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Received : 15-11-2023

Accepted : 22-11-2023



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Get Permission Gupta: The evolution of anesthesia: Embracing emerging technologies and AI

Anesthesia is at the forefront of technical advancement in the quickly evolving field of healthcare. New technologies and artificial intelligence (AI) are redefining anesthetic delivery with never-before-seen efficiency, safety, and precision. The management and administration of anesthesia are about to undergo a revolutionary change because of the combination of AI and technological advancement. These changes are reflected in innovative monitoring systems to predictive analytics with the potential to enhance patient safety and simplify anesthetic procedures. This article explores into how these innovations are transforming the field, emphasizing their potential advantages and addressing the limitations that arise with such rapid advancements.

Recent Advancements in Healthcare Technology

Recent developments in healthcare have seen the surge of Internet of Things (IoT), AI, and Blockchain technologies.1 These advancements have refined healthcare with promising results. In the field of anesthesia, AI has been successfully utilized in perioperative risk assessment, deep monitoring, automatic drug administration, and teaching and training. These advancements hold the promise of improving the standardization and efficiency of clinical workflows and reducing errors and costs across all healthcare settings.

Automated Monitoring Systems

Recent breakthroughs in the field of anesthesia have presented advanced automated monitoring systems powered by artificial intelligence (AI) and machine learning.2, 3 These systems play a crucial role during surgery by continuously analysing vital signs such as heart rate, blood pressure, and oxygen saturation. They provide real-time data and alert anaesthetists to any deviations from the norm. The use of these technologies holds the potential to prevent complications and significantly improve patient safety during surgical procedures.

Tailoring Anesthesia with Predictive Analytics

The integration of AI in anesthesia has mastered the art of predictive analytics, helping healthcare professionals in early detection of patient's risk factors and predicting their unique response to anesthesia.4 By analysing extensive patient data, including medical history, genetic information, and physiological parameters, AI algorithms identify patterns and trends that may not be easily deceptive to human providers. This personalized approach enables anesthesiologists to tailor their anesthesia delivery, optimizing dosing, minimizing side effects, and ultimately improving patient outcomes.

Precision Medicine in Anesthesia

Precision medicine as a rapidly evolving concept is primarily based on individualized medicine with the amalgam of genomics, bioengineering, and big data science.3, 5 This approach involves tailoring anesthesia based on individual patient characteristics, genetics, and responses. With the integration of AI, machine learning algorithms can predict how patients will respond to anesthesia drugs. This enables anesthesiologists to customize dosage levels, minimizing adverse effects and improving overall perioperative outcomes. Precision medicine in anesthesia is an efficient, safe, and cost-effective step toward establishing a new paradigm of healthcare services.5, 6

Telemedicine in Anesthesia Consultations

The integration of telemedicine in anesthesia consultations represents a significant advancement in preoperative care. Anesthesiologists can now remotely evaluate patients' medical histories, discuss potential risks, and provide necessary recommendations. This not only improves accessibility for patients in remote areas but also streamlines the preoperative workflow. The use of telemedicine in anesthesia consultations further optimizes resources and allows for more efficient use of healthcare services, ultimately contributing to a more patient-centred and accessible healthcare system.7

Robotic-Assisted Surgery and Anesthesia

Robotic-assisted surgery, coupled with AI-driven anesthesia, represents a deep collaboration of technological prodigies. Robotics allow for minimally invasive procedures with increased precision, while AI in anesthesia ensures optimal sedation levels and physiological stability throughout the surgery.8 Collaborative robots, or cobots, work alongside anesthesiologists, streamlining tasks and enhancing efficiency. This collaborative approach not only enhances the precision of surgical procedures but also minimizes the physical strain on healthcare providers.

Training and Skill Enhancement for Healthcare Professionals

As technology becomes increasingly integral to anesthesia practice, there is a growing need for training and skill enhancement among healthcare professionals. Anesthesiologists and anesthesia providers must not only possess traditional medical skills but also be proficient in understanding and interpreting data from advanced technologies.9 Continuous education and training programs should be established to keep healthcare providers updated on the latest technological advancements. This ensures their competence in steering the evolving landscape of AI-driven anesthesia, contributing to enhanced patient care and safety.

Challenges in Healthcare Technology Adoption and Ethical Considerations

Bringing advanced technologies like smart sensors, IoT, AI, and Blockchain into healthcare systems faces hurdles. Managing the complexity of generated data from various compatible devices is another puzzle to solve. There's a shortage of affordable and accurate medical sensors, making data collection tricky along with rapidly emerging technologies in anesthesia. Safety and reliability are key concerns, especially as AI algorithms get more complex. To guide the responsible use of these technologies, we need strong rules and standards.10

The use of AI in anesthesia raises ethical issues such as patient privacy, information security, data sources, and the "black box" phenomenon, requiring careful consideration and adherence to ethical standards. Ethical aspects, like patient privacy and consent, need attention too. Clear guidelines for how we collect, store, and share data are vital to safeguard patient confidentiality and follow privacy rules. Balancing the benefits with ethical considerations is essential for responsible and effective use in anesthesia and healthcare.3, 10

In summary, the incorporation of emerging technologies and AI in anesthesia marks a significant change in the field of anesthesiology. These technologies, ranging from advanced monitoring to predictive analytics, hold the potential to revolutionize how anesthesia is delivered and managed, promising a more personalized and efficient experience for patients. However, successful integration demands thoughtful attention to regulatory, ethical, and workforce considerations. Collaboration among healthcare providers, policymakers, and industry stakeholders is essential for optimal patient care with advanced technologies and AI-empowered anesthesiologists. This shift not only shapes the future of anesthesia but also emphasizes the importance of a patient-centric approach in embracing these innovations.

References

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M Soori B Arezoo R Dastres Artificial intelligence, machine learning and deep learning in advanced robotics, a reviewCognitive Robotics202335470

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M Singhal L Gupta K Hirani A comprehensive analysis and review of artificial intelligence in anaesthesiaCureus2023159e45038

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M Singh G Nath Artificial intelligence and anesthesia: A narrative reviewSaudi J Anaesth20221618693

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AR Absalom JIB Glen GJC Zwart TW Schnider MMRF Struys Target-Controlled Infusion: A Mature TechnologyAnesth Analg20161221708

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S Gu Q Luo C Wen Y Zhang L Liu L Liu Application of advanced technologies-nanotechnology, genomics technology, and 3D printing technology-in precision anesthesia: A comprehensive narrative reviewPharmaceutics20231592289

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V Chatrath JP Attri R Chatrath Telemedicine and anaesthesiaIndian J Anaesth2010543199204

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TM Hemmerling Robots Will Perform Anesthesia in the Near FutureAnesthesiology2020132221920

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CW Connor Artificial intelligence and machine learning in anesthesiologyAnesthesiology [Internet]20191316134659

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L Gupta The potential of artificial intelligence in anaesthesiaIndian J Clin Anaesth20231021201



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