Avatar Models and Radar Plots: The Future of Intraoperative Anesthesia Monitoring

Various diagrams facilitate the understanding of many concepts within anesthesia, such as the anesthetic triangle model, which describes a drug’s effect on narcosis, analgesia, and neuromuscular relaxation, leading to the common knowledge that anesthesia is not complete until all three components have been reached.¹  As anesthesiologists, we strive to ensure that our patients maintain homeostasis throughout surgical procedures, often using multiple different monitoring strategies such as electrocardiograms, arterial lines, and pulse oximetry, among various other tools. However, the use of multiple monitors can lead to an abundance of information and a relative feeling of sensory overload, which has been a topic of attention in previous studies that highlight that an increased amount of information displayed on monitors can reduce the ability of users to detect unexpected changes, even when they are in plain sight.^2,3 

Many studies have identified problems with patient monitoring due to at-a-glance monitoring, inattentional blindness, and alarm fatigue, all of which can lead to avoidable errors in patient care.⁴  As a result, advances have been made with revolutionary monitors such as Visual Patient technology, which has the intended purpose of allowing the physician to quickly assess a problem with little cognitive effort in order to rapidly find a solution.⁴  A study done by Roche et al. confirmed that conventional monitoring plus the Visual Patient avatar is noninferior to conventional monitoring alone.⁵  Similarly, the University of Michigan (Ann Arbor, Michigan) developed a multifunction decision support display that extracts, analyzes, and presents more than 250 pieces of data via a one-monitor organ system view, along with color coding to indicate normal and abnormal situations.⁶ 

With this in mind, we would like to offer a similar simplified model known as a radar or star plot, which provides a thorough and simple way to understand visual graphics. We believe that this model can be extrapolated to the operating room by using data from the various invasive and noninvasive monitoring devices—similar to previously discussed models—to yield an anesthetic radar plot that the anesthesiologist can quickly interpret. A sample of the radar plot model can be seen in figure 1, which shows eight possible determinants for the model, all of which have underlying subdeterminants. For example, in the event that oxygen saturation and driving pressure are altered, the anesthesiologist’s attention will quickly be driven to the ventilator to evaluate the subdeterminants of factors such as positive end-expiratory pressure, plateau pressure, and peak airway pressure, along with additional color coding to understand the severity of compromise. This approach was created with the goal of encouraging the scientific community and our colleagues around the world to undertake further research in a global effort to simplify adequate patient monitorization, support current revolutionary monitoring technology, and advance efforts in perfecting perioperative patient care strategies.

The authors would like to acknowledge the Anesthesiology and Critical Care Interest Group - Universidad El Bosque and Group of Basic and Clinical Investigations (GIBACUS) - Universidad del Sinú.

The authors declare no competing interests.