Vol. 1 No. 1 (2026): ARTIFICIAL INTELLIGENCE IN HEALTHCARE WITH EMPHASIS ON SURGICAL DISCIPLINES: A MIXED-METHODS EVALUATION OF IMPLEMENTATION AND OUTCOMES

This study evaluates the implementation and impact of artificial intelligence (AI) in healthcare, with a particular focus on surgical disciplines. A mixed-methods approach was used to assess clinical outcomes, operational efficiency, and adoption patterns across multi-center surgical settings.

The findings indicate that AI integration significantly improved operational performance, including reductions in hospital length of stay and ICU admissions. At the same time, key clinical outcomes such as complications, readmissions, and mortality remained stable, supporting the safety of AI implementation in surgical workflows.

Increased adoption of AI tools, improved staff training, and enhanced perceptions of usability, governance, and trust contributed to successful implementation. The study highlights the importance of aligning AI systems with clinical workflows to maximize effectiveness.

However, challenges such as alert fatigue, data integration issues, and equity considerations in diverse patient populations remain critical. Addressing these factors is essential for ensuring safe and scalable deployment of AI technologies in healthcare systems.

Overall, artificial intelligence demonstrates strong potential to enhance surgical care delivery by improving efficiency and decision-making, while requiring robust governance frameworks and continuous monitoring to ensure long-term value.