use vary by feature, and that efficiency of use (how clicks are spread across sessions) varies across age, gender and feature. We provide a new approach for understanding system use through click data analysis utilizing system logs (an underutilized data source available to all health‐care organizations), an example of how big data can help health‐care organizations learn more about their patients’ utilization of patient portals.