Objective Assessment Metrics for Central Line Simulators: An Exploration of Causal Factors

Author:

Gonzalez-Vargas Jessica M.1,Brown Dailen C.1,Moore Jason Z.1,Han David C.2,Sinz Elizabeth H.2,Sonntag Cheyenne C.2,Miller Scarlett R.1

Affiliation:

1. Pennsylvania State University

2. Penn State Health Milton S. Hershey Medical Center

Abstract

The Dynamic Haptic Robotic Trainer (DHRT) was developed to minimize the up to 39% of adverse effects experienced by patients during Central Venous Catheterization (CVC) by standardizing CVC training, and provide automated assessments of performance. Specifically, this system was developed to replace manikin trainers that only simulate one patient anatomy and require a trained preceptor to evaluate the trainees’ performance. While the DHRT system provides automated feedback, the utility of this system with real-world scenarios and expertise has yet to be thoroughly investigated. Thus, the current study was developed to determine the validity of the current objective assessment metrics incorporated in the DHRT system through expert interviews. The main findings from this study are that experts do agree on perceptions of patient case difficulty, and that characterizations of patient case difficulty is based on anatomical characteristics, multiple needle insertions, and prior catheterization.

Publisher

SAGE Publications

Subject

General Medicine,General Chemistry

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Progressive Medical Simulation: An Analysis of the Integration of Progressive and Personalized Learning in Central Line Simulators;Proceedings of the Human Factors and Ergonomics Society Annual Meeting;2023-09

2. Difficult or high risk? Objective task assessment vs. faculty perceptions of surgical skills;Global Surgical Education - Journal of the Association for Surgical Education;2023-04-19

3. Evaluating the Impact of Assessment Metrics for Simulated Central Venous Catheterization Training;Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare;2022-11-16

4. Learning From Failure: A Case Study Of Human Driven Risk Assessment In Medical Simulator Design;Proceedings of the Human Factors and Ergonomics Society Annual Meeting;2022-09

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