Predictive Analytics and Workflow Automation to Reduce Administrative Burden and Clinician Burnout in United States Clinical Settings: A Systematic Review.

Published in Advances in health information science and practice. Abstract: Electronic health record (EHR)-related administrative burden remains a frequently cited contributor to clinician burnout in the United States. Although digital systems were implemented to improve quality, safety, and care coordination, expanded documentation requirements, inbox messaging, and regulatory reporting have increased clerical workload. Traditional interruptive clinical decision support tools may further increase cognitive demands through alert fatigue and workflow disruption. Health systems have increasingly adopted predictive analytics and workflow-integrated automation, including ambient artificial intelligence (AI) documentation, inbox prioritization, and audit log-based workflow monitoring. However, their effects on operational efficiency and clinician well-being remain uncertain. This review examined clinician-facing interventions in US clinical settings and their impact on documentation workload, operational efficiency, and burnout-related outcomes. A systematic review guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses was conducted using PubMed, CINAHL, and Embase. The search included English-language studies published between January 1, 2019, and December 31, 2025, with an updated search capturing eligible early online publications through 2026. Eligible studies evaluated clinician-facing predictive analytics or workflow automation in US clinical settings and reported measurable outcomes, including documentation time, after-hours E...