Overcoming Barriers to Robotic Surgery Integration: A Literature Analysis for Improved Patient Outcomes and Healthcare Efficiency
2025 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 HE credits
Student thesis
Abstract [en]
Robotic surgery has rapidly been developed into a more central technique within modern healthcare and offering increased precision, shorter recovery times and reduced surgical trauma but still these advantages, does integration of robotic surgery face challenges. This study identifies the major obstacles, including technical limitations like lack of haptic feedback and advanced imaging technology, educational issues related to standardized training like socio economic factors such as high costs and uneven distribution of resources.
A systematic review was conducted to analyse these obstacles and suggest solutions. The results demonstrated that including piezoelectric sensors and AI based decision making could improve precision and safety by reducing the risk of accidental tissue damage and excessive force application. These technologies provide real time feedback and predictive analytic that improve surgeons’ more accuracy and reduce complications. In addition, can national education programs with VR based simulators reduce the learning curve and increase surgeons’competence. Socio eco-nomic challenges like high costs and uneven access robotic to systems, could be handled through national strategies and government subsidies.
The study concluded that if these obstacles could be overcome. could a wider usage of robotic system in Sweden lead to improved patient outcome through fewer complications, shorter hospital stays and higher surgical precision. Future research should focus on cost efficiency, regional differences and the implementation of proposed solutions in practice.
Place, publisher, year, edition, pages
2025. , p. 26
Keywords [en]
Robotic surgery, Haptic Feedback in Robotic Surgery, AI in Robotic-Assisted Surgery, Technical Barriers, Invasive Surgery
National Category
Robotics and automation
Identifiers
URN: urn:nbn:se:hv:diva-23189Local ID: EXR600OAI: oai:DiVA.org:hv-23189DiVA, id: diva2:1946976
Subject / course
Robotics
Educational program
Master in robotics and automation
Supervisors
Examiners
Note
21 Hp
2025-04-092025-03-242025-09-30Bibliographically approved