Authors: Young May Cha, MD
IARS Daily Dose, May 3, 2026.
This session from the 2026 Annual Meeting presented by the International Anesthesia Research Society explored the evolving role of preoperative risk assessment tools in perioperative medicine and how these tools may improve surgical outcomes, enhance shared decision-making, and personalize perioperative care.
Dr. Joshua Bloomstone moderated the session, “Does Preoperative Risk Prediction Improve Perioperative Outcome? An Update,” which reviewed both the strengths and limitations of current perioperative risk prediction models.
Dr. Rafael Noriega presented an overview of available perioperative risk calculators. Individualized tools such as the American College of Surgeons National Surgical Quality Improvement Program calculator provide procedure-specific and data-driven risk prediction. Broader tools such as frailty assessments identify vulnerabilities not always captured by traditional calculators. Other commonly used systems reviewed included POSSUM, Portsmouth-POSSUM, ASA Physical Status classification, and the Revised Cardiac Risk Index (RCRI). Each tool has distinct strengths and weaknesses. For example, POSSUM systems require intraoperative data and are therefore less useful for preoperative planning, while the RCRI focuses only on cardiac complications and may underestimate risk in today’s increasingly older and medically complex population.
The session also reviewed the growing role of biomarkers in perioperative risk assessment. Biomarkers such as BNP, troponin, cystatin C, and procalcitonin may improve perioperative risk stratification, although widespread implementation remains limited due to institutional availability. The speakers emphasized that risk assessment tools should not merely predict complications but should directly influence perioperative management decisions in order to improve outcomes.
Dr. Benjamin Houseman discussed perioperative risk communication from the perspective of shared decision-making. Patients increasingly want individualized risk information and many are willing to pursue prehabilitation strategies to reduce perioperative risk. However, multiple barriers limit effective communication, including time constraints, cognitive overload during informed consent discussions, limited patient comprehension, and the traditionally brief anesthesia consultation process.
An important concern raised was the low frequency of detailed risk documentation by anesthesiologists. Fewer than 1 in 20 anesthesiologists document individualized organ-specific morbidity or mortality risks despite increasing regulatory emphasis on personalized risk communication. Dr. Houseman emphasized that true shared decision-making should extend beyond a single preoperative encounter and continue throughout the perioperative and postoperative period.
Emerging technologies were also highlighted. Virtual reality-assisted consent processes were well received by patients and reduced specialist consultation time. Artificial intelligence models including OpenAI’s ChatGPT and Google’s Gemini performed well in explaining general anesthesia-related complications. The speakers suggested embedding individualized risk calculators directly into electronic health records and tracking their use as quality metrics to improve adoption and consistency.
Dr. Kamal Maheshwari concluded the session by discussing the future of perioperative predictive analytics. He described how large language models and advanced AI systems may eventually synthesize data from electronic health records, wearable devices, laboratory studies, and genetic testing into individualized perioperative care pathways. Future predictive systems may help tailor prehabilitation programs, postoperative monitoring strategies, and long-term recovery planning while incorporating patient-centered goals and quality-of-life outcomes.
The session emphasized that perioperative risk assessment should evolve beyond simply labeling patients as “high-risk.” Instead, the goal should be to use predictive information proactively to improve outcomes, personalize perioperative care, and support truly informed patient decisions.
Key Points
• Modern perioperative risk assessment tools vary widely in scope, accuracy, and clinical applicability.
• Procedure-specific tools such as ACS-NSQIP provide more individualized risk prediction than generalized scoring systems.
• Frailty assessments and biomarkers may improve identification of patients at elevated perioperative risk.
• Shared decision-making requires individualized risk communication that continues throughout the perioperative process.
• Documentation of organ-specific perioperative risks by anesthesiologists remains uncommon.
• Virtual reality and artificial intelligence technologies may improve patient understanding and efficiency during informed consent.
• Future AI-driven predictive systems may integrate wearable data, genetic information, and electronic health record data to personalize perioperative care.
Thank you to the International Anesthesia Research Society Daily Dose for allowing us to summarize and share this article.