Disease severity classification and COVID-19 outcomes, Republic of Korea

Problem The surge in coronavirus disease 2019 (COVID-19) cases overwhelmed the health system in the Republic of Korea. Approach To help health-care workers prioritize treatment for patients with more severe disease and to decrease the burden on health systems caused by COVID-19, the government established a system to classify disease severity. Health-care staff in city- and provincial-level patient management teams classified the patients into the different categories according to the patients' pulse, systolic blood pressure, respiratory rate, body temperature and level of consciousness. Patients categorized as having moderate, severe and very severe disease were promptly assigned to beds or negative-pressure isolation rooms for hospital treatment, while patients with mild symptoms were monitored in 16 designated facilities across the country. Local setting The case fatality rate was higher in the city of Daegu and the Gyeongsangbuk- do province (1.6%; 124/7756) than the rest of the country (0.5%; 7/1485). Relevant changes From 25 February to 26 March 2020, the ratio of negative-pressure isolation rooms per COVID-19 patient was below 0.15 in the city of Daegu and the Gyeongsangbuk- do province. In the rest of the country, this ratio decreased from 5.56 to 0.63 during the same period. Before the classification system was in place, eight (15.7%) out of the 51 deaths occurred at home or during transfer from home to health-care institutions. Lessons learnt Categorizing patients according to their disease severity should be a prioritized measure to ease the burden on health systems and reduce the case fatality rate.

Automated summary

The surge in COVID-19 cases overwhelmed the health system in South Korea, leading the government to establish a severity classification system to prioritize treatment for patients and reduce the burden on healthcare facilities. Categorizing patients based on disease severity has been effective in reducing case fatality rates and optimizing healthcare resources utilization.