Incorporating Real-Time Audiovisual and Haptic Feedback in a Novel Thoracostomy Tube Training Model

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2024-01-30

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Abstract

INTRODUCTION: Simulation-based training can enhance clinical performance, but chest tube insertion is challenging to simulate due to the precision needed for controlled pleural entry. This study evaluates the efficacy of a novel training model with real-time pressure monitoring and audiovisual feedback for force and time to pleural entry in a model. METHODS: The model consisted of a Kelly clamp with force sensors installed at the index finger (sensor 1) and both finger loops (sensors 2 and 3) and a manikin with a replaceable chest wall pad. Data obtained from experts indicated standard force value for pleural entry (Newtons, "N") and acceptable time to completion (3000-5000 milliseconds, "ms"). Thirteen participants ranging from PGY-1 to PGY-6 were introduced to the procedure and model. Force and time were measured from dermal entry to pleural space puncture. A significant drop in pressure suggested puncturing through the chest wall. RESULTS: Force was measured in the linear, plateau, and drop phases of the procedure. Linear phase (~3,000ms) was from start to point of maximum force (<30N). Plateau phase was from maximum force until drop phase. Drop phase was a drop in pressure by >5 Newtons within 150ms indicating procedure completion (pleural entry). All participants successfully completed the task. Pleural entry force ranged from 17N to 30N, and time to pleural entry ranged from 7,500-15,000ms. Of note, left-handed participants relied more on sensors 1 and 3 while right-handed participants relied more on sensors 1 and 2. Thus, only force measurements from sensor 1 were utilized to standardize our assessment. CONCLUSIONS: This novel chest tube trainer with continuous force monitoring can be applied to training for a variety of scenarios, including vascular access, trocar placement and other common procedures. Next steps involve evaluating its impact on trainee accuracy and efficiency.

General Notes

The 62nd Annual Medical Student Research Forum at UT Southwestern Medical Center (Tuesday, January 30, 2024, 3-6 p.m., D1.700 Lecture Hall)

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Najjar, A., Hegde, S., Hofman, E., Dubagunta, S., Awad, D., Khan, O., Eisaman, K., Hossain, I., Walker, J., Sherman, B., Kadakia, Y., & Park, C. (2024, January 30). Incorporating real-time audiovisual and haptic feedback in a novel thoracostomy tube training model [Poster session]. 62nd Annual Medical Student Research Forum, Dallas, Texas. https://hdl.handle.net/2152.5/10253

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