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At Home Monitoring for Patients With Covid19

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

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT04453774
Enrollment
432
Registered
2020-07-01
Start date
2020-11-01
Completion date
2024-06-01
Last updated
2025-01-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Coronavirus

Keywords

telemedicine, clinical care, predictive modeling, epidemiology, hospitalization

Brief summary

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.

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.

Interventions

DEVICECovidfree@home

Mobile phone, Covidfree@home app, thermometer, pulse oximeter, smart watch

Sponsors

Sunnybrook Health Sciences Centre
CollaboratorOTHER
University of Toronto
CollaboratorOTHER
University Health Network, Toronto
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

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

Design outcomes

Primary

MeasureTime frameDescription
Number of participants with an unplanned hospital admissions30 daysNumber of participants with an unplanned emergency department visits leading to hospital admission
Number of participants with planned hospital admissions that are found to be necessary30 daysNumber of participants with planned hospital admissions that are found to be necessary

Secondary

MeasureTime frameDescription
Number of participants with an emergency department visits not resulting in hospital admission30 daysNumber of participants with an emergency department visit not resulting in a hospital admission
Number of planned hospital admissions which are found to be unnecessary30 daysNumber of planned hospital admissions which are found to be unnecessary

Countries

Canada

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 26, 2026