New developments in information technology are revolutionizing healthcare operations by providing new ways to optimize operational efficiency and reduce costs. Among the methods are artificial intelligence, machine learning, agile methodologies, and robotic process automation. These systems can improve operations by learning from past data to predict future trends, avoid pitfalls, and automate repetitive, mundane tasks. This study measured the impact of using an Al-based algorithm within a multi-center radiology practice to increase operational efficiency by predicting and filling unutilized capacity which reduces patient wait times. The study was conducted over 31 weeks and demonstrated a 71% reduction in patient wait time from 7 days to 2 days and a 6% increase in the utilization of CT and MRI machines with no increase in workload for the scheduling staff or the working hours of the operational staff. While this study has limitations, standards for Al-based algorithms in healthcare are needed to reduce bias, improve equity, and establish trust in this technology.
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