Remote Monitoring of COVID-19 Positive Outpatients

Covid19

Telemedicine, Risk assessment

This study seeks to evaluate how secondary data retrieved from remote physiological monitoring performed during routine outpatient/at-home care periods can allow for the discovery of novel physiomarkers that predict acute deterioration or hospitalization among people testing positive for Coronavirus Disease 2019 (COVID-19).

Most recent research publications and clinical trials have exclusively focused on the hospital and intensive care unit (ICU) care of COVID-19 patients. Few have focused on how to direct care delivered at home, where the majority of coronavirus infected will recover, and how and when to rescue those who are at immediate risk for poor outcomes. To standardize the home monitoring process and offer guidance in this uncharted territory, the researchers have created a method for outpatient management of COVID-19 patients and high suspicion influenza-like illness (ILI) for Emory University Hospital. This includes the newly implemented model of clinics including in-person ambulatory management in the Acute Respiratory Clinic (ARC), the Virtual Outpatient Management Clinic (VOMC), and the Emory COVID-19 Outpatient Remote Monitoring Registry (E-CORMR). Initial analysis of the management system, particularly in risk tier assignment, has shown that assigning risk tiers early can help to identify patients at risk for clinical deterioration. The researchers have also demonstrated symptom profiles and durations of the typical outpatient disease course. The E-CORMR was used to create a dashboard for improved management of these frequently complex patients. It was determined after its creation that it could also be used for research purposes to store data collected from physiologic parameters. The goal of this study is to develop algorithms using secondary data abstracted from remote monitoring devices that were collected within the E-CORMR. The researchers propose to derive robust algorithms through the analysis of that data that identify a potential hospitalization. The findings will not only improve the management of patients with known or suspected COVID-19 but also provide information that allows early intervention on patients at risk of decompensation. This information can then be used by other healthcare systems to care for patients more safely at home, thus reducing the impact of COVID-19 on overburdened acute care settings and preventing poor outcomes.

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United States