Ethical concerns of AI in healthcare: A systematic review of qualitative studies

Abstract

With the rapid penetration of artificial intelligence (AI) in healthcare, its associated ethical issues have become increasingly prominent. However, existing research often lacks systematic approaches and fails to explore cognitive differences thoroughly among healthcare professionals across regions, professions, and departments. To address this gap, this study systematically retrieved 19 qualitative studies from Embase, PubMed, and Web of Science databases. Quality was assessed using the JBI-QARI tool, and data were analyzed through thematic analysis, encompassing healthcare professionals from diverse backgrounds. Findings reveal that while AI enhances diagnostic accuracy and optimizes resource allocation, it also triggers ethical dilemmas such as algorithmic bias, data privacy breaches, and ambiguous accountability. Furthermore, cultural, resource, and policy disparities across regions significantly influence healthcare professionals' perceptions, while differing professional roles and departmental responsibilities lead to distinct ethical priorities. Thus, AI applications in healthcare face multidimensional ethical challenges that disrupt practitioners' workflows while profoundly impacting patient rights protection and healthcare system operations. Future efforts must develop systematic solutions across technological R&D, responsibility allocation, data security, and personnel training to balance innovation with ethics and advance sustainable AI-driven healthcare.

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