Application of Design Structure Matrix to Simulate Surgical Procedures and Predict Surgery Duration
Author(s) -
Zhaoxuan Li,
D. L. Tate,
Thomas E. McGill,
John Griswold,
MingChien Chyu
Publication year - 2021
Publication title -
minimally invasive surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.548
H-Index - 19
eISSN - 2090-1453
pISSN - 2090-1445
DOI - 10.1155/2021/6340754
Subject(s) - duration (music) , surgical procedures , matrix (chemical analysis) , computer science , medicine , surgery , chemistry , chromatography , physics , acoustics
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.
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