Objectives: The COVID-19 outbreak in Singapore has largely centred around migrant worker dormitories, comprising over 90% of all cases in the country. Dormitories are home to a culturally and linguistically distinct, low-income population, without on-site healthcare after-hours. The primary objective of this study was to assess the engagement and utilisation of a simple, low-cost, accessible, mobile health solution for remote self-reporting of vital parameters in dormitory residents with COVID-19.
Design: Retrospective review of medical care.
Setting: Two large migrant worker dormitories with a combined population of 31 546.
Participants: All COVID-19-affected residents housed in dormitories during the study period.
Intervention: All residents were taught to use a chat assistant to self-report their temperature, heart rate and oxygen saturations. Results flowed into a dashboard, which alerted clinicians of abnormal results.
Outcomes: The primary outcome measure was engagement rate. This was derived from the total number of residents who registered on the platform over the total number of COVID-19-affected residents in the dormitories during the study period. Secondary outcome measures included outcomes of the alerts and subsequent escalations of care.
Results: 800 of the 931 COVID-19-affected residents (85.9%) engaged with the platform to log a total of 12 511 discrete episodes of vital signs. Among 372 abnormal readings, 96 teleconsultations were initiated, of which 7 (1.8%) were escalated to emergency services and 18 (4.9%) were triaged to earlier physical medical review on-site.
Conclusions: A chat-assistant-based self-reporting platform is an effective and safe community-based intervention to monitor marginalised populations with distinct cultural and linguistic backgrounds, living communally and affected by COVID-19. Lessons learnt from this approach may be applied to develop safe and cost-effective telemedicine solutions across similar settings.
Keywords: health informatics; public health; telemedicine; world wide web technology.
© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.