After the World Health Organization declared a COVID-19 pandemic, global health care researchers are becoming more interested in South Korea’s experience and data. The country is becoming a center of research on international clinical data to overcome COVID-19 based on data of treatment information and progress in Korean patients.

EvidNet, which has built up clinical data of 27 general hospitals in Korea as well as 33 million hospitals that are part of the standard data network, began research on COVID-19 along with the general hospitals in Daegu and North Gyeongsan Province, which have joined the data network.

Based on the clinical standard data of COVID-19 prepared by EvidNet, various researchers can conduct diverse studies such as comparing the safety and efficacy of medicines already being taken by patients and being considered as treatments for the novel coronavirus and predicting the prognosis of the confirmed patients. It also provides a data platform.

The OHDSI Consortium conducted a research marathon online for four days from March 26 to 29, using standardized data from COVID-19 patients available worldwide to tackle the pandemic. The research marathon was attended by more than 350 global researchers from institutions including National Institutes of Health, Johnson Hopkins University, and Oxford University.

EvidNet joins forces with Ajou University Industry-Academic Cooperation Foundation, which received funding from the Bill & Melinda Gates Foundation regarding the steps for standardizing and providing COVID-19 clinical data from Korea to the research marathon.

Meanwhile, by the end of 2020, EvidNet aims to establish big data infrastructure that can be safely used without personal information exposure by standardizing and de-identifying 50 million patients’ medical data. Based on this infrastructure, the company plans to support the activation of the data service ecosystem in the healthcare field.

EvidNet has developed a data conversion technology that powers patient data standardization, which turns medical data of different formats into a standard data model that is recognized internationally.

(khnews@heraldcorp.com)