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Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study
BACKGROUND: Prehospitalization documentation is a challenging task and prone to loss of information, as paramedics operate under disruptive environments requiring their constant attention to the patients. OBJECTIVE: The aim of this study is to develop a mobile platform for hands-free prehospitalizat...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548972/ https://www.ncbi.nlm.nih.gov/pubmed/34636729 http://dx.doi.org/10.2196/32301 |
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author | Woo, MinJae Mishra, Prabodh Lin, Ju Kar, Snigdhaswin Deas, Nicholas Linduff, Caleb Niu, Sufeng Yang, Yuzhe McClendon, Jerome Smith, D Hudson Shelton, Stephen L Gainey, Christopher E Gerard, William C Smith, Melissa C Griffin, Sarah F Gimbel, Ronald W Wang, Kuang-Ching |
author_facet | Woo, MinJae Mishra, Prabodh Lin, Ju Kar, Snigdhaswin Deas, Nicholas Linduff, Caleb Niu, Sufeng Yang, Yuzhe McClendon, Jerome Smith, D Hudson Shelton, Stephen L Gainey, Christopher E Gerard, William C Smith, Melissa C Griffin, Sarah F Gimbel, Ronald W Wang, Kuang-Ching |
author_sort | Woo, MinJae |
collection | PubMed |
description | BACKGROUND: Prehospitalization documentation is a challenging task and prone to loss of information, as paramedics operate under disruptive environments requiring their constant attention to the patients. OBJECTIVE: The aim of this study is to develop a mobile platform for hands-free prehospitalization documentation to assist first responders in operational medical environments by aggregating all existing solutions for noise resiliency and domain adaptation. METHODS: The platform was built to extract meaningful medical information from the real-time audio streaming at the point of injury and transmit complete documentation to a field hospital prior to patient arrival. To this end, the state-of-the-art automatic speech recognition (ASR) solutions with the following modular improvements were thoroughly explored: noise-resilient ASR, multi-style training, customized lexicon, and speech enhancement. The development of the platform was strictly guided by qualitative research and simulation-based evaluation to address the relevant challenges through progressive improvements at every process step of the end-to-end solution. The primary performance metrics included medical word error rate (WER) in machine-transcribed text output and an F1 score calculated by comparing the autogenerated documentation to manual documentation by physicians. RESULTS: The total number of 15,139 individual words necessary for completing the documentation were identified from all conversations that occurred during the physician-supervised simulation drills. The baseline model presented a suboptimal performance with a WER of 69.85% and an F1 score of 0.611. The noise-resilient ASR, multi-style training, and customized lexicon improved the overall performance; the finalized platform achieved a medical WER of 33.3% and an F1 score of 0.81 when compared to manual documentation. The speech enhancement degraded performance with medical WER increased from 33.3% to 46.33% and the corresponding F1 score decreased from 0.81 to 0.78. All changes in performance were statistically significant (P<.001). CONCLUSIONS: This study presented a fully functional mobile platform for hands-free prehospitalization documentation in operational medical environments and lessons learned from its implementation. |
format | Online Article Text |
id | pubmed-8548972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-85489722021-11-10 Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study Woo, MinJae Mishra, Prabodh Lin, Ju Kar, Snigdhaswin Deas, Nicholas Linduff, Caleb Niu, Sufeng Yang, Yuzhe McClendon, Jerome Smith, D Hudson Shelton, Stephen L Gainey, Christopher E Gerard, William C Smith, Melissa C Griffin, Sarah F Gimbel, Ronald W Wang, Kuang-Ching JMIR Mhealth Uhealth Original Paper BACKGROUND: Prehospitalization documentation is a challenging task and prone to loss of information, as paramedics operate under disruptive environments requiring their constant attention to the patients. OBJECTIVE: The aim of this study is to develop a mobile platform for hands-free prehospitalization documentation to assist first responders in operational medical environments by aggregating all existing solutions for noise resiliency and domain adaptation. METHODS: The platform was built to extract meaningful medical information from the real-time audio streaming at the point of injury and transmit complete documentation to a field hospital prior to patient arrival. To this end, the state-of-the-art automatic speech recognition (ASR) solutions with the following modular improvements were thoroughly explored: noise-resilient ASR, multi-style training, customized lexicon, and speech enhancement. The development of the platform was strictly guided by qualitative research and simulation-based evaluation to address the relevant challenges through progressive improvements at every process step of the end-to-end solution. The primary performance metrics included medical word error rate (WER) in machine-transcribed text output and an F1 score calculated by comparing the autogenerated documentation to manual documentation by physicians. RESULTS: The total number of 15,139 individual words necessary for completing the documentation were identified from all conversations that occurred during the physician-supervised simulation drills. The baseline model presented a suboptimal performance with a WER of 69.85% and an F1 score of 0.611. The noise-resilient ASR, multi-style training, and customized lexicon improved the overall performance; the finalized platform achieved a medical WER of 33.3% and an F1 score of 0.81 when compared to manual documentation. The speech enhancement degraded performance with medical WER increased from 33.3% to 46.33% and the corresponding F1 score decreased from 0.81 to 0.78. All changes in performance were statistically significant (P<.001). CONCLUSIONS: This study presented a fully functional mobile platform for hands-free prehospitalization documentation in operational medical environments and lessons learned from its implementation. JMIR Publications 2021-10-12 /pmc/articles/PMC8548972/ /pubmed/34636729 http://dx.doi.org/10.2196/32301 Text en ©MinJae Woo, Prabodh Mishra, Ju Lin, Snigdhaswin Kar, Nicholas Deas, Caleb Linduff, Sufeng Niu, Yuzhe Yang, Jerome McClendon, D Hudson Smith, Stephen L Shelton, Christopher E Gainey, William C Gerard, Melissa C Smith, Sarah F Griffin, Ronald W Gimbel, Kuang-Ching Wang. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 12.10.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Woo, MinJae Mishra, Prabodh Lin, Ju Kar, Snigdhaswin Deas, Nicholas Linduff, Caleb Niu, Sufeng Yang, Yuzhe McClendon, Jerome Smith, D Hudson Shelton, Stephen L Gainey, Christopher E Gerard, William C Smith, Melissa C Griffin, Sarah F Gimbel, Ronald W Wang, Kuang-Ching Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study |
title | Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study |
title_full | Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study |
title_fullStr | Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study |
title_full_unstemmed | Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study |
title_short | Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study |
title_sort | complete and resilient documentation for operational medical environments leveraging mobile hands-free technology in a systems approach: experimental study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548972/ https://www.ncbi.nlm.nih.gov/pubmed/34636729 http://dx.doi.org/10.2196/32301 |
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