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Covid Fast Fax: A system for real-time triage of Covid-19 case report faxes

Authors :
Matthew White
Adam Lavertu
Rajiv Pramanik
Greg McInnes
Alison Stribling
Russ B. Altman
Amit Kaushal
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

The scale and speed of the COVID-19 pandemic has strained many parts of the national healthcare infrastructure, including communicable disease monitoring and prevention. Many local health departments now receive hundreds or thousands of COVID-19 case reports a day. Many arrive via faxed handwritten forms, often intermingled with other faxes sent to a general fax line, making it difficult to rapidly identify the highest priority cases for outreach and monitoring. We present an AI-based system capable of real-time identification and triage of handwritten faxed COVID-19 forms. The system relies on two models: one model to identify which received pages correspond to case report forms, and a second model to extract information from the set of identified case reports. We evaluated the system on a set of 1,224 faxes received by a local health department over a two-week period. For the 88% of faxes of sufficient quality, the system detects COVID-19 reports with high precision, 0.98, and high recall, 0.91. Among all received COVID-19 faxes, the system identifies high priority cases with a specificity of 0.87, a precision of 0.46 and recall of 0.83. Our system can be adapted to new forms, after a brief training period. Covid Fast Fax can support local health departments in their efforts to control the spread of COVID-19 and limit its impact on the community. The tool is freely available.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........e5ba048ba214e3ea38433a689540e8e5