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Effectiveness and safety of pulse oximetry in remote patient monitoring of patients with COVID-19: a systematic review
LANCET DIGITAL HEALTH ; 4(4), 2022.
Article in English | Web of Science | ID: covidwho-1935109
ABSTRACT
The COVID-19 pandemic has led health systems to increase the use of tools for monitoring and triaging patients remotely. In this systematic review, we aim to assess the effectiveness and safety of pulse oximetry in remote patient monitoring (RPM) of patients at home with COVID-19. We searched five databases (MEDLINE, Embase, Global Health, medRxiv, and bioRxiv) from database inception to April 15, 2021, and included feasibility studies, clinical trials, and observational studies, including preprints. We found 561 studies, of which 13 were included in our narrative synthesis. These 13 studies were all observational cohorts and involved a total of 2908 participants. A meta-analysis was not feasible owing to the heterogeneity of the outcomes reported in the included studies. Our systematic review substantiates the safety and potential of pulse oximetry for monitoring patients at home with COVID-19, identifying the risk of deterioration and the need for advanced care. The use of pulse oximetry can potentially save hospital resources for patients who might benefit the most from care escalation;however, we could not identify explicit evidence for the effect of RPM with pulse oximetry on health outcomes compared with other monitoring models such as virtual wards, regular monitoring consultations, and online or paper diaries to monitor changes in symptoms and vital signs. Based on our findings, we make 11 recommendations across the three Donabedian model domains and highlight three specific measurements for setting up an RPM system with pulse oximetry.
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Collection: Databases of international organizations Database: Web of Science Type of study: Experimental Studies / Reviews / Systematic review/Meta Analysis Language: English Journal: LANCET DIGITAL HEALTH Year: 2022 Document Type: Article

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Collection: Databases of international organizations Database: Web of Science Type of study: Experimental Studies / Reviews / Systematic review/Meta Analysis Language: English Journal: LANCET DIGITAL HEALTH Year: 2022 Document Type: Article