Journal of Preventive Medicine and Public Health

COVID-19: Special Article

COVID-19 International Collaborative Research by the Health Insurance Review and Assessment Service Using Its Nationwide Real-world Data: Database, Outcomes, and Implications: Yeunsook Rho, Do Yeon Cho, Yejin Son, Yu Jin Lee, Ji Woo Kim, Hye Jin Lee, Seng Chan You, Rae Woong Park, Jin Yong Lee; J Prev Med Public Health. 2021;54(1):8-16. Published online January 26, 2021; DOI: https://doi.org/10.3961/jpmph.20.616

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This article aims to introduce the inception and operation of the COVID-19 International Collaborative Research Project, the world’s first coronavirus disease 2019 (COVID-19) open data project for research, along with its dataset and research method, and to discuss relevant considerations for collaborative research using nationwide real-world data (RWD). COVID-19 has spread across the world since early 2020, becoming a serious global health threat to life, safety, and social and economic activities. However, insufficient RWD from patients was available to help clinicians efficiently diagnose and treat patients with COVID-19, or to provide necessary information to the government for policy-making. Countries that saw a rapid surge of infections had to focus on leveraging medical professionals to treat patients, and the circumstances made it even more difficult to promptly use COVID-19 RWD. Against this backdrop, the Health Insurance Review and Assessment Service (HIRA) of Korea decided to open its COVID-19 RWD collected through Korea’s universal health insurance program, under the title of the COVID-19 International Collaborative Research Project. The dataset, consisting of 476 508 claim statements from 234 427 patients (7590 confirmed cases) and 18 691 318 claim statements of the same patients for the previous 3 years, was established and hosted on HIRA’s in-house server. Researchers who applied to participate in the project uploaded analysis code on the platform prepared by HIRA, and HIRA conducted the analysis and provided outcome values. As of November 2020, analyses have been completed for 129 research projects, which have been published or are in the process of being published in prestigious journals.

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Evaluation Studies

An Evaluation of Sampling Design for Estimating an Epidemiologic Volume of Diabetes and for Assessing Present Status of Its Control in Korea.: Ji Sung Lee, Jaiyong Kim, Sei Hyun Baik, Ie Byung Park, Juneyoung Lee; J Prev Med Public Health. 2009;42(2):135-142.; DOI: https://doi.org/10.3961/jpmph.2009.42.2.135

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Abstract PDF

OBJECTIVES
An appropriate sampling strategy for estimating an epidemiologic volume of diabetes has been evaluated through a simulation. METHODS: We analyzed about 250 million medical insurance claims data submitted to the Health Insurance Review & Assessment Service with diabetes as principal or subsequent diagnoses, more than or equal to once per year, in 2003. The database was re-constructed to a 'patient-hospital profile' that had 3,676,164 cases, and then to a 'patient profile' that consisted of 2,412,082 observations. The patient profile data was then used to test the validity of a proposed sampling frame and methods of sampling to develop diabetic-related epidemiologic indices. RESULTS: Simulation study showed that a use of a stratified two-stage cluster sampling design with a total sample size of 4,000 will provide an estimate of 57.04% (95% prediction range, 49.83 - 64.24%) for a treatment prescription rate of diabetes. The proposed sampling design consists, at first, stratifying the area of the nation into "metropolitan/city/county" and the types of hospital into "tertiary/secondary/primary/clinic" with a proportion of 5:10:10:75. Hospitals were then randomly selected within the strata as a primary sampling unit, followed by a random selection of patients within the hospitals as a secondly sampling unit. The difference between the estimate and the parameter value was projected to be less than 0.3%. CONCLUSIONS: The sampling scheme proposed will be applied to a subsequent nationwide field survey not only for estimating the epidemiologic volume of diabetes but also for assessing the present status of nationwide diabetes control.

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Diabetes & Metabolism Journal.2013; 37(4): 233. CrossRef
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Asian Pacific Journal of Cancer Prevention.2012; 13(9): 4661. CrossRef

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