Surgical errors are commonplace and can have devastating consequences. More than 200 million surgeries occur annually worldwide and, in industrialized countries, preventable complications occur in up to 22% of cases for some procedures. Consequent permanent disability or mortality rates range between 0.4% and 0.8%. Errors can have numerous origins, including cognitive errors of judgment, missing a surgical step, performing them in the wrong order, or simply committing an error in technical execution. These can lead to poor surgical outcomes, poor patient satisfaction, reoperation, and litigation. Most surgeons are well aware of the high-risk steps in a given procedure, yet for most there is no widespread and reliable technology to prevent errors. We propose groundbreaking research in surgical error prevention by developing simulation technology, based on mathematical reconstructions of human tissue that can be utilized for our overall mission, to create a system to identify, model, and prevent surgical errors. To accomplish this, we will use motion analysis and high-fidelity 3-D models to simulate and measure surgical errors. We will analyze errors in a complex, high-risk step of one particular surgery, the midurethral sling (MUS) procedure. This surgery is an ideal choice for modeling individual surgeon error. Approximately 170,000 MUS surgeries are performed annually in the United States, a number that will likely increase given the aging US population. In performing the MUS, the surgeon is tasked with blindly guiding a sharp steel trocar past the bladder, bowel, and major blood vessels, so the surgeon must exhibit excellent bimanual dexterity and the ability to envision a blind 3-D space. If the trocar is not guided properly, complications can turn an elective minor surgery into a costly, protracted hospital course that may involve blood transfusions, a bowel resection, a colostomy, even sepsis and death. Novices are understandably anxious about performing this on a patient. We hypothesize that surgical error from trocar passage in the MUS surgery can be predicted, and thus avoided, by discrete changes in the kinematics of the surgeon?s shoulder, arm, and hand and by the spatio-temporal characteristics of trocar passage. We will create a 3-D pelvic simulator and use motion analysis with sensors to identify and prevent surgical errors during this complex, high-risk step. We will test the hypothesis with the following Aims:
Aim 1 : Create a high-fidelity pelvic simulator capable of identifying surgical errors involved in one surgery, the midurethral sling.
Aim 2 : Identify the kinematics of surgeon gross motor movements and of the surgical instrument during simulated trocar passage.
Aim 3 : Develop virtual surgical feedback software that when added to a printed pelvic simulation model will further reduce novice errors in the Midurethral Sling surgery. Our high-impact research and multi- disciplinary team is revolutionary in its approach to surgical error prevention. Our methods can be applied subsequently to a multitude of high-risk steps in numerous surgeries, and thus has the potential to prevent surgical injury for many patients.

Public Health Relevance

Surgical errors have the potential to cause devastating injury. The current proposal aims to model and quantitatively describe surgical errors through the kinematic analysis of one preventable surgical error, trocar passage from the midurethral sling surgery, so that young surgeons can be trained not to commit them. We aim to create a systematic way of identifying and modeling surgical errors that can be applied to high-risk steps in other surgeries and will lead to effective error prevention.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Exploratory/Developmental Grants (R21)
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Bioengineering, Technology and Surgical Sciences Study Section (BTSS)
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Peng, Grace
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University of Missouri Kansas City
Obstetrics & Gynecology
Schools of Medicine
Kansas City
United States
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