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A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms
BACKGROUND: This is a systematic review protocol to identify automated features, applied technologies, and algorithms in the electronic early warning/track and triage system (EW/TTS) developed to predict clinical deterioration (CD). METHODOLOGY: This study will be conducted using PubMed, Scopus, and...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10016632/ https://www.ncbi.nlm.nih.gov/pubmed/36920960 http://dx.doi.org/10.1371/journal.pone.0283010 |
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author | Rostam Niakan Kalhori, Sharareh Deserno, Thomas M. Haghi, Mostafa Ganapathy, Nagarajan |
author_facet | Rostam Niakan Kalhori, Sharareh Deserno, Thomas M. Haghi, Mostafa Ganapathy, Nagarajan |
author_sort | Rostam Niakan Kalhori, Sharareh |
collection | PubMed |
description | BACKGROUND: This is a systematic review protocol to identify automated features, applied technologies, and algorithms in the electronic early warning/track and triage system (EW/TTS) developed to predict clinical deterioration (CD). METHODOLOGY: This study will be conducted using PubMed, Scopus, and Web of Science databases to evaluate the features of EW/TTS in terms of their automated features, technologies, and algorithms. To this end, we will include any English articles reporting an EW/TTS without time limitation. Retrieved records will be independently screened by two authors and relevant data will be extracted from studies and abstracted for further analysis. The included articles will be evaluated independently using the JBI critical appraisal checklist by two researchers. DISCUSSION: This study is an effort to address the available automated features in the electronic version of the EW/TTS to shed light on the applied technologies, automated level of systems, and utilized algorithms in order to smooth the road toward the fully automated EW/TTS as one of the potential solutions of prevention CD and its adverse consequences. TRIAL REGISTRATION: Systematic review registration: PROSPERO CRD42022334988. |
format | Online Article Text |
id | pubmed-10016632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100166322023-03-16 A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms Rostam Niakan Kalhori, Sharareh Deserno, Thomas M. Haghi, Mostafa Ganapathy, Nagarajan PLoS One Study Protocol BACKGROUND: This is a systematic review protocol to identify automated features, applied technologies, and algorithms in the electronic early warning/track and triage system (EW/TTS) developed to predict clinical deterioration (CD). METHODOLOGY: This study will be conducted using PubMed, Scopus, and Web of Science databases to evaluate the features of EW/TTS in terms of their automated features, technologies, and algorithms. To this end, we will include any English articles reporting an EW/TTS without time limitation. Retrieved records will be independently screened by two authors and relevant data will be extracted from studies and abstracted for further analysis. The included articles will be evaluated independently using the JBI critical appraisal checklist by two researchers. DISCUSSION: This study is an effort to address the available automated features in the electronic version of the EW/TTS to shed light on the applied technologies, automated level of systems, and utilized algorithms in order to smooth the road toward the fully automated EW/TTS as one of the potential solutions of prevention CD and its adverse consequences. TRIAL REGISTRATION: Systematic review registration: PROSPERO CRD42022334988. Public Library of Science 2023-03-15 /pmc/articles/PMC10016632/ /pubmed/36920960 http://dx.doi.org/10.1371/journal.pone.0283010 Text en © 2023 Rostam Niakan Kalhori et al 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 author and source are credited. |
spellingShingle | Study Protocol Rostam Niakan Kalhori, Sharareh Deserno, Thomas M. Haghi, Mostafa Ganapathy, Nagarajan A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms |
title | A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms |
title_full | A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms |
title_fullStr | A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms |
title_full_unstemmed | A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms |
title_short | A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms |
title_sort | protocol for a systematic review of electronic early warning/track-and-trigger systems (ew/tts) to predict clinical deterioration: focus on automated features, technologies, and algorithms |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10016632/ https://www.ncbi.nlm.nih.gov/pubmed/36920960 http://dx.doi.org/10.1371/journal.pone.0283010 |
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