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Robotic Assisted Surgical Systems (RASS) in healthcare management

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Robotically Assisted Surgical Systems (RASS) have been used in carrying out over 7 million surgical procedures, since their emergence in the 1970s (Klodmann et al., 2021). The use of the systems has eased the workload of medical practitioners, for example, the positions held by the robot arms during surgery, create opportunity for surgical assistants to focus on other tasks (Klodmann et al., 2021). More so, Robotic Assisted Surgery (RAS) is gradually gaining predominance globally (Peters et al., 2018). Its size, specialty, use and versatility have evolved over the years (Brodie & Vasdev, n.d.). The use of RAS has enhanced ergonomics, tissue magnification, precision, improved training and seamless workflow, thus reducing the need for human assistants during surgical operations (McLeod, Melder & Da Vinci, 2005; Moawad et al., 2020). However, the significance of its influence on patients’ wellbeing and clinical practices is still under study by researchers, and the adoption of RASS in healthcare practices is expected to grow exponentially in the next decade (Brodie & Vasdev, n.d.). The adoption of RAS in healthcare practices is quite expensive and it requires changes in behavioural pattern as regards to surgery, which can be complex and difficult. Therefore, it is advisable to get the required training on the usage and application, before adopting it in surgical practices (Atkins et al., 2017). This article assesses the pros and cons of RAS while looking at its concept, use, advantage and Hazards.
Original languageEnglish
Title of host publicationAdvanced Manufacturing and Automation XIV: Conference proceedings
EditorsYi Wang, Tao Yu, Kesheng Wang
PublisherSpringer
Pages403-408
Number of pages6
ISBN (Print)9789819626243
DOIs
Publication statusPublished - 14 Feb 2025
EventAdvanced Manufacturing and Automation XIV - Kunming
Duration: 11 Oct 202412 Oct 2024

Publication series

NameLecture Notes in Electrical Engineering
Volume1364 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceAdvanced Manufacturing and Automation XIV
CityKunming
Period11/10/2412/10/24
OtherAdvanced Manufacturing and Automation XIV (11/10/2024-12/10/2024, Kunming )

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Digital medical services
  • Health industry
  • Robotics
  • artificial intelligence
  • Artificial Intelligence
  • Information systems

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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