KNOWLEDGE, ATTITUDES, AND PERCEPTIONS OF HEALTHCARE PROFESSIONALS ON THE USE OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE – A CROSS-SECTIONAL STUDY

ABSTRACT Background: Artificial Intelligence (AI) has become an increasingly integral part of healthcare systems, offering the potential to enhance diagnosis, treatment, and patient care. However, despite the growing interest in AI, the understanding of its role and implications within healthcare settings among professionals remains underexplored. This study aims to assess healthcare professionals' knowledge, attitudes, and perceptions regarding the integration of AI in clinical practices, focusing on its potential to transform healthcare delivery. Objective: The primary objective of this research is to evaluate healthcare professionals' awareness of AI technologies and their perceptions of AI’s impact on clinical decision-making, patient care, and the healthcare workforce. Additionally, the study seeks to identify the challenges and ethical concerns associated with the implementation of AI in healthcare systems. Methods: An online survey was distributed to 250 healthcare professionals, including doctors, nurses, and allied health professionals, working across different healthcare settings. The survey collected both quantitative and qualitative data regarding participants' familiarity with AI technologies, their beliefs about AI’s role in healthcare, and its potential impact on their professional practices. Quantitative data were analyzed using descriptive statistics, and qualitative responses were examined through thematic analysis to identify key themes and concerns. Results: The study revealed that while most healthcare professionals were familiar with general AI technologies, a significant gap remained in their knowledge of AI applications specific to healthcare. Approximately 60% of participants expressed optimism about AI's potential to assist in routine administrative tasks, but fewer believed AI could effectively replace complex clinical decision-making tasks. Ethical concerns, particularly regarding patient privacy and AI biases, were highlighted by 70% of respondents. Additionally, concerns about the impact of AI on job security in certain medical specialties were prevalent. Conclusion: This research underscores the promise of AI in improving healthcare efficiency and supporting clinical decision-making. However, the findings also highlight the need for enhanced education and training to equip healthcare professionals with the knowledge required to effectively integrate AI into practice. Furthermore, addressing ethical challenges and ensuring equitable access to AI technologies are essential steps in fostering a successful transition toward AI-assisted healthcare systems. Future research should focus on examining the long-term effects of AI integration and developing policies to mitigate associated risks.