Enhancing Healthcare Administrative Efficiency through Artificial Intelligence–Driven Decision Support Systems

Abstract

Aim: This study examines the impact of Artificial Intelligence–Driven Decision Support Systems (AI-DSS) on enhancing administrative efficiency in healthcare organizations. Conducted across public and private healthcare facilities in Saudi Arabia, the study surveyed 357 healthcare administrators, decision-makers, and operational staff using a structured five-point Likert scale.

    Findings indicate that AI-DSS significantly improves administrative decision accuracy, reduces time delays, enhances resource allocation, and supports predictive planning. AI-based tools, including machine learning algorithms and predictive analytics, were shown to reduce human error and improve workflow efficiency. Regression analysis revealed a strong positive relationship between the use of AI-DSS and administrative performance indicators.

    The study recommends expanding AI adoption across healthcare facilities, improving digital infrastructure, and training healthcare administrators to optimize the use of AI-driven tools.

    In addition, the study highlights the strategic importance of integrating AI-DSS within healthcare administrative frameworks to support evidence-based decision-making and long-term organizational sustainability. The findings suggest that AI-driven systems can play a critical role in strengthening institutional resilience, improving responsiveness to dynamic healthcare demands, and enhancing overall administrative governance. By leveraging real-time data and predictive capabilities, healthcare organizations can better anticipate operational challenges, allocate resources more effectively, and maintain high standards of administrative performance. Consequently, the adoption of AI-DSS represents a key driver for advancing modern healthcare administration in rapidly evolving healthcare environments.

https://doi.org/10.24897/acn.64.68.20251224007