Sevo Sistas

Artificial Intelligence is not going to replace you! 6 ways AI will assist Anesthesiologists

Elisha Peterson MD MEd FAAP FASA

In today's episode, we delve into the exciting realm of Artificial Intelligence (AI) in anesthesiology, uncovering its potential to revolutionize hospital systems and patient safety.

  • We'll address common concerns about AI taking over jobs and emphasize why the human touch remains irreplaceable in healthcare.

Segment 1: The Human Connection

  • AI's role in healthcare isn't about replacing physicians; it's about augmenting their abilities.
  • Patients seek a unique connection with their physicians that AI can't replicate.
  • AI can reduce administrative tasks and enhance our focus on patients, such as minimizing Electronic Health Record (EHR) documentation.

Segment 2: AI in Anesthesiology - A Scoping Review

  • We draw insights from two key papers:
    1.  Daniel A. Hashimoto, Elan Witkowski, Lei Gao, Ozanan Meireles, Guy Rosman; Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations. Anesthesiology 2020; 132:379–394 

  • 2.  Bellini V, Valente M, Gaddi AV, Pelosi P, Bignami E. Artificial intelligence and telemedicine in anesthesia: potential and problems. Minerva Anestesiol. 2022 Sep;88(9):729-734. doi: 10.23736/S0375-9393.21.16241-8. Epub 2022 Feb 14. PMID: 35164492.

Segment 3: 6 Key Themes of AI in the Operating Room (OR)

Preoperatively

  1. Event Prediction: AI can classify ASA status, predict difficult airways, and recommend optimal anesthesia methods, enhancing safety.

Intraop
2. Depth of Anesthesia Assessment: AI, alongside BIS (Bispectral Index Monitoring), assesses the depth of anesthesia.

  • AI's accuracy surpasses BIS in assessing depth, reducing the risk of intraoperative awareness

3.  Control of Anesthesia Delivery: AI automates the delivery of paralytics and predicts drug pharmacokinetics for precise titration.

4.  Ultrasound Guidance: AI assists in identifying critical structures during ultrasound, such as arteries and ideal vertebral levels for epidural placement.

5.  Pain Management: AI analyzes whole-brain MRI to understand patients' responses to pain stimuli, improving our understanding of pain perception.

6.  OR Logistics: AI attempts to optimize OR scheduling, staffing, and team dynamics but faces challenges due to the complexity of the OR environment
                       Real-world data is essential for improving AI's accuracy in this domain.

Conclusion

  • While AI holds immense promise in anesthesiology, we must ensure it is fed with diverse and representative data to avoid perpetuating healthcare disparities.
  • Pain is a personal experience, and AI must complement, not replace, our understanding of patients' pain.
  • AI is a tool that can enhance efficiency and patient safety, but it will always work alongside the human touch in healthcare.

Remember the words of Rodney Brooks, an Australian roboticist and entrepreneur: "Artificial intelligence is a tool, not a threat." AI's potential lies in its ability to support healthcare professionals and ultimately improve patient outcomes

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