Integrating autonomously navigating assistance systems into the clinic: guiding principles and the ANTS-OR approach
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Published:2020-04-02
Issue:6
Volume:15
Page:1063-1067
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ISSN:1861-6410
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Container-title:International Journal of Computer Assisted Radiology and Surgery
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language:en
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Short-container-title:Int J CARS
Author:
Bernhard Lukas,Ostler Daniel,Feußner Hubertus,Wilhelm Dirk
Abstract
Abstract
Purpose
Autonomously self-navigating clinical assistance systems (ASCAS) seem highly promising for improving clinical workflows. There is great potential for easing staff workload and improving overall efficiency by reducing monotonous and physically demanding tasks. However, a seamless integration of such systems into complex human-supervised clinical workflows is challenging. As of yet, guiding principles and specific approaches for solving this problem are lacking.
Methods
We propose to treat ASCAS orchestration as a scheduling problem. However, underlying objectives and constraints for this scheduling problem differ considerably from those found in other domains (e.g., manufacturing, logistics). We analyze the clinical environment to deduce unique needs and conclude that existing scheduling approaches are not sufficient to overcome these challenges.
Results
We present four guiding principles, namely human precedence, command structure, emergency context and immediacy, that govern the integration of self-navigating assistance systems into clinical workflows. Based on these results, we propose our approach, namely Auto-Navigation Task Scheduling for Operating Rooms (ANTS-OR), for solving the ASCAS orchestration problem in a surgical application scenario, employing a score-based scheduling strategy.
Conclusion
The proposed approach is a first step toward addressing the ASCAS orchestration problem for the OR wing. We are currently advancing and validating our concept using a simulation environment and aim at realizing a dynamic end-to-end ASCAS orchestration platform in the future.
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Radiology Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering
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