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

<p style="text-align: justify;">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.</p>

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Publication Details

Journal
AFMN Biomedicine
Published
2024-12-01
DOI
https://doi.org/10.5937/afmnai42-54811
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

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

Tatjana Kilibarda, Tanja Prodović, Novica Bojanić, Šćepan Sinanović et al.
AFMN Biomedicine
Artificial Intelligence in Healthcare and Education
article

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

Tatjana Kilibarda, Tanja Prodović, Novica Bojanić, Šćepan Sinanović, Saša Bubanj, Milić Kimi
article en

Abstract

<p style="text-align: justify;">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.</p>

AFMN BiomedicineVol. 42(2)
University of Nis (RS)
Openalex Percentile: Top 78%
Artificial Intelligence in Healthcare and Education
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