Primary Care Physician Factors Associated with Inbox Message Volume

Introduction: The objective of this study was to better understand the relationship between panel size, full-time status, and estimated socioeconomic status of a patient panel with types and number of primary care clinician inbox messages. Methods: The study used data from the Epic Signal database to examine inbox volume and types of messages for 86 primary care clinicians at 19 primary care sites. We measured correlations and performed multiple regression analysis to understand the relationship between inbox volume and types of messages and 3 factors: panel size, full-time status, and estimated socioeconomic status of patient panels. Results: The study found positive correlation between the number of messages and panel size, full-time status, and estimated socioeconomic status of patient panels. The number of patient portal messages generated from patient panels with higher socioeconomic status accounted for the positive correlation in total inbox messages and that factor. Discussion: These findings contribute to our understanding of primary care workload, specifically as it relates to panel size, full-time status, and patient panel socioeconomic status. Increase in clinical time or panel size needs to come with trained team members or additional time to address inbox messages.