Objective Signatures of Endoscopic Surgical Performance

Background: Recent reports indicate a need for alternative metrics for assessing operative performance.¹ Primary outcome measures generally include morbidity and mortality detrimentally affecting willingness to care for high-risk patients. These metrics represent the cumulative sum of variables influencing patient outcomes. To specifically address the variable of surgical performance, investigators are assessing objective metrics of surgical performance.

Pioneering work from our laboratory and others utilized statistical models capable of differentiating surgical skill.^2,3 However, video analysis remains the gold standard for assessing surgical skill and was found to correlate with surgical outcomes.⁴ In the present study, we sought to characterize a method for identifying characteristic signatures of surgical performance.

Methods: An endoscopic endonasal surgical task was performed in a cadaver model involving an approach to the pituitary. Instrument tip coordinates were tracked in three-dimensional space via a commercially-available surgical navigation system. Data points were exported and uploaded to MATLAB. Coordinates were used to calculate point-to-point velocity and acceleration in the time and frequency domains during different portions of the procedure.

Results: Preliminary data demonstrate variability in velocity and acceleration in the time domain dependent on the area where instrument motion occurred (Fig. 1). When data was evaluated in the frequency domain, we found narrow clustering with a propensity for higher velocities versus a wider range of accelerations.

Discussion: The current study presents preliminary work developing a method for identifying characteristic signatures of surgical performance. This critical research builds the foundation for investigating identifying patterns of operative technique. Future work will build on this platform to fully elucidate signatures of endoscopic endonasal surgery and correlate these signatures with outcome-associated measures of performance.

Fig. 1

References

References

1 McCabe JM, Joynt KE, Welt FG, Resnic FS. Impact of public reporting and outlier status identification on percutaneous coronary intervention case selection in Massachusetts. JACC Cardiovasc Interv 2013;6(6):625–630

2 Ahmidi N, Ishii M, Fichtinger G, Gallia GL, Hager GD. An objective and automated method for assessing surgical skill in endoscopic sinus surgery using eye-tracking and tool-motion data. Int Forum Allergy Rhinol 2012;2(6):507–515

3 Rosen J, Solazzo M, Hannaford B, Sinanan M. Objective laparoscopic skills assessments of surgical residents using Hidden Markov Models based on haptic information and tool/tissue interactions. Stud Health Technol Inform 2001;81:417–423

4 Birkmeyer JD, Finks JF, O’Reilly A, et al; Michigan Bariatric Surgery Collaborative. Surgical skill and complication rates after bariatric surgery. N Engl J Med 2013;369(15):1434–1442