AI for Healthcare Workflow Optimization: Reducing Burnout and Enhancing Efficiency

Abstract

Healthcare systems are burdened by inefficiencies and administrative overload, contributing to clinician burnout. This paper explores how AI is streamlining workflows through automated scheduling, intelligent resource allocation, and real-time data analytics. Case studies include AI tools for automating medical coding, managing patient queues, and optimizing operating room schedules. The discussion also covers challenges such as resistance to AI adoption, the need for workforce training, and ensuring transparency in AI-driven decisions.