BACKGROUND: Usable real-time displays of intravenous anesthetic concentrations and effects could significantly enhance intraoperative clinical decision-making. Pharmacokinetic models are available to estimate past, present, and future drug effect-site concentrations, and pharmacodynamic models are available to predict the drug's associated physiologic effects. METHODS: An interdisciplinary research team (bioengineering, architecture, anesthesiology, computer engineering, and cognitive psychology) developed a graphic display that presents the real-time effect-site concentrations, normalized to the drugs' EC(95), of intravenous drugs. Graphical metaphors were created to show the drugs' pharmacodynamics. To evaluate the effect of the display on the management of total intravenous anesthesia, 15 anesthesiologists participated in a computer-based simulation study. The participants cared for patients during two experimental conditions: with and without the drug display. RESULTS: With the drug display, clinicians administered more bolus doses of remifentanil during anesthesia maintenance. There was a significantly lower variation in the predicted effect-site concentrations for remifentanil and propofol, and effect-site concentrations were maintained closer to the drugs' EC(95). There was no significant difference in the simulated patient heart rate and blood pressure with respect to experimental condition. The perceived performance for the participants was increased with the drug display, whereas mental demand, effort, and frustration level were reduced. In a post-simulation questionnaire, participants rated the display to be a useful addition to anesthesia monitoring. CONCLUSIONS: The drug display altered simulated clinical practice. These results, which will inform the next iteration of designs and evaluations, suggest promise for this approach to drug data visualization.
BACKGROUND: Usable real-time displays of intravenous anesthetic concentrations and effects could significantly enhance intraoperative clinical decision-making. Pharmacokinetic models are available to estimate past, present, and future drug effect-site concentrations, and pharmacodynamic models are available to predict the drug's associated physiologic effects. METHODS: An interdisciplinary research team (bioengineering, architecture, anesthesiology, computer engineering, and cognitive psychology) developed a graphic display that presents the real-time effect-site concentrations, normalized to the drugs' EC(95), of intravenous drugs. Graphical metaphors were created to show the drugs' pharmacodynamics. To evaluate the effect of the display on the management of total intravenous anesthesia, 15 anesthesiologists participated in a computer-based simulation study. The participants cared for patients during two experimental conditions: with and without the drug display. RESULTS: With the drug display, clinicians administered more bolus doses of remifentanil during anesthesia maintenance. There was a significantly lower variation in the predicted effect-site concentrations for remifentanil and propofol, and effect-site concentrations were maintained closer to the drugs' EC(95). There was no significant difference in the simulated patient heart rate and blood pressure with respect to experimental condition. The perceived performance for the participants was increased with the drug display, whereas mental demand, effort, and frustration level were reduced. In a post-simulation questionnaire, participants rated the display to be a useful addition to anesthesia monitoring. CONCLUSIONS: The drug display altered simulated clinical practice. These results, which will inform the next iteration of designs and evaluations, suggest promise for this approach to drug data visualization.
Authors: S Blake Wachter; Jim Agutter; Noah Syroid; Frank Drews; Matthew B Weinger; Dwayne Westenskow Journal: J Am Med Inform Assoc Date: 2003-03-28 Impact factor: 4.497
Authors: Shilo Anders; Robert Albert; Anne Miller; Matthew B Weinger; Alexa K Doig; Michael Behrens; Jim Agutter Journal: Int J Med Inform Date: 2012-04-23 Impact factor: 4.046
Authors: Ken B Johnson; Noah D Syroid; Dhanesh K Gupta; Sandeep C Manyam; Nathan L Pace; Cris D LaPierre; Talmage D Egan; Julia L White; Diane Tyler; Dwayne R Westenskow Journal: Anesth Analg Date: 2009-10-09 Impact factor: 5.108