ROBOT-ASSISTED SURGERIES OPERATIONS MANAGEMENT: A COMPREHENSIVE ANALYSIS, BENCHMARKING, AND CASE STUDY

Abstract

In recent years, Robot-Assisted Surgeries (RAS) have undergone significant advancements, resulting in improved patient outcomes, faster recovery times, and enhanced surgical precision. This study aims to: (1) Examine the Operational Management of Robotic-Assisted Surgeries (OM-RAS), (2) Benchmark the strategic implementation of RAS in Qatar with the Middle East and the globe, (3) Conduct a case study using real data to provide improvement strategies. In the first phase of this thesis conducted an extensive literature review. The findings revealed the heavy influence of emerging technologies on OM-RAS, impacting workflow optimization, performance enhancement, and skill assessment. However, challenges such as implementation costs and seamless technology integration persist despite notable operational improvements. The benchmarking highlighted a global upsurge in the number of procedures over the past decade, marking significant advancements in RAS technology. In Qatar, there is a budding opportunity to embrace RAS technology more broadly, with 11 producers across 4 medical specialties poised for integration. While the private sector's RAS procedures are limited, its potential to catalyze broader adoption in Qatar's healthcare future is significant. In the third phase, a collaboration with a large surgical center assessed the impact of a new bleeding control technique on operational Key Performance Indicators (KPIs) during RAS of Partial Nephrectomy. The analysis compared the effectiveness of using the VerisetTM hemostatic patch alone versus combining it with suturing across four hypotheses. Findings indicated that combining suturing with VerisetTM significantly reduced Length of Stay (LOS) and Post-Anesthesia Care Unit (PACU) times without affecting Warm Ischemia Time (WIT) and Operation Time (OT). Five managerial recommendations and several future research directions were identified based on these results.

Date of Award	2024
Original language	American English
Awarding Institution	HBKU College of Science and Engineering