ArticleJMIR formative research2025
Monitoring People With COVID-19 at Home With the COVIDFree@Home Program: Feasibility Cohort Study.
Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Predicting low oxygen in patients with acute COVID-19 infection isolating at home: a clinical prediction model.BMJ open respiratory research · 2026Trial
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: During the COVID-19 pandemic, many with acute infection isolated at home, with a small but significant number requiring hospitalization. At the time, since the pathogen was fairly unknown, clinicians were uncertain about which patients would rapidly deteriorate and need hospitalization. We developed the COVIDFree@Home smartphone app and clinician dashboard to monitor and support people managing at home with acute COVID-19 infection. It was uncertain whether such an app would be used by patients and whether it would support patient care. This knowledge would inform telemedicine and digital health tools being used to deliver care to patients remotely at that time. Objective: This study aimed to determine the feasibility of using a smartphone app and clinician dashboard for remote clinical monitoring of people with COVID-19 at home. Methods: A feasibility study set at 3 hospital sites (University Health Network, Sunnybrook Health Sciences Centre, and Trillium Health Partners) between 2020 and 2022 was conducted. Participants newly diagnosed with COVID-19 were asked to enter data into a smartphone app called COVIDFree@Home twice daily for 10 days while isolating at home. Their data, including symptoms, temperature, and oxygen saturation, were monitored on a clinician-facing dashboard. The primary outcome of feasibility was the number of patients who used the app. We also examined patient satisfaction through a survey questionnaire. Results: A total of 431 patients were recruited, out of which 229 (56.5%) were females and the average age was 38.9 (SD 12.8) years. There were 376 (87.2%) participants who used the app to report symptoms or oxygen saturation at least once. Among these participants, 373 (99.2%) reported symptoms and 363 (96.5%) reported oxygen saturation. Participants reported symptoms an average of 1.7 (SD 1.1) times per day for a median of 5 (IQR 3-8) days. Oxygen saturation levels were reported 1.5 times per day for a median of 6 (IQR 4-9) days. There were 19 hospitalizations (4.4%) among study participants. Most patients felt comfortable using the app, felt reassured their data was being monitored and did not have privacy concerns. Conclusions: Patients with acute COVID-19 infection engaged with a remote home monitoring platform, however, not at the recommended frequency or duration. Remote patient monitoring of acute respiratory infection appears viable and can offer patients reassurance. It has the potential to reduce strain on the health care system during future pandemics, but further evidence is required to demonstrate improved health outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.