Operating theatre efficiency remains a crucial concern within health care systems, directly influencing the timeliness and effectiveness of surgical care. It is important for a variety of reasons, including patient satisfaction, cost savings, medical team morale, improved infection control, and reduced turnaround time. However, persistent challenges like surgical delays, suboptimal scheduling, and inefficient resource allocation persist. Artificial Intelligence (AI) has emerged as a promising avenue to address these challenges and optimize operating theatre efficiency. This article provides an in-depth exploration of the implications of AI in improving surgical punctuality, scheduling precision, and resource allocation.
Key components of AI-driven strategies encompass machine
learning models, intelligent management systems, and optimization algorithms.
Recent research demonstrates that machine learning models exhibit remarkable
accuracy in predicting surgical case durations, leading to improved and
streamlined surgical scheduling and punctuality. Simultaneously, intelligent
management systems play a pivotal role in facilitating, patient flow
management, and optimizing resource distribution. The application of
optimization algorithms, including genetic algorithms, is instrumental in
resolving intricate scheduling dilemmas and curtailing waiting times.
Optimization algorithms improve operating theatre efficiency by minimizing
downtime, reducing patient waiting times, and maximizing resource utilization
through careful scheduling. The integration of AI into efforts to enhance
operating theatre efficiency promises numerous benefits, including improved
patient care standards, reduced costs, and heightened operational efficiency.
However, challenges pertaining to data quality, interpretability, and
organizational adaptability, need to be addressed rigorously. Ethical and legal
considerations of patient privacy, data security, and algorithm biases must be
scrupulously managed while using AI in healthcare. To harness AI's full
potential, future advancements should focus on real-time data analytics,
predictive modeling, and autonomous decision-making. These inferences from this
article underscore AI's transformative impact on optimizing operating theatre
efficiency and emphasise the need for well-defined ethical guidelines and
comprehensive regulations to ensure responsible implementation.
Author (s)
details:-
Wiam El
Jellouli
Department of Surgery and Scientific Research, Faculty of Medicine and
Pharmacy, Mohammed V University, Rabat, Morocco.
Wiam El
Jellouli
Department of Surgery and Scientific Research, Faculty of Medicine and
Pharmacy, Mohammed V University, Rabat, Morocco.
Wiam El
Jellouli
Department of Surgery and Scientific Research, Faculty of Medicine and
Pharmacy, Mohammed V University, Rabat, Morocco.
Mohamed
Alioui
Department of Surgery, Anesthesiology and Intensive Care, Faculty of
Medicine and Pharmacy, Mohammed V, Military Hospital, Mohammed V University,
Rabat, Morocco.
Houda Nadir
Department of Surgery and Scientific Research, Faculty of Medicine and
Pharmacy, Mohammed V University, Rabat, Morocco.
Mustapha
Bensghir
Department of Surgery, Anesthesiology and Intensive Care, Faculty of
Medicine and Pharmacy, Mohammed V, Military Hospital, Mohammed V University,
Rabat, Morocco.
Khalil Abou
Elalaa (Head of the Operating Room Theatre)
Department of Surgery, Anesthesiology and Intensive Care, Faculty of
Medicine and Pharmacy, Mohammed V, Military Hospital, Mohammed V University,
Rabat, Morocco.
Please See the book here :-
https://doi.org/10.9734/bpi/mria/v1/8430E
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