MScore Analyzes Robotic Surgery Simulator Performance

MScore Analyzes Robotic Surgery Simulator Performance

New Proficiency Based Scoring System

MScore is utilizing data collected from more than 100 experienced

surgeons with over 75 robotic cases completed. Assessment is

based on expert averages and standard deviations similar to the

Fundamentals of Laparoscopic Surgery (FLS) protocol to facilitate

credentialing and privileging.

New Curriculum Tools and Customization

Educators can now build their own robotic surgery training protocols

from more than 40 exercises and assign different curricula to each

user. Curricula, including exercises, completion order, and scoring

baselines, can be imported and exported to facilitate collaboration

and sharing between institutions.

Comprehensive Metrics for Surgical

Skills Assessment

Time to Completion Master Workspace Range

Economy of Motion Blood Loss

Instrument Collisions Broken Vessels

Number of Drops Excessive Instrument Force

Missed Targets Misapplied Energy

Instruments Out of View Overall Score

Objective Skills Assessment for Robotic Surgery

Proficiency based scoring system

Import and export customized curricula

Admin tools for course creation and management

Track learning history for each exercise and metric

Customize scoring baselines and proficiency levels

Export data for statistical analysis in Excel

Mimic Technologies, a company that builds the dV-Trainer, a da Vinci surgical robot simulator, recently released a software product to help assess how novice surgeons are using the simulator. The company has been collecting data from experienced surgeons performing various tasks on the simulator, and the MScore application is able to compare a novice user of the dv-Trainer against this data set to provide an overall performance score.

The hope is that with better in-silico training coupled with performance feedback, fewer animals will be sacrificed for this task, and patients will have better skilled surgeons working on them.

From MScore’s brochure:

MScore is utilizing data collected from more than 100 experienced surgeons with over 75 robotic cases completed. Assessment is based on expert averages and standard deviations similar to the Fundamentals of Laparoscopic Surgery (FLS) protocol to facilitate credentialing and privileging.

Educators can now build their own robotic surgery training protocols from more than 40 exercises and assign different curricula to each user. Curricula, including exercises, completion order, and scoring baselines, can be imported and exported to facilitate collaboration and sharing between institutions.

Seattle, WA—A new assessment system has been developed by a team of researchers to more reliably predict

whether surgeons are ready to operate on patients using the da Vinci robot. The new technology, called MScore,

provides more precise analysis of actual surgical performance, which has been shown to be difficult to accomplish

using common training approaches.

Prior to the introduction of da Vinci simulation training, the only option for most robotic surgeons was to learn on

patients, animals and simple plastic models. Such training methods rely on a subjective assessment from proctors

rather than precise measurement of movement and actions.

Mimic Technologies, the simulation company that built the da Vinci simulation platform, is developing MScore,

utilizing performance data collected from more than 100 experienced surgeons and academics who have

completed at least 75 separate cases. This performance data is being collected from seven leading academic

medical centers worldwide, including University of Southern California, U.C. Irvine, and Columbia University.

MScore compares a novice surgeon performance to that of experienced surgeons in order to give an objective

assessment of a surgeon’s skills. Such an evaluation can help hospitals decide whether a new da Vinci surgeon is

proficient enough to conduct surgery on patients. The MScore system encourages continued training long after

proficiency has been established, and performance is monitored over time to inspire a surgeon to continually

advance their level of skill.

“This new technology is important for a surgeon’s own assessment of his or her performance on a machine as

complex and necessary as the da Vinci,” says Inderbir S. Gill, M.D., M.Ch., chairman & professor, Catherine and

Joseph Aresty Department of Urology, Keck School of Medicine of USC. “Surgeons are encouraged to continue to

measure their ability with the best methods possible in order to ensure the safety of the patient and the quality

of their work.”

The MScore system allows every movement and action the surgeon makes to be tracked and evaluated within a

virtual reality training environment. A surgeon’s proficiency and score is established by utilizing a wide variety of

performance metrics, such as task time, efficiency of instrument motion, blood loss and the force applied to tissue.

Performance baselines are derived from the data collected from experienced surgeons.

“We believe, based on a decade of experience working with surgeons and hospitals, that assessment of surgeon

performance must be objective and consistently applied regardless of training institution,” says Jeff Berkley,

Founder and CEO of Mimic Technologies. “The medical community and patients will have an increased level of

comfort with robotic technology once there is such measurement of performance.”

MScore assessment is based on an evaluation protocol called the Fundamentals of Laparoscopic Surgery (FLS),

which is used to train and credential surgeons through the American College of Surgeons. The FLS scoring system

has been limited to general and vascular services and requires testing with physical models and proctor overview.

Mimic’s virtual reality system automates the process for surgical robotics training and provides instant assessment

and feedback. Current research is focused on utilizing MScore for surgeon credentialing across a wide breadth of

surgical subspecialties. Beyond establishing new surgeon proficiency, Mimic’s MScore is being applied to

alternative training protocols, such as warming up before surgery and retaining surgical skills during periods of

inactivity.

“Surgeons want to know their level of performance, as well as where they can improve,” says Rick Satava, M.D.,

Professor of Surgery, University of Washington “Providing proficiency-based benchmarks developed from the

performance of experts allows surgeons to gauge their own performance level and how to improve and become

more effective for their patients.”

Source : http://www.mimicsimulation.com/news/MScore%20Press%20Release%20Feb.pdf

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