Maximizing Resource Allocation and Workflow Efficiency in Healthcare via Computer Vision and AI: Creating Intelligent Systems for Managing Patient Flow, Staffing, and Equipment Utilization

Abstract

Efficient resource allocation and workflow management are critical challenges in healthcare systems worldwide. Suboptimal utilization of resources, including staffing, equipment, and facilities, can lead to increased healthcare costs, prolonged waiting times, and compromised patient care. Computer vision and artificial intelligence (AI) technologies offer a promising solution to optimize resource allocation and workflow efficiency in healthcare settings. This research article explores the development of intelligent systems leveraging computer vision and AI algorithms for patient flow management, staffing optimization, and equipment utilization. By examining case studies, current research, and future prospects, we aim to highlight the potential of these technologies in streamlining healthcare operations, reducing costs, and improving patient outcomes. The article also discusses the challenges and considerations associated with the implementation of AI-driven resource allocation systems, including data privacy, system interoperability, and the need for human-AI collaboration.