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Clinical informatics solutions in COVID-19 pandemic: Scoping literature review
BACKGROUND: The global outbreak of COVID-19 (coronavirus disease 2019) disease has highlighted the importance of disease monitoring, diagnosing, treating, and screening. Technology-based instruments could efficiently assist healthcare systems during pandemics by allowing rapid and widespread transfe...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949656/ https://www.ncbi.nlm.nih.gov/pubmed/35350124 http://dx.doi.org/10.1016/j.imu.2022.100929 |
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author | Ganjali, Raheleh Eslami, Saeid Samimi, Tahereh Sargolzaei, Mahdi Firouraghi, Neda MohammadEbrahimi, Shahab khoshrounejad, Farnaz Kheirdoust, Azam |
author_facet | Ganjali, Raheleh Eslami, Saeid Samimi, Tahereh Sargolzaei, Mahdi Firouraghi, Neda MohammadEbrahimi, Shahab khoshrounejad, Farnaz Kheirdoust, Azam |
author_sort | Ganjali, Raheleh |
collection | PubMed |
description | BACKGROUND: The global outbreak of COVID-19 (coronavirus disease 2019) disease has highlighted the importance of disease monitoring, diagnosing, treating, and screening. Technology-based instruments could efficiently assist healthcare systems during pandemics by allowing rapid and widespread transfer of information, real-time tracking of data transfer, and virtualization of meetings and patient visits. Therefore, this study was conducted to investigate the applications of clinical informatics (CI) during the COVID-19 outbreak. METHODS: A comprehensive search was performed on Medline and Scopus databases in September 2020. Eligible studies were selected based on the inclusion and exclusion criteria. The extracted data from the studies reviewed were about study sample, study type, objectives, clinical informatics domain, applied method, sample size, outcomes, findings, and conclusion. The risk of bias was evaluated in the studies using appropriate instruments based on the type of each study. The selected studies were then subjected to thematic synthesis. RESULTS: In this review study, 72 out of 2716 retrieved articles met the inclusion criteria for full-text analysis. Most of the articles reviewed were done in China and the United States of America. The majority of the studies were conducted in the following CI domains: prediction models (60%), telehealth (36%), and mobile health (4%). Most of the studies in telehealth domain used synchronous methods, such as online and phone- or video-call consultations. Mobile applications were developed as self-triage, self-scheduling, and information delivery tools during the COVID-19 pandemic. The most common types of prediction models among the reviewed studies were neural network (49%), classification (42%), and linear models (4.5%). CONCLUSION: The present study showed clinical informatics applications during COVID-19 and identified current gaps in this field. Health information technology and clinical informatics seem to be useful in assisting clinicians and managers to combat COVID-19. The most common domains in clinical informatics for research on the COVID-19 crisis were prediction models and telehealth. It is suggested that future researchers conduct scoping reviews to describe and analyze other levels of medical informatics, including bioinformatics, imaging informatics, and public health informatics. |
format | Online Article Text |
id | pubmed-8949656 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Authors. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89496562022-03-25 Clinical informatics solutions in COVID-19 pandemic: Scoping literature review Ganjali, Raheleh Eslami, Saeid Samimi, Tahereh Sargolzaei, Mahdi Firouraghi, Neda MohammadEbrahimi, Shahab khoshrounejad, Farnaz Kheirdoust, Azam Inform Med Unlocked Article BACKGROUND: The global outbreak of COVID-19 (coronavirus disease 2019) disease has highlighted the importance of disease monitoring, diagnosing, treating, and screening. Technology-based instruments could efficiently assist healthcare systems during pandemics by allowing rapid and widespread transfer of information, real-time tracking of data transfer, and virtualization of meetings and patient visits. Therefore, this study was conducted to investigate the applications of clinical informatics (CI) during the COVID-19 outbreak. METHODS: A comprehensive search was performed on Medline and Scopus databases in September 2020. Eligible studies were selected based on the inclusion and exclusion criteria. The extracted data from the studies reviewed were about study sample, study type, objectives, clinical informatics domain, applied method, sample size, outcomes, findings, and conclusion. The risk of bias was evaluated in the studies using appropriate instruments based on the type of each study. The selected studies were then subjected to thematic synthesis. RESULTS: In this review study, 72 out of 2716 retrieved articles met the inclusion criteria for full-text analysis. Most of the articles reviewed were done in China and the United States of America. The majority of the studies were conducted in the following CI domains: prediction models (60%), telehealth (36%), and mobile health (4%). Most of the studies in telehealth domain used synchronous methods, such as online and phone- or video-call consultations. Mobile applications were developed as self-triage, self-scheduling, and information delivery tools during the COVID-19 pandemic. The most common types of prediction models among the reviewed studies were neural network (49%), classification (42%), and linear models (4.5%). CONCLUSION: The present study showed clinical informatics applications during COVID-19 and identified current gaps in this field. Health information technology and clinical informatics seem to be useful in assisting clinicians and managers to combat COVID-19. The most common domains in clinical informatics for research on the COVID-19 crisis were prediction models and telehealth. It is suggested that future researchers conduct scoping reviews to describe and analyze other levels of medical informatics, including bioinformatics, imaging informatics, and public health informatics. The Authors. Published by Elsevier Ltd. 2022 2022-03-25 /pmc/articles/PMC8949656/ /pubmed/35350124 http://dx.doi.org/10.1016/j.imu.2022.100929 Text en © 2022 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Ganjali, Raheleh Eslami, Saeid Samimi, Tahereh Sargolzaei, Mahdi Firouraghi, Neda MohammadEbrahimi, Shahab khoshrounejad, Farnaz Kheirdoust, Azam Clinical informatics solutions in COVID-19 pandemic: Scoping literature review |
title | Clinical informatics solutions in COVID-19 pandemic: Scoping literature review |
title_full | Clinical informatics solutions in COVID-19 pandemic: Scoping literature review |
title_fullStr | Clinical informatics solutions in COVID-19 pandemic: Scoping literature review |
title_full_unstemmed | Clinical informatics solutions in COVID-19 pandemic: Scoping literature review |
title_short | Clinical informatics solutions in COVID-19 pandemic: Scoping literature review |
title_sort | clinical informatics solutions in covid-19 pandemic: scoping literature review |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949656/ https://www.ncbi.nlm.nih.gov/pubmed/35350124 http://dx.doi.org/10.1016/j.imu.2022.100929 |
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