Evaluation of a Remote Monitoring Smartphone Application and Care Model of COVID-19 Patients in the Community (ReCOVER)

Study Overview
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Brief Summary
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This is a multi-site, prospective, non-randomised trial assessing the implementation of a smartphone application-based model of care for patients with COVID-19 infection managed in community isolation. We will recruit 2000 COVID +ve patients aged 18 years and over who are managed at home. The objective will be to describe the rates of avoidable presentations to ED and 30 day all case mortality per diagnosed COVID-19 case and to compare these to a propensity matched and synthetic control group.

Official Title
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ReCOVER (Remote COVID-19 Evaluation and Response): a Prospective Non-randomised Controlled Trial to Evaluate the Effect of a Novel Smartphone Application-centric Model of Care for the Remote Monitoring of COVID-19 Patients in the Community.

Conditions
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COVID

Intervention / Treatment
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* Device: TCC-COVID mHealth solution


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age greater or equal to 18 years Able to provide informed consent Proven diagnosis of COVID-19 based on positive virology testing Patients who are being managed at home OR those who are being discharged from hospital for ongoing home-based care in isolation. Access to a smartphone or device that is compatible with the TCC-COVID app Any iPhone or iPad running iOS 9 or above (essentially any iPhone 5 or above) Any Android phone that is operating Android 7.0 or above Speaks adequate English Exclusion Criteria: Patient meets clinical criteria for hospital-based care. Inability to use the TCC-COVID app and pulse oximeter due to reasons including but not limited to: Cognitive impairment Impaired dexterity Visual impairment Language barrier Patient residing outside the SESLHD catchment area during their period of isolation

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Supportive Care
Allocation: Non-Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Active Comparator: TCC-COVID mHealth solution<br>TCC-COVID is an app-based model of care which includes a smartphone app and a pulse oximeter that measures oxygen saturation, pulse rate and collects symptoms, connected to a back-end clinical database with inbuilt data analytics. | Device: TCC-COVID mHealth solution<br>* Patients place their index finger in the pulse oximeter to measure their oxygen saturation and pulse rate twice a day, which will take approximately 5 minutes each time. Patients then enter the results into the TCC-COVID app twice daily, and complete a symptom questionnaire via the TCC-COVID app once daily, which will take approximately 5 minutes. The symptom questionnaire was designed specifically for this study. The measurements and information are directly connected to a clinician interface (KIOLA database) which provides the data of all patients in aggregate and an easy to use responsive format with customisable alerts. The alerts identify if the oxygen saturation levels are low or the pulse rate is out of range. The alerts also identify if a measurement has not been completed in a timely manner and the central monitoring service will contact the patient to check on their safety or if they are experiencing any technical issues. The overall duration of participation will be 14 days.<br>|
| No Intervention: Control<br>Propensity matched and synthetic control groups will be utilised from another local health district not participating in the ReCOVER study. The control group will not be actively recruited at the same time as the intervention. The control group will be matched via data linkage at the completion of the trial. However, it is not a historical control, as the control standard of care treatment will be provided simultaneously as our intervention | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Rate of avoidable Emergency Department presentations per diagnosed COVID-19 case | Definition based on potentially avoidable general practitioner-type presentations as specified in the National Healthcare | 12 months | 
| All cause mortality per diagnosed COVID-19 case All-cause mortality rate at 30 days per diagnosed COVID-19 case |  | 30 days | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Rate of hospital admission per diagnosed COVID case | Data linkage to patient medical records | 12 months | 
| Rate of MBS claims for un-referred visits to general practitioners and analogous COVID-19 MBS telehealth items per diagnosed COVID case | Data linkage to MBS database and patient medical records | 12 months | 
| Average length of stay (LOS) for admitted patients per diagnosed COVID case | Data linkage to patient medical records | 12 months | 
| Rate of admission to Intensive Care Unit (ICU) for admitted patients per diagnosed COVID case | Data linkage to patient medical records | 12 months | 
| Time from presentation to admission to ICU for patients admitted to ICU per diagnosed COVID case | Data linkage to patient medical records | 12 months | 
| Rate of intubation in admitted patients per diagnosed COVID case | Data linkage to patient medical records | 12 months | 
| Rate of readmission within 30 days of discharge in admitted patients per diagnosed COVID case | Data linkage to patient medical records | 30 days | 
| All-cause mortality at 90 days per diagnosed COVID case |  | 90 days | 
| Rate of avoidable Emergency Department presentations with COVID-19 diagnosis per 100,000 population, during trial period | Data linkage to patient medical records | 12 months | 
| Rate of hospital admission with COVID-19 diagnosis per 100,000 population, during trial period | Data linkage to patient medical records | 12 months | 
| Rate of admission to ICU with COVID-19 diagnosis per 100,000 population during trial period | Data linkage to patient medical records | 12 months | 
| Rate of mortality with COVID-19 cause of death per 100,000 population, during trial period | Data linkage to patient medical records | 12 months | 
| Qualitative assessment of TCC-COVID app usability via a subjective feedback questionnaire provided to all patients enrolled in the study. | The feedback questionnaire was designed specifically for this study. | 12 months | 
| Cost-effectiveness of TCC-COVID by measuring the incremental cost per death averted, per ICU admission averted and per length of stay in ICU | From NSW Health data linkage | 12 months | 
| Rate of hospital bed days with COVID-19 diagnosis per 100,000 population, during trial period | Data linkage to patient medical records | 12 months | 
| Rate of ICU bed days with COVID-19 diagnosis per 100,000 population, during trial period | Data linkage to patient medical records | 12 months | 
| Qualitative assessment of KIOLA physician portal usability via a subjective feedback questionnaire | Completed by all physicians and research nurses entering data into the portal and monitoring patients throughout the study. The feedback questionnaire was designed specifically for this study. | 12 months |