Application of Design Structure Matrix to Simulate Surgical Procedures and Predict Surgery Duration

Zhaoxuan Li; Derrick Tate; Thomas McGill; John Griswold; Ming-Chien Chyu

doi:10.1155/2021/6340754

Application of Design Structure Matrix to Simulate Surgical Procedures and Predict Surgery Duration

Minim Invasive Surg. 2021 Dec 6:2021:6340754. doi: 10.1155/2021/6340754. eCollection 2021.

Authors

Zhaoxuan Li¹, Derrick Tate^{1

2}, Thomas McGill³, John Griswold³, Ming-Chien Chyu^{1

2}

Affiliations

¹ Healthcare Engineering Graduate Program, Lubbock, TX, USA.
² Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, USA.
³ Department of Surgery, School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA.

Abstract

Background: The complexities of surgery require an efficient and explicit method to evaluate and standardize surgical procedures. A reliable surgical evaluation tool will be able to serve various purposes such as development of surgery training programs and improvement of surgical skills.

Objectives: (a) To develop a modeling framework based on integration of dexterity analysis and design structure matrix (DSM), to be generally applicable to predict total duration of a surgical procedure, and (b) to validate the model by comparing its results with laparoscopic cholecystectomy surgery protocol.

Method: A modeling framework is developed through DSM, a tool used in engineering design, systems engineering and management, to hierarchically decompose and describe relationships among individual surgical activities. Individual decomposed activities are assumed to have uncertain parameters so that a rework probability is introduced. The simulation produces a distribution of the duration of the modeled procedure. A statistical approach is then taken to evaluate surgery duration through integrated numerical parameters. The modeling framework is applied for the first time to analyze a surgery; laparoscopic cholecystectomy, a common surgical procedure, is selected for the analysis.

Results: The present simulation model is validated by comparing its results of predicted surgery duration with the standard laparoscopic cholecystectomy protocols from the Atlas of Minimally Invasive Surgery with 2.5% error and that from the Atlas of Pediatric Laparoscopy and Thoracoscopy with 4% error.

Conclusion: The present model, developed based on dexterity analysis and DSM, demonstrates a validated capability of predicting laparoscopic cholecystectomy surgery duration. Future studies will explore its potential applications to other surgery procedures and in improving surgeons' performance and training novices.