Innovative use of health informatics to augment contact tracing during the COVID-19 pandemic in an acute hospital

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.

Keywords: COVID-19; contact tracing, informatics system; data mining algorithm, improved manpower utilization.