Providing ambulatory medicine based on remote surveillance for COVID-19 patients with mild-to-moderate symptoms can help to preserve medical resources for the most severe patients and limit in-person interactions during the pandemic. While most patients will be able to endure the disease at home, it is estimated that 10 to 15% of the cases will become more severe, requiring hospitalisation. The challenge of remote monitoring therefore is to identify the patients at risk of deterioration as quickly as possible, and to propose a timely response.
Covidom is a web application for home management of patients with mild-to-moderate symptoms of COVID-19 through distant monitoring. The application has proven to be helpful, but this project will seek to improve it with patient data. Patients using the app fill in brief, standardised daily questionnaires on their symptoms for 30 days. Their answers are analysed by algorithms, and when a problem is indicated, the system generates mild or top-priority alerts, which are managed by a single regional control centre. In case of an alert, the control centre can refer the patient to a consultation or hospitalisation, or else send mobile emergency services directly to a patient’s home. Covidom was launched in the Paris area on 9 March 2020, and 50,000 patients are already included in the system. Now it is being deployed in other French regions. The Covidom team initially developed empirical algorithms to trigger alerts, but many alerts proved to be irrelevant. The project team will use patient data that has already been gathered by the system to improve the algorithms, thereby making the Covidom platform more efficient.
Covidom benefits the health system by enabling patient care while preserving hospital beds and the time of professional carers for patients that truly need these resources. It also mitigates risks to healthcare workers by reducing their direct contact with COVID-19 cases. Learning from patient data obtained through the app will not only improve the accuracy of the Covidom algorithms, it will also provide valuable information on the nature of COVID-19.
EIT Health Partner