DOI: 10.3897/jbcr.e182990

Authors: Supriya Khade, Mohini Mahatme, Neha Meshram, Vikram Bobade

Abstract: Introduction: Artificial Intelligence (AI) has the potential to transform healthcare in various ways. It can turn large amounts of patient data into actionable information, improve public health surveillance, accelerate health responses & produce faster & more targeted research & development. In context of developing countries, the potential of AI in public health needs to be assessed. This study enables a comprehensive exploration of clinicians' views, aiming to identify actionable insights for addressing barriers to AI implementation in healthcare systems.Methodology: It is a cross-sectional study in which a pre-validated questionnaire developed. A purposive sample of 94 clinicians from various specialities taken in the study. Data is collected using a structured questionnaire designed after an extensive literature review & expert consultation. Data were analyzed using the appropriate statistical test.Results: The study identified key challenges hindering AI adoption in healthcare, based on responses from 94 clinicians. The primary barriers include insufficient infrastructure (68.5%), lack of AI-specific training (44.7%) & limited collaboration between healthcare sectors (63.8%). Clinicians' skepticism (58%) about AI’s decision-making accuracy and ethical concerns regarding patient data security (74.5%) were significant obstacles. Fragmented healthcare data systems (70%) further hindered the effective AI integration.Conclusion: While AI has substantial potential to enhance healthcare delivery, particularly in optimizing operations and personalizing treatment, addressing these challenges through comprehensive strategies involving ethical frameworks, robust data management & stakeholder engagement is crucial for successful implementation & acceptance of AI technologies in clinical practice.

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