At Home Monitoring for Patients With Covid19

Covidfree@Home: At Home Monitoring Using Mobile Devices for Patients With Covid19

The vast majority of individuals with Covid19 have mild illness that can be managed in the outpatient setting. A small but significant number of these people will deteriorate and require hospitalization. Symptoms are a poor - and possibly late - indicator for deterioration. While people who have died, and/or been cared for in the ICU or hospital have been well characterized, there remains a dearth of information about the clinical course of people in the outpatient setting. Most notably, it is not known when to escalate to hospital care. The consequence of non-escalation when needed is significant patient morbidity and mortality, of escalation when not needed is unnecessarily overwhelmed hospitals. Technologies for clinical management and early diagnostics for severe Covid19 infection will address this challenge.

The research goal of this study is to use real-time remote patient monitoring to detect which patients with Covid19 are at risk of deterioration to bring to hospital, while at the same ensuring the worried will receive reassurance so they stay at home. The clinical goal is to help clinicians provide excellent care using ubiquitous mobile phones.

Study Overview

• Status: Completed
• Conditions: Coronavirus
• Intervention / Treatment: Device: Covidfree@home

Detailed Description

People with COVID infection recovering at home or in long-term care are at high risk of hospitalization and death, a reservoir of the disease, and the source of any second wave. Three important gaps still besiege their well-being and, consequently, the well-being of all of us. First, we cannot yet accurately predict the approximately 10% who deteriorate and need hospitalization. Deterioration happens quick and without warning. Delayed detection of deterioration worsens patient outcomes. Second, COVID patients feel terrified and alone. This leads them to come to EDs when not indicated, to have poor mental health and to risk violating physical distancing rules. Third, the health of people with COVID cannot be improved without having a means of studying and understanding what they are going through. None of these gaps are being filled by public health.

It is imperative that Ontario have an effective and safe outpatient care and research strategy for people with COVID isolated at home and in long term care to survive this COVID pandemic.

The investigators are building a mobile smartwatch/smartphone application to create a scalable safe virtual system that meets the care needs of COVID patients at home and in long term care (including reassurance when they are doing well), that uses continuous symptom, heart rate, respiratory rate, cough and other monitoring to predict who needs to go to hospital in real time and that provides a research platform to learn how to further improve and preserve their health.

• Study Type: Interventional
• Enrollment (Actual): 432
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Canada
  • Ontario
    • Toronto, Ontario, Canada, M4N3M5
      • Sunnybrook Health Sciences Centre
    • Toronto, Ontario, Canada, M5G 2Cr
      • University Health Network

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria

• Patients who tested positive for Covid19
• Patients experiencing symptoms of Covid19 and have been deemed to likely have Covid19

Exclusion Criteria

• Does not speak English
• Unable to use a mobile smartphone and smart watch
• Unable to complete questionnaires on own
• Significant comorbid condition that would confound symptoms and sensor readings
• Deemed palliative with goals of care being comfort measures only

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Covi19 patients receiving intervention; We will collect self-reported symptoms via a questionnaire, temperature and oxygen saturation will be entered by the patient and passive near continuous sensing of heart rate, audio for cough detection, respiratory rate, cough and physical activity from a smart watch. The smart watch then transmits this sensor data to the paired smartphone.	Device: Covidfree@home; Mobile phone, Covidfree@home app, thermometer, pulse oximeter, smart watch

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of participants with an unplanned hospital admissions	Number of participants with an unplanned emergency department visits leading to hospital admission	30 days
Number of participants with planned hospital admissions that are found to be necessary	Number of participants with planned hospital admissions that are found to be necessary	30 days

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of participants with an emergency department visits not resulting in hospital admission	Number of participants with an emergency department visit not resulting in a hospital admission	30 days
Number of planned hospital admissions which are found to be unnecessary	Number of planned hospital admissions which are found to be unnecessary	30 days

Collaborators and Investigators

• Sponsor: University Health Network, Toronto
• Collaborators: Sunnybrook Health Sciences Centre; University of Toronto
• Investigators: Principal Investigator: Robert Wu, University Health Network, Toronto

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2020
• Primary Completion (Actual): July 1, 2022
• Study Completion (Actual): June 1, 2024

Study Registration Dates

• First Submitted: May 6, 2020
• First Submitted That Met QC Criteria: June 29, 2020
• First Posted (Actual): July 1, 2020

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: January 22, 2025
• Last Verified: January 1, 2025

More Information

Terms related to this study

• Keywords: epidemiology; telemedicine; hospitalization; clinical care; predictive modeling
• Additional Relevant MeSH Terms: Infections; RNA Virus Infections; Virus Diseases; Coronaviridae Infections; Nidovirales Infections; Coronavirus Infections
• Other Study ID Numbers: 3185

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No