UTILITY AND USABILITY OF AN AUTOMATED COVID-19 SYMPTOM MONITORING SYSTEM (CoSMoS) IN PRIMARY CARE DURING COVID-19 PANDEMIC: A QUALITATIVE STUDY

Abstract

COVID-19 telemonitoring applications have been developed and used in primary care to monitor patients quarantined at home. There is a lack of evidence on the utility and usability of telemonitoring applications from the end user’s perspective. This study aimed to evaluate the utility and usability of a COVID-19 symptom monitoring system (CoSMoS), which consists of an algorithm-based Telegram bot, a monitoring dashboard and teleconsultation. This was a qualitative study using in-depth interviews. Patients with suspected COVID-19 infection who used CoSMoS Telegram bot to monitor their COVID-19 symptoms and doctors who conducted the telemonitoring via CoSMoS dashboard were recruited. Universal sampling was used in this study. We stopped the recruitment when data saturation was reached. Patients and doctors shared their experiences using CoSMoS, its utility and usability for COVID-19 symptoms monitoring. Data were coded and analysed using thematic analysis. A total of 11 patients and four doctors were recruited into this study. For utility, CoSMoS was found to be useful in providing close monitoring and continuity of care, supporting patients’ decision making, ensuring adherence to reporting, and reducing healthcare workers’ burden during the pandemic. In terms of usability, patients expressed that CoSMoS was convenient and easy to use. The use of the existing social media application for symptom monitoring was acceptable for the patients. The content in the Telegram bot was easy to understand, although revision was needed to keep the content updated. Doctors preferred to integrate CoSMoS into the electronic medical record. CoSMoS was acceptable and useful to the patients and doctors in providing remote monitoring and teleconsultation in a primary care setting. This study suggested that CoSMoS might reduce the healthcare system’s burden while providing a better patient care model during the pandemic. This study highlighted the key lessons learned to design and implement a user-centred monitoring system during a pandemic.