CoronavirusNCT04453774
At Home Monitoring for Patients With Covid19
A study testing Covidfree@home in people with Coronavirus, run by University Health Network, Toronto at 2 sites in Canada.
Trial 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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Coronavirus
- What is being tested?
- Covidfree@home
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 432 participants
- Where
- 2 sitesCanada
- Study dates
- 1 Nov 2020to 1 Jun 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- Patients who tested positive for Covid19
- Patients experiencing symptoms of Covid19 and have been deemed to likely have Covid19
Who cannot join
- 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
Trial locations and contacts
2 sites in 1 country.
Canada2 sites
Sunnybrook Health Sciences Centre
Toronto, Ontario, M4N3M5
University Health Network
Toronto, Ontario, M5G 2Cr
About this study
Official title: 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.
Read the 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.
- Conditions
- Coronavirus
- Being tested
- Covidfree@home
- Keywords
- telemedicine, clinical care, predictive modeling, epidemiology, hospitalization
- Medical subject headings
- Coronavirus Infections
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Covidfree@homeDevice
Mobile phone, Covidfree@home app, thermometer, pulse oximeter, smart watch
| Study group | Role | What they receive |
|---|---|---|
| Covi19 patients receiving intervention | Experimental | 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. Receives: Device: Covidfree@home |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of participants with an unplanned hospital admissions
Number of participants with an unplanned emergency department visits leading to hospital admission
Measured: 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
Measured: 30 days
Secondary outcomes (2)
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
Measured: 30 days
Number of planned hospital admissions which are found to be unnecessary
Number of planned hospital admissions which are found to be unnecessary
Measured: 30 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Jul 2020
- Study start1 Nov 2020
- Primary completion1 Jul 2022
- Study completion1 Jun 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for CoronavirusStudies of the same condition, open and under way.
- More trials run by University Health Network, TorontoThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 432 participants (actual)
Sponsor and investigators
- Lead sponsor
- University Health Network, Toronto
- Sponsor type
- University, hospital or other
- Collaborators
- Sunnybrook Health Sciences Centre, University of Toronto
- Responsible party
- Principal investigator, Robert Wu, University Health Network, Toronto
- Investigators
- Robert Wu, Principal investigator, University Health Network, Toronto
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04453774
- Sponsor's protocol ID
- 3185
- Status last verified
- Jan 2025
- First submitted
- 6 May 2020
- Last updated
- 24 Jan 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Wu R, Mariakakis A, de Lara E, Munn J, Liaqat D, Liaqat S, Chen J, To T, Lam PW, Simor A, Chan AK, Andany N, Masood S, Daneman N, Chan T, Graham C, Comondore V, Tu AY, Gershon A. Predicting low oxygen in patients with acute COVID-19 infection isolating at home: a clinical prediction model. BMJ Open Respir Res. 2026 Feb 24;13(1):e003728. doi: 10.1136/bmjresp-2025-003728.
PubMed 41735015Gershon AS, Mariakakis A, de Lara E, Munn J, Calligan M, Liaqat D, Liaqat S, Chen J, To T, Lam PW, Simor A, Chan AK, Andany N, Masood S, Daneman N, Chan T, Graham C, Comondore V, de Moulliac A, Tu AY, Wu R. Monitoring People With COVID-19 at Home With the COVIDFree@Home Program: Feasibility Cohort Study. JMIR Form Res. 2025 Oct 8;9:e69140. doi: 10.2196/69140.
PubMed 41061108
Study at a glance
From the registry record, last updated by the sponsor on 24 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Covidfree@Home: At Home Monitoring Using Mobile Devices for Patients With Covid19
- ClinicalTrials.gov ID
- NCT04453774
- Acronym / sponsor ID
- 3185
- Conditions
- Coronavirus
- Keywords
- telemedicine, clinical care, predictive modeling, epidemiology, hospitalization
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 432 participants (actual)
- Lead sponsor
- University Health Network, TorontoUniversity, hospital or other
- Collaborators
- Sunnybrook Health Sciences Centre, University of Toronto
- Study start
- 1 Nov 2020 (actual)
- Primary completion
- 1 Jul 2022 (actual)
- Study completion
- 1 Jun 2024 (actual)
- First posted
- 1 Jul 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Covi19 patients receiving intervention | Experimental | Device: Covidfree@homeWe 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. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (2 listed)
- Patients who tested positive for Covid19
- Patients experiencing symptoms of Covid19 and have been deemed to likely have Covid19
Key exclusion criteria (5 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Covidfree@homeMobile phone, Covidfree@home app, thermometer, pulse oximeter, smart watch | Device | Covi19 patients receiving intervention |
Primary outcome
Number of participants with an unplanned hospital admissions
Time frame: 30 days
Number of participants with an unplanned emergency department visits leading to hospital admission
Number of participants with planned hospital admissions that are found to be necessary
Time frame: 30 days
Number of participants with planned hospital admissions that are found to be necessary
2 secondary outcomes
Number of participants with an emergency department visits not resulting in hospital admission
Time frame: 30 days
Number of planned hospital admissions which are found to be unnecessary
Time frame: 30 days
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Jan 2025.
- Derived from this study: PubMed 41735015Wu R, Mariakakis A, de Lara E, Munn J, Liaqat D, Liaqat S, Chen J, To T, Lam PW, Simor A, Chan AK, Andany N, Masood S, Daneman N, Chan T, Graham C, Comondore V, Tu AY, Gershon A. Predicting low oxygen in patients with acute COVID-19 infection isolating at home: a clinical prediction model. BMJ Open Respir Res. 2026 Feb 24;13(1):e003728. doi: 10.1136/bmjresp-2025-003728.
- Derived from this study: PubMed 41061108Gershon AS, Mariakakis A, de Lara E, Munn J, Calligan M, Liaqat D, Liaqat S, Chen J, To T, Lam PW, Simor A, Chan AK, Andany N, Masood S, Daneman N, Chan T, Graham C, Comondore V, de Moulliac A, Tu AY, Wu R. Monitoring People With COVID-19 at Home With the COVIDFree@Home Program: Feasibility Cohort Study. JMIR Form Res. 2025 Oct 8;9:e69140. doi: 10.2196/69140.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Robert Wu principal investigator
University Health Network, Toronto
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Covidfree@home in people with Coronavirus, run by University Health Network, Toronto at 2 sites in Canada.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Jan 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of participants with an unplanned hospital admissions (time frame: 30 days). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04453774, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Jan 2025.