LITERATURE REVIEW: DAMPAK IMPLEMENTASI AI (ARTIFICIAL INTELLIGENCE) TERHADAP EFISIENSI OPERASIONAL DAN KINERJA KEUANGAN RUMAH SAKIT

Abstract

The implementation of Artificial Intelligence (AI) in the healthcare sector has become a key driver of hospital operational transformation. This study analyzes the impact of AI implementation on hospital operational efficiency and financial performance through a comprehensive literature review. The results show that AI technology, specifically Natural Language Processing (NLP), predictive analytics, and machine learning, can reduce administrative burdens by up to 45%, improve documentation accuracy, and accelerate insurance claims processing. The integration of AI into Clinical Decision Support Systems (CDSS) has been shown to improve diagnostic accuracy in radiology, dermatology, and cardiology, reduce clinical errors, and accelerate medical decision-making. Furthermore, AI enables prediction of hospitalization needs, length of stay (LOS), and emergency triage, thereby improving the effectiveness of resource allocation and scheduling of medical personnel. On the financial side, various studies have shown that AI contributes to cost savings through reduced medical errors, supply chain optimization, and improved revenue cycle management. However, implementation barriers remain, primarily related to high initial investment, limited system interoperability, and limited human resource readiness. This study confirms that the benefits of AI are multidimensional and increasingly relevant for improving hospital competitiveness, with higher ROI in larger institutions with better data integration capabilities. These findings provide an important foundation for formulating future hospital digitalization strategies.