Innovative use of health informatics to augment contact tracing during the COVID-19 pandemic in an acute hospital
Narayan Venkataraman, Beng Hoong Poon, Chuin Siau
Abstract
This case report describes the innovative design and build of an algorithm that integrates available data from separate hospital-based informatics systems, which perform different daily functions to augment the contact-tracing process of COVID-19 patients by identifying exposed neighboring patients and healthcare workers and assessing their risk. Prior to the establishment of the algorithm, contact-tracing teams comprising 6 members would spend up to 10 hours each to complete contact tracing for 5 new COVID-19 patients. With the augmentation by the algorithm, we observed ≥ 60% savings in overall man-hours needed for contact tracing when there were 5 or more daily new cases through a time-motion study and Monte Carlo simulation. This improvement to the hospital's contact-tracing process supported more expeditious and comprehensive downstream contact-tracing activities as well as improved manpower utilization in contact tracing.