Enhancing Human Resource Management in Healthcare: Integrating AI for Improved Work Efficiency and Reduced Burnout
Keywords:
Artificial intelligence, Burnout, Healthcare, Human Resource Management, Work efficiencyAbstract
Burnout among healthcare professionals continues to be a critical issue worldwide, affecting their psychological well-being, job satisfaction, and care quality. The integration of artificial intelligence (AI) in healthcare has emerged as a strategic solution to enhance human resource management (HRM) by improving work efficiency and reducing burnout. This systematic review searched recent literature from PubMed, ScienceDirect and Google Scholar including AI-related studies that measured burnout reduction or work efficiency among healthcare workers. The result showed the large language model was the most frequently applied approach across 13 countries. Burnout reduction via AI is most effective when systems are integrated with behavior-sensitive feedback or designed to offload documentation. AI's impact on work efficiency is well-supported such as time reduction and improved scheduling. Efficiency-focused AI interventions tend to yield faster observable benefits. Key challenges including system integration, clinician trust, interpretability of AI decisions, and ethical concerns. These findings offer valuable guidance of practical AI in healthcare that can support sustainable HRM practices by improving time efficiency, promoting workforce well-being, and maintaining care quality.
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