Dr. Syed-Abdul Shabbir, an Associate Professor from Taipei Medical University (TMU) helped his team to give a brilliant demonstration of the TMU Smart Triage at-home screening system at MIT COVID-19 Datathon.
Dr. Shabbir worked with teammates from the United States, Hong Kong, Colombia, and other countries to develop the Smart Triage—a self-assessment and risk analysis system, which allows users to assess their risk of being infected by COVID-19 and decide whether it’s necessary to visit the hospital urgently.
According to Dr. Shabbir, Smart-Triage is based on a database of 72,000 confirmed cases of COVID-19 from the United States and China. Users can enter their age, gender, habits, disease history, and current symptoms into the system, which then provides them with current potential risk of being infected. This information further helps users to determine the urgency of a hospital visit.
The design of the system is based on the user’s medical records, including whether they had a loss of smell (anosmia), coughing, diabetes, tobacco addiction, etc. Users are also informed if their health condition requires immediate medical attention and screening. If the score is low, users can choose to go to the hospital when it’s not too crowded to avoid increasing their risk of contracting the virus.
As the epidemic is raging all over the world, healthcare professionals and medical resources are being tested to their limits. Dr. Shabbir and his teammates designed the system primarily to make hospital screenings more efficient and help to reduce burden on the medical team. This way, members of the public without urgent needs can avoid unnecessary hospital visits, and unnecessary risks of contagion are reduced.
The team used data from tens of thousands of confirmed COVID-19 cases to design a weighted scoring system. Through the system, the public can learn what their likelihood of COVID-19 contagion is. The system also integrates a hospital registration system, which provides waiting time for screening, while displaying the possibility of other patients waiting for appointments, being infected by COVID-19. This helps users decide when to visit the hospital. Not only does this make for more efficient traffic flows, but it also lowers the risk of infection.
Thus, in order to reduce the burden on hospital authorities, this system can help to deliver such solutions, in response to the epidemic, enabling efficient and timely healthcare delivery.