Does Artificial Intelligence (AI)-based Applications Improve Operational Efficiency in Healthcare Organizations?: Opportunities and Challenges

Abstract

Purpose: This study investigates whether adoption of AI-based systems and technologies improve operational efficiency in healthcare organizations through a systematic review of the literature and real-world examples.Methods: In this study, we divided the AI application cases into care services and administrative functions, then we explored opportunities and challenges in each area.Results: The analysis results indicate that the care service field primarily uses AI-based systems and technologies for quick disease diagnosis and treatment, surgery and disease prediction, and the provision of personalized healthcare services. In the administrative field, AI-based systems and technologies are used to streamline processes and automate tasks for the following functions: patient monitoring through virtual care support systems; automating patient management systems for appointment times, reservations, changes, and no-shows; facilitating patient-medical staff interaction and feedback through interaction support systems; and managing admission and discharge procedures.Conclusion: The results of this study provide valuable insights and significant implications about the application of AI-based systems or technologies for various innovation opportunities in healthcare organizations. As digital transformation accelerates across all industries, these findings provide valuable information to managers of hospitals that are interested in AI adoption, as well as for policymakers involved in the formulation of medical regulations and laws.

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