Advancements and challenges in robotic surgery: A holistic examination of operational dynamics and future directions.

BACKGROUND

In recent years, Robot-Assisted Surgeries (RAS) have advanced significantly, revolutionizing healthcare with better patient outcomes, faster recovery times, and greater surgical accuracy. However, challenges such as restricted maneuverability and communication issues persist, along with the need to evaluate surgeons' proficiency in RAS. Healthcare 5.0 seeks to enhance RAS by integrating technologies like advanced imaging, haptic feedback, and artificial intelligence.

OBJECTIVE

This paper explores the Operational Management of Robotic-Assisted Surgeries (OM-RAS) by analyzing recent research. It assesses surgical robotics operations, workflow optimization, performance enhancement, and skill assessment. Additionally, it examines challenges and gaps in the RAS domain, providing a comprehensive research overview.

METHODS

A comprehensive literature search was conducted across databases such as Scopus, Web of Science, and Google Scholar, covering publications up to the third quarter of 2023. Search terms were selected using scientific criteria and validated by experts, resulting in a substantial document collection. A rigorous screening process, aligned with PRISMA 2020 standards, filtered the selection to 50 research papers, forming the foundation for detailed investigation.

FINDINGS

OM-RAS is a multidimensional field influenced by emerging technologies that optimize workflows, enhance performance, and improve skill assessment in RAS. Despite superior outcomes, challenges such as implementation costs and seamless technology integration persist. Additionally, research gaps exist regarding RAS benefits, creating opportunities for efficiency enhancement in patient care. Further exploration of RAS procedure scheduling across different surgery types is essential.

CONCLUSION

Integrating advanced technologies into RAS has improved surgical outcomes, shortened hospital stays, and enhanced working environments. This study advocates for a holistic multi-criteria decision-making approach, considering factors like kinematics, imaging, Internet of Things/Tactile Internet (IoT/TI), and AI. It provides valuable insights, guiding future research and shaping OM-RAS studies.