Special Topic Burnout: The Digital Workload Divide: Investigating Gender Differences in EHR Messaging Among Primary Care Clinicians.

BACKGROUND

Electronic Health Record (EHR) patient portal messaging has become as 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.

OBJECTIVES

This evaluation explores the factors in clinician gender disparity in EHR messaging burden.

METHODS

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 on the types of patient-initiated messages to primary care clinicians and subsequently on all messages across the UVMHN.

RESULTS

Female clinicians received significantly more patient-initiated medical advice requests than their male counterparts (68.28 vs. 49.22 messages/month, p=0.005) and spent more time managing messages (1.85 vs. 1.35 min/day, p=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 patients send more messages than male patients. (59 vs. 52 messages/female vs. male, p=0.001). Panels size and complexity were similar for both male and female providers.

CONCLUSIONS

These findings highlight an unequal messaging burden for female clinicians, largely due to patient demographics. Patient panel complexity and clinician full-time equivalent (FTE) 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 AI-driven message triage systems may help to mitigate the burden on female clinicians and promote greater equity in primary care.