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KMID : 1812620220020020183
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HIRA Research
2022 Volume.2 No. 2 p.183 ~ p.201
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Changes of Inpatient Health Care Utilization in Public and Private Hospitals during the COVID-19 Pandemic
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Kim Dong-Hwan
Yoo Tae-Kyung
Lee Yoon-Ye
An Mi-Ra
An Sung-Eun
Baek Sang-Ju
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Abstract
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Background: This study aimed to compare the difference in healthcare utilization public and private hospitals (by hospital ownership) during Coronavirus disease (COVID-19) pandemic in Republic of Korea.
Methods: The study analyzed the national health insurance claim data from January 1, 2019 to December 31, 2021. We performed a panel regression with a fixed effects model using balanced panel data (n=406, time=36). The response variables are the number of inpatients per bed and the proportion of COVID-19 inpatients. The uncertainty was measured by volatility (calculating standard deviation) of daily confirmed cases of COVID-19. An interaction term between volatility and public hospital was included as an explanatory variable. In addition, region population, geospatial accessibility, the number of beds, the ratio of negative pressure isolation beds, and COVID-19 severity were included as control variables.
Results: As a result of panel regression analysis, for aggregation of data, (1) the volatility of daily confirmed cases of COVID-19 was not directly related to the number of inpatients per bed. For public hospitals, an increase in the number of inpatients per bed was observed with increasing volatility of daily confirmed cases of COVID-19. (2) For the log-transformed value of the number of inpatients per bed, the time effect of the first wave was ?0.488, which was lower than those of the second (-0.328), third (-0.468), and fourth (-0.276) waves. (3) The interaction of volatility and public hospitals was positively associated with the ratio of COVID-19 inpatients.
Conclusion: In this study, quantification of uncertainty is proposed to reduce uncertainty of new infectious diseases. Therefore, it is expected to contribute to the policies on health resources.
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KEYWORD
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COVID-19, Pandemic, Inpatients, Uncertainty, Volatility
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