인공지능(AI) 기반 애플리케이션 도입이 의료기관의 운영효율성을 향상시킬까?: 기회와 도전

• Published in: 品質經營學會誌 Vol. 52; no. 3; pp. 557 - 574
• Main Authors: 이돈희, Lee Donhee
• Format: Journal Article
• Language: Korean
• Published: 한국품질경영학회 30.09.2024
• Subjects: AI-based System and Technology; Applications; Digital Transformation; Healthcare Service; Opportunities and Challenges; Quality of Data; Real-world Examples; 학제간연구; Applications; Opportunities and Challenges; Real-world Examples; Quality of Data; Digital Transformation; AI-based System and Technology; Healthcare Service
• ISSN: 1229-1889; 2287-9005
• DOI: 10.7469/JKSQM.2024.52.3.557

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.