AI is revolutionizing patient safety during anesthesia. Here’s how

AI now helps measure how deeply the brain is anesthetized while a patient is asleep

Driven by Artificial Intelligence (AI), anesthesiology is experiencing substantial transformations, especially so in the areas of patient monitoring and safety devices. Gradual but steady improvements have continued to happen in anesthesiology. Today, we have reached a stage where the anesthesia administered is so accurate that patients can be up and about active in just a few minutes following surgery. 

 “Artificial Intelligence has been the real game-changer in anesthesia,” said Dr. Aman Sai G, an assistant professor at the Anesthesiology Department at GITAM Institute of Medical Sciences and Research (GIMSR),

“In this digital era, AI has pervaded all aspects of medicine, including anesthesiology. It is supporting anesthesiologists with improved patient monitoring, accurate drug control, postoperative pain management, and timely treatment of acute postoperative complications,” Dr. Aman added. 

AI Algorithms: Backbone of Modern Anesthesiology

AI algorithms, based on bounded solution space, efficient search, and termination criteria, are being developed.

“These algorithms incorporate the ability to learn from experience or training to perform a task by being shown a large set of example inputs to a problem and the desired responses of the system,” Dr Aman said. 

These algorithms form the basis for AI-supported closed loops, designed for the pharmacological maintenance of anesthesia and hemodynamic management. They offer real-time feedback to prevent adverse events, resulting in improved patient safety.

Intraoperative Anesthesia Management

Intraoperative Anesthesia Management, a significant aspect of anesthesiology, involves patient monitoring and precise drug control during surgery. Any error in this process could have dire consequences. However, with AI, these tasks have become efficient and accurate. 

AI now helps measure how deeply the brain is anesthetized while a patient is asleep. This advancement has greatly helped medical professionals in controlling the patient’s bodily functions safely during surgery.

Dr. Aman explains: “With the help of AI, we have been able to develop precise and reproducible interventions in complex surgeries and anesthesia management.”

 AI has taken over repetitive tasks, enabling anesthesiologists to focus on overall assessment and decision-making. As a result, clinical decision support systems have been designed to offer relevant recommendations based on the clinical scenario to aid decision-making.

The role of AI in anesthesiology extends beyond monitoring and drug control. It has facilitated the development of innovative devices and systems like the Kepler intubation system, Automated intubation robotic system (AIRS), McSleepy control loop, and MySurgeryRisk score, all designed to enhance patient safety.

Patient Safety Device Monitoring in Anesthesia

Thanks to technological advancements, monitoring has become less invasive. For instance, non-invasive assessment of cardiac output is now possible using a blood pressure cuff applied to the finger. Similarly, intracranial tissue oxygen saturation can be measured using cerebral pulse oximetry, aiding in brain autoregulation assessment.

Target-Controlled Infusion (TCI) Devices: Enhancing Safety

TCI devices have been instrumental in improving patient safety. These computer-controlled infusion pumps administer anesthetic drugs based on the patient’s parameters, ensuring accurate and controlled doses.

Dr. Aman elaborates on the benefits of TCI, “The use of Target Controlled Infusion as a part of anesthesia delivery resulted in the precision, reliability, efficacy, and safety of intravenous anesthesia delivery.”

Challenges in Implementing AI in Anesthesia

Despite the significant strides, the path to integrating AI into anesthesiology isn’t without challenges. Few AI-based studies focus on the integration of AI into the daily clinical workflow in anesthesia, and even fewer demonstrate a significant impact on clinical outcomes.

Data ethics is a critical issue that needs addressing, particularly regarding informed consent, privacy, data protection, ownership, objectivity, and transparency. Further, data quality is fundamental for building accurate AI algorithms. A potential source of bias, data quality needs stringent control and regulation. 

Dr. Aman highlights the need for collaboration: “Strong collaboration is required among clinicians, scientists, manufacturers, regulators, and administrators for proper data storage and exchange.”

Future of Anesthesiology with AI

With the rise of AI, anesthesiology is set to evolve significantly. It can aid in risk stratification, prediction of a difficult airway, and even help in checking the completeness of the preoperative checklist. AI-assisted anesthesia simulations are also expected to enhance the quality of education in anesthesiology.

Dr. Aman envisages a future where “AI would replace complex monitors and machines with single-button anesthesia machines enhancing the patient experience with better patient outcomes, with lesser complications and real-time results.”

While AI algorithms have not yet surpassed human performance, their ability to quickly and accurately sift through large amounts of data and discover correlations and patterns imperceptible to human cognition makes them an invaluable tool for clinicians.

As the world strides towards a future dominated by technology, it is undeniable that AI’s role in anesthesiology will be pivotal. With its potential to enhance patient safety and improve clinical outcomes, AI seems poised to redefine the future of anesthesiology.

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