Treatment cost assessment for COVID-19 inpatients in Shenzhen, China 2020-2021: facts and suggestions

2020-2021年中国深圳新冠肺炎住院患者治疗费用评估:事实与建议

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Abstract

BACKGROUND: Knowledge regarding the treatment cost of coronavirus disease 2019 (COVID-19) in the real world is vital for disease burden forecasts and health resources planning. However, it is greatly hindered by obtaining reliable cost data from actual patients. To address this knowledge gap, this study aims to estimate the treatment cost and specific cost components for COVID-19 inpatients in Shenzhen city, China in 2020-2021. METHODS: It is a 2 years' cross-sectional study. The de-identified discharge claims were collected from the hospital information system (HIS) of COVID-19 designated hospital in Shenzhen, China. One thousand three hundred ninety-eight inpatients with a discharge diagnosis for COVID-19 from January 10, 2020 (the first COVID-19 case admitted in the hospital in Shenzhen) to December 31, 2021. A comparison was made of treatment cost and cost components of COVID-19 inpatients among seven COVID-19 clinical classifications (asymptomatic, mild, moderate, severe, critical, convalescent and re-positive cases) and three admission stages (divided by the implementation of different treatment guidelines). The multi-variable linear regression models were used to conduct the analysis. RESULTS: The treatment cost for included COVID-19 inpatients was USD 3,328.8. The number of convalescent cases accounted for the largest proportion of all COVID-19 inpatients (42.7%). The severe and critical cases incurred more than 40% of treatment cost on western medicine, while the other five COVID-19 clinical classifications spent the largest proportion (32%-51%) on lab testing. Compared with asymptomatic cases, significant increases of treatment cost were observed in mild cases (by 30.0%), moderate cases (by 49.2%), severe cases (by 228.7%) and critical cases (by 680.7%), while reductions were shown in re-positive cases (by 43.1%) and convalescent cases (by 38.6%). The decreasing trend of treatment cost was observed during the latter two stages by 7.6 and 17.9%, respectively. CONCLUSIONS: Our findings identified the difference of inpatient treatment cost across seven COVID-19 clinical classifications and the changes at three admission stages. It is highly suggestive to inform the financial burden experienced by the health insurance fund and the Government, to emphasize the rational use of lab tests and western medicine in the COVID-19 treatment guideline, and to design suitable treatment and control policy for convalescent cases.

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