Automatic Clinical Procedure Detection for Emergency Services

Understanding a patient's state is critical to providing optimal care. However, information loss occurs during patient hand-offs (e.g., emergency services (EMS) transferring patient care to a receiving hospital), which hinders care quality. Augmenting the information flow from an EMS vehicle to...

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Bibliographic Details
Main Authors: Heard, Jamison, Paris, Richard A., Scully, Deirdre, McNaughton, Candace, Ehrenfeld, Jesse M., Coco, Joseph, Fabbri, Daniel, Bodenheimer, Bobby, Adams, Julie A.
Format: Conference Proceeding
Language:English
Subjects:
Biomedical imaging
Feature extraction
Head
Wearable sensors
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Summary:Understanding a patient's state is critical to providing optimal care. However, information loss occurs during patient hand-offs (e.g., emergency services (EMS) transferring patient care to a receiving hospital), which hinders care quality. Augmenting the information flow from an EMS vehicle to a receiving hospital may reduce information loss and improve patient outcomes. Such augmentation requires a noninvasive system that can automatically recognize clinical procedures being performed and send near real-time information to a receiving hospital. An automatic clinical procedure detection system that uses wearable sensors, video, and machine-learning to recognize clinical procedures within a controlled environment is presented. The system demonstrated how contextual information and a majority vote method can substantially improve procedure recognition accuracy. Future work concerning computer vision techniques and deep learning are discussed.
ISSN:1558-4615
2694-0604
DOI:10.1109/EMBC.2019.8856281