The Digital Workload Divide: Investigating Gender Differences in Electronic Health Record Messaging among Primary Care Clinicians

Electronic health record (EHR) patient portal messaging has become an essential tool for patient-clinician communication by improving accessibility to primary care. While messaging is beneficial for patients, it can increase clinicians' workloads. Female clinicians receive a greater number of EHR messaging, resulting in an increased workload.This evaluation explores the factors in clinician gender disparity in EHR messaging burden.The first phase of the evaluation included a retrospective analysis of the messages to 267 primary care clinicians in the University of Vermont Health Network (UVMHN). The second phase analyzed patient demographics and panel complexity. Statistical analysis was performed across all categories of patient care-generated messages to primary care clinicians and subsequently on all messages across the UVMHN.Female clinicians received significantly more patient-initiated medical advice request messages than their male counterparts (68.28 vs. 49.22 messages/month, <i>p</i> = 0.005) and spent more time managing messages (1.85 vs. 1.35 minute/day, <i>p</i> = 0.006). Despite this increased workload, response times remained similar between genders. Female clinicians have a higher proportion of female patients, and analysis of all messages sent across the organization demonstrated that female patient care produces more messages than male patient care (59 vs. 52 messages/female vs. male, <i>p</i> = 0.001). Panels size and complexity were similar for both male and female providers.These findings highlight an unequal messaging burden for female clinicians in primary care specialties of internal and family medicine, largely due to patient demographics. Patient panel complexity as defined by UVMHN and clinician full-time equivalent were similar between genders. Disparities in message volumes appear to be driven primarily by patient communication behavior differences between genders rather than differences in workload allocation. These findings likely contribute to increased burnout risk among female clinicians. Addressing this imbalance through workflow optimization and artificial intelligence-driven message triage systems may help to mitigate the burden on female clinicians and promote greater equity in primary care.