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

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...

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Detalles Bibliográficos
Autores principales: Venkataraman, Narayan, Poon, Beng Hoong, Siau, Chuin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7499570/
https://www.ncbi.nlm.nih.gov/pubmed/32835358
http://dx.doi.org/10.1093/jamia/ocaa184
Descripción
Sumario: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.