Episode #152 Addressing the Quintuple Aim for Healthcare Delivery During Anesthesia Care with AI

Hello and welcome back to the Anesthesia Patient Safety Podcast.  My name is Alli Bechtel, and I am your host. Thank you for joining us for another show. Chat GPT came up with this opening for our show today:

“Welcome back to our podcast series on the relationship between artificial intelligence and anesthesia patient safety. In the previous episode, we discussed how AI technology can be used to improve patient outcomes and reduce risks associated with anesthesia. We explored various applications of AI in the field, from predicting adverse events to optimizing dosing and providing real-time feedback to clinicians.

In this second part of the series, we will delve deeper into the topic and examine some of the challenges and ethical considerations surrounding the use of AI in anesthesia. We will explore issues such as data privacy, bias, and the potential for over-reliance on technology, as well as discussing ways to address these challenges and ensure that patient safety remains the top priority.

So, join us as we continue our exploration of the fascinating and rapidly evolving field of AI and anesthesia patient safety.”

Before we dive into the episode today, we’d like to recognize Masimo, a major corporate supporter of APSF. Masimo has generously provided unrestricted support to further our vision that “no one shall be harmed by anesthesia care”. Thank you, Masimo – we wouldn’t be able to do all that we do without you!”

And thank you to Chat GPT for helping to kick off the show today. Our featured article is from the February 2023 APSF Newsletter. It is “Artificial Intelligence, Patient Safety, and Achieving the Quintuple Aim in Anesthesiology” by Jonathan Tan and Maxime Cannesson. To follow along with us, head over to APSF.org and click on the Newsletter Heading. First one down is the current issue, and this article is right at the top of the page, or you can click on the fifth one down, Newsletter archives, then click on February 2023 and you will see the article at the top of the page. I will include a link in the show notes as well.

Last week, we talked about artificial intelligence or AI as an emerging technology and the likely impact on anesthesia patient safety. We talked about some of the challenges for keep patients safe during anesthesia care that include:

• Complex patients with multiple significant co-morbidities
• The speed of care delivery
• Scale of health systems
• Challenges in multispecialty communication
• Massive volume of data generated.

Anesthesia professionals must be ready to face these challenges by increasing their knowledge, presence, and effectiveness during the perioperative phases of care and AI is here to help especially with ongoing staffing shortages and increasing production pressures.

We also defined AI as the ability of a computer or device to analyze a large volume of complex health care data, reveal knowledge, identify risks and opportunities, and support improved decision-making. Plus, we reviewed several AI technologies including machine learning, natural language processing, and combining AI with clinical decision support with graphic user interfaces.

Last week, we talked about the Quintuple Aim, and I mentioned that there will be a quiz this week. Well, get your pencils ready because who can tell me the 5 aims for optimal health care delivery. Just go ahead and write them down now.

[Jeopardy Music]

Here are the answers:

1. Patient Experience
2. Population Health
3. Lower Costs
4. Clinician Well-being
5. Health Equity

How’d did you do on the quiz? Don’t worry, everyone tuning into this podcast gets a gold star!

Today, we are going to pick up right where we left off last week. Check out Figure 2 in the article which includes a framework that describes options for AI to help improve anesthesia patient safety throughout the perioperative environment with a focus on the quintuple aim. I will include it in the show notes as well. This figure takes us through the preoperative, intraoperative, and postoperative phases of care and the relationships with the 5 aims and with artificial intelligence. Let’s review them now.

The first row is the preoperative phase. For patient experience, considerations include leveraging AI for improved perioperative communication of important health and event notifications and using AI to drive text messaging to communicate perioperatively. For population health, this may include understanding population health risk factors to help with anesthesia and surgical scheduling and planning as well as leveraging large datasets to safely triage patients to an ambulatory surgery center. These steps are currently completed by members of the healthcare team, but AI may be an efficient, effective, and safe alternative. The use of AI may help to lower costs by analyzing factors related to operating room logistics such as OR time scheduling. In the clinician well-being category, the considerations include the following: using AI algorithms to improve anesthesia staff scheduling on electronic platforms and optimizing staffing ratios based on predictive factors of patient perioperative risk and clinical load. This step may be especially helpful if there are staffing shortages and if it is effective may be able to help retain staff. For the final aim, health equity, AI may be used to study demographic, socioeconomic, and environmental risk factors that may be predictive of perioperative morbidity and mortality. We just completed the preoperative phase and there are so many opportunities for AI to help improve anesthesia patient safety.

Let’s move into the operative room now. First up, for patient experience, a couple options include using AI to assist in successful placement on first attempt of vascular access and nerve blocks using ultrasound guidance as well as using AI to assist in difficult airway management risk stratification. These are critical parts of anesthesia care. Next up, for population health AI may be used to help inform which patients need type and screen and or cross match for their surgery. AI may help to lower healthcare costs for anesthesia depth monitoring and optimization to decrease waste. Clinical well-being may be supported with the following considerations: use of AI to reduce cognitive load in clinical care environments with smart alarms and clinical decision support tools and decreasing unnecessary interactions with the electronic medical record through optimizing charting with natural language processing. Health equity may be improved in the intraoperative phase with the development of AI recommendation algorithms to reduce variation in care among different populations.

The surgery has been completed and it is time to leave the operating room and move into the postoperative phase. Let’s looks at what AI may be able to do. Under the patient experience aim, AI decision support may be used for postoperative risk stratification and disposition to optimize inpatient and critical care resources. Lower costs may be addressed by leveraging AI to assist in optimizing hospital bed management efficiency including time to discharge. AI may also be used to improve heath equity by using large datasets to study race and ethnicity disparities in care among a large health care system.

All of the AI applications that we just talked about are likely to improve patient safety in the future, but we are not there yet. There is still a lot of work to be done. While the progressing has been slower than anticipated, we may see integration of AI and perioperative patient safety in the near future. In 2019, the US Food and Drug Administration, the FDA, developed new regulatory pathways to decrease barriers and the related financial uncertainty for companies working to develop AI applications for healthcare. These changes helped to address the differences between AI and other medical devices. We are looking forward to seeing AI applications go live at the individual and health system wide level with new clarity on regulation and improved research and development.

Keep in mind that for healthcare AI applications to be successful in improving patient safety, there must be transparent levels of understanding about how the algorithms are designed while striving to minimize and eliminate bias associated with AI algorithms. The authors provide the example of an AI algorithm designed to help improve clinician performance that must be understood by the teams using the AI with a level of transparency in how the algorithms function. Check out the article, “Achieving Greater Health Equity: An Opportunity for Anesthesiology” by Diallo and colleagues published in Anesthesia and Analgesia in February 2022.

There is a call to action to reduce the risks of race/ethnicity, socioeconomic, and statistical bias during the development of AI algorithms in healthcare and the use of data to create AI tools. The future for anesthesia patient safety is bright with emerging technologies including artificial intelligence. The authors tell us:

“For AI to be effective, implementation of data-driven analytics with patient safety paradigms in anesthesiology will require organ­izations to innovate by supporting the development and building of multidisciplinary teams of clinicians, data scientists, engineers, and patient safety scientists. As anesthesia care delivery continues to evolve, the multidisciplinary nature of perioperative patient safety will need to respond with an innovative multidisciplinary approach, team, and solution—one that harnesses the scalability and strengths of AI through the lens of the Quintuple Aim.”

We are looking forward to seeing some of these AI applications in use in the preoperative anesthesia clinic, operating rooms, and postoperative anesthesia care units.

What are you doing in September? We hope that you are looking forward to the 2023 APSF Stoelting Conference September 6-7^th with a focus on “Emerging Medical Technologies – A Patient Safety Perspective on Wearables, Big Data, and Remote Care.” For more information, head over to APSF.org and click on the Conferences and Events heading. Second one down is the APSF Stoelting Conference 2023. I will include a link in the show notes as well. This will be a hybrid meeting with in-person and virtual options, and you don’t want to miss it!

If you have any questions or comments from today’s show, please email us at [email protected]. Please keep in mind that the information in this show is provided for informational purposes only and does not constitute medical or legal advice. We hope that you will visit APSF.org for detailed information and check out the show notes for links to all the topics we discussed today.

Until next time, stay vigilant so that no one shall be harmed by anesthesia care.

© 2023, The Anesthesia Patient Safety Foundation