Published Paper Details:

Artificial Intelligence (AI) has emerged as a transformative force in healthcare, extending its influence beyond clinical diagnosis and patient care into the domain of healthcare finance. Healthcare organisations worldwide face increasing financial pressures arising from escalating treatment costs, complex insurance systems, billing inefficiencies, fraudulent claims, and growing demands for cost-effective service delivery. AI-powered technologies - including machine learning, natural language processing, robotic process automation, and predictive analytics - are increasingly being integrated into financial operations to improve efficiency, enhance decision-making, reduce administrative costs, and strengthen financial sustainability. This study presents a systematic review of the existing literature on the application of artificial intelligence in healthcare finance and its implications for medical economics. The review examines major areas of AI implementation, including revenue cycle management, automated medical billing, insurance claims processing, fraud detection, financial forecasting, hospital resource allocation, and cost optimisation. The study further explores how AI contributes to improving operational efficiency, minimising financial risks, enhancing transparency, and supporting evidence-based financial planning within healthcare institutions.