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32 Executive Briefing scheduled medication list and reduce the likelihood of an opioid- related adverse event. As with pain management, Dr. Pease believes anesthesia will benefit from precision medicine, specifically in the development of novel pharmacological agents. The opioid epidemic has prompted new research aimed at developing opioid-free anesthesia and pain management medications that could be available to physicians in the next few years, she said. These agents combine the sedative- hypnotic drug properties of currently available medications with a rapid titratable intravenous delivery system. The resulting therapies would allow for effective drug delivery with limited side effects. Precision medicine and individualized care can both support the surgical shop model and improve care for the whole patient. Specifically, when care coordinators meet with patients to gather patient information and relay this information to the care team, this information can be used to develop individualized care plans that include therapies best suited to that patient. AI and virtual care AI-supported solutions play a pivotal role in supporting successful surgical solution shop models. By incorporating automation and data analytics into individualized care, elements like advanced early warning systems — wireless surveillance technology that uses algorithms to recognize potential symptoms and diseases — will allow clinicians to better utilize technology to recognize patient deterioration and activate interventions. Dr. Pease said AI will also support nurse avatars that will reach patients in their homes via telemedicine. Patients will be able to interact with these avatars, and the avatars will lead patients through exercises and repetitive tasks to ensure optimal preoperative and postoperative care. "With analytical and reasoning capabilities and a wide range of clinical knowledge, this automated routine work will support clinical decision-making and free clinicians to focus more on direct patient communication and complex care decisions," Dr. Pease said. Research published January 2018 in Baylor University Medical Center Proceedings examined the role of AI in anesthesia. Researchers found that while many attempts to incorporate automation into anesthesia have failed, "recent innovations in AI, especially machine learning, may usher in a new era of automation across many industries, including anesthesia." 6 In addition to the nurse avatars, AI can also facilitate clinical guidance that better tracks real time data to optimize anesthesia care. Such automation requires rule-based, closed-loop feedback systems to manage or maintain general anesthesia within patient specific goals of care such as goal directed fluid therapy or low pressure ventilation. Efforts to develop these types of systems are in their infancy, but experts still believe systems like these are the next generation of technology improving patient safety and quality. 6 Researchers argue that while AI will influence how anesthesia is practiced, the complexity of the specialty will limit it from ever achieving full-automation. These researchers feel the best utilization of AI in anesthesia will be to support elements of perioperative home care and clinical decision support. 6 Dr. Pease echoed this sentiment, since AI can interpret hard data elements but can never replace the tactile feel of a patient's response to therapy and clinical judgement calls that occur minute to minute within the operating room. AI may be able to interpret patient's vital signs but will not appreciate the nuances of the surgical care playing out in the surgical field that impact those vital signs. "In the specific case of anesthesiology, these innovations may allow anesthesiology the freedom to reinvent itself from an intraoperative specialty to one of true perioperative medicine," she said. AI-supported tools like nurse avatars allow clinicians to reach patients outside of the hospital. Advances in AI-based diagnostic technologies can also flag patients and alert clinicians to conditions before appointments. Such advancements support the solution shop model by extending and sharpening a clinician's expertise and ability to generate better outcomes. The solution shop model and the evolution of anesthesiology The emergence of the solution shop model is an example of healthcare's continued evolution. A concept created in the business space is being co-opted into healthcare to continue improvements in patient-centered care. This isn't the first time healthcare providers have looked to outside industries to improve processes, according to Dr. Pease. Surgical checklists, safety protocols and Lean Six Sigma were all adopted from other industries and have made deep impressions in healthcare. The future of anesthesia care will be largely influenced by personalized medicine and AI-supported technologies. By incorporating these advancements into a solution shop model, practices will be able to standardize processes, improve patient flow, improve clinical outcomes and decrease waste and error. "By being more solution-oriented, we can better coordinate care and manage complex patients across the continuum of care in a more cohesive manner," Dr. Pease said. "These types of multidisciplinary interventions decrease perioperative complications and enable patients to be discharged quicker and with fewer readmissions, which are solutions we need in healthcare." n References 1 Wanamaker, B. (2016, August 22). Why Cleveland Clinic always wins: The solution shop business model. Retrieved from https://www.christenseninstitute.org/blog/ why-cleveland-clinic-always-wins-the-solution-shop-business-model/ 2 Ferner, R. E., & Aronson, J. K. (2010). Pharmacogenetics and adverse drug reactions. Adverse Drug Reaction Bulletin, &NA;(264), 1015-1018. doi:10.1097/ fad.0b013e328340bc88 3 White House. (2015, January 30). FACT SHEET: President Obama's Precision Medicine Initiative. Retrieved from https://obamawhitehouse.archives.gov/the-press- office/2015/01/30/fact-sheet-president-obama-s-precision-medicine-initiative 4 Iravani, M., Lee, L. K., & Cannesson, M. (2017). Standardized Care Versus Precision Medicine in the Perioperative Setting. Survey of Anesthesiology, 61(5-6), 143. doi:10.1097/01.sa.0000527518.23397.ca 5 Center for Drug Evaluation and Research. (n.d.). Drug Interactions & Labeling - Preventable Adverse Drug Reactions: A Focus on Drug Interactions. Retrieved from https://www.fda.gov/Drugs/DevelopmentApprovalProcess/DevelopmentResources/ DrugInteractionsLabeling/ucm110632.htm 6 Alexander, J., MD, & Joshi, G. P., MD. (2017). Anesthesiology, automation, and artificial intelligence. Baylor University Medical Center Proceedings, 117-119. doi:10. 1080/08998280.2017.1391036 At TeamHealth, our purpose is to perfect our physicians' ability to practice medicine, every day, in everything we do. TeamHealth offers outsourced emergency medicine, hospital medicine, anesthesia, orthopedic hospitalist, acute care surgery, obstetrics and gynecology hospitalist, urgent care, post-acute care and medical call center solutions to approximately 3,200 civilian and military hospitals, clinics, physician groups and post-acute care facilities nationwide.