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The application of artificial intelligence in the healthcare system management in the Republic of Serbia: Enhancing efficiency, predictive capacity, and decision-making

By
Milić Kimi ,
Milić Kimi
Šćepan Sinanović Orcid logo ,
Šćepan Sinanović
Tatjana Kilibarda ,
Tatjana Kilibarda
Saša Bubanj Orcid logo ,
Saša Bubanj

University of Nis , Niš , Serbia

Novica Bojanić Orcid logo ,
Novica Bojanić

University of Nis , Niš , Serbia

Tanja Prodović
Tanja Prodović

Abstract

Artificial intelligence (AI) offers transformative potential in healthcare management by enhancing predictive analytics, optimizing resource allocation, and supporting clinical decision-making. This study aims to examine the applications of AI in Serbian healthcare institutions, focusing on improving operational efficiency and patient outcomes. The research employed a cross-sectional survey conducted among 450 healthcare professionals from various levels of healthcare in Serbia (primary, secondary, and tertiary). Data were collected via an online survey during October and November 2024. Statistical analysis included methods such as ANOVA and regression analysis to evaluate the impact of AI on diagnostic accuracy, resource optimization, and patient satisfaction. The study found that AI implementation positively impacts diagnostic accuracy (88% of respondents), resource optimization (82%), and patient satisfaction (79%). Differences were observed between urban and rural areas, as well as between public and private healthcare institutions. Major challenges identified include the lack of training (75%), data privacy concerns (68%), and limited infrastructure (70%). The study confirms that AI holds significant potential to improve healthcare in Serbia, particularly in urban and private institutions with better infrastructure. However, addressing challenges related to training, data privacy, and infrastructure is crucial, especially in rural areas. A phased approach to AI implementation is recommended, focusing initially on diagnostics and resource management to maximize healthcare performance.

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