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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 Publisher Pubmed



Kalhori SRN1, 2 ; Deserno TM1 ; Haghi M3 ; Ganapathy N1, 4
Authors
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Authors Affiliations
  1. 1. Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig, Hannover Medical School, Braunschweig, Germany
  2. 2. Health Information Management and Medical Informatics Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Ubiquitous Computing Laboratory, Department of Computer Science, Konstanz University of Applied Sciences, Konstanz, Germany
  4. 4. Biomedical Informatics Laboratory, Department of Biomedical Engineering, Indian Institute of Technology, Hyderabad, India

Source: PLoS ONE Published:2023


Abstract

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. Copyright: © 2023 Rostam Niakan Kalhori et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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