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2 "Population surveillance"
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Developing a national surveillance system for stroke and acute myocardial infarction using claims data in the Republic of Korea: a retrospective study
Tae Jung Kim, Hak Seung Lee, Seong-Eun Kim, Jinju Park, Jun Yup Kim, Jiyoon Lee, Ji Eun Song, Jin-Hyuk Hong, Joongyub Lee, Joong-Hwa Chung, Hyeon Chang Kim, Dong-Ho Shin, Hae-Young Lee, Bum Joon Kim, Woo-Keun Seo, Jong-Moo Park, Soo Joo Lee, Keun-Hwa Jung, Sun U. Kwon, Yun-Chul Hong, Hyo-Soo Kim, Hyun-Jae Kang, Juneyoung Lee, Hee-Joon Bae
Osong Public Health Res Perspect. 2024;15(1):18-32.   Published online January 31, 2024
DOI: https://doi.org/10.24171/j.phrp.2023.0248
  • 1,966 View
  • 96 Download
Graphical AbstractGraphical Abstract AbstractAbstract PDF
Objectives
Limited information is available concerning the epidemiology of stroke and acute myocardial infarction (AMI) in the Republic of Korea. This study aimed to develop a national surveillance system to monitor the incidence of stroke and AMI using national claims data. Methods: We developed and validated identification algorithms for stroke and AMI using claims data. This validation involved a 2-stage stratified sampling method with a review of medical records for sampled cases. The weighted positive predictive value (PPV) and negative predictive value (NPV) were calculated based on the sampling structure and the corresponding sampling rates. Incident cases and the incidence rates of stroke and AMI in the Republic of Korea were estimated by applying the algorithms and weighted PPV and NPV to the 2018 National Health Insurance Service claims data. Results: In total, 2,200 cases (1,086 stroke cases and 1,114 AMI cases) were sampled from the 2018 claims database. The sensitivity and specificity of the algorithms were 94.3% and 88.6% for stroke and 97.9% and 90.1% for AMI, respectively. The estimated number of cases, including recurrent events, was 150,837 for stroke and 40,529 for AMI in 2018. The age- and sex-standardized incidence rate for stroke and AMI was 180.2 and 46.1 cases per 100,000 person-years, respectively, in 2018. Conclusion: This study demonstrates the feasibility of developing a national surveillance system based on claims data and identification algorithms for stroke and AMI to monitor their incidence rates.
Changes in the pattern and disease burden of acute respiratory viral infections before and during the COVID-19 pandemic
Chungmin Park, Donghan Lee, Bryan Inho Kim, Sujin Park, Gyehee Lee, Sangwoo Tak
Osong Public Health Res Perspect. 2022;13(3):203-211.   Published online June 30, 2022
DOI: https://doi.org/10.24171/j.phrp.2022.0144
  • 5,424 View
  • 177 Download
  • 1 Web of Science
  • 1 Crossref
AbstractAbstract PDF
Objectives
We conducted a comparative analysis of the differences in the incidence of 8 acute respiratory viruses and the changes in their patterns before and during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Three sentinel surveillance systems of the Korea Disease Control and Prevention Agency and data from the Health Insurance Review and Assessment Service were analyzed. The average numbers of reported cases and the related hospital admissions and outpatient data were compared between April 2018–2019 and 2020–2021. Changes in the disease burden and medical expenditures between these 2 time periods were evaluated. Results: During the COVID-19 pandemic, the number of reported cases of all acute respiratory viral infections, except for human bocavirus, decreased significantly. Data from the Health Insurance Review and Assessment Service also showed decreases in the actual amount of medical service usage and a marked reduction in medical expenditures. Conclusion: Non-pharmacological interventions in response to COVID-19 showed preventive effects on the transmission of other respiratory viruses, as well as COVID-19. Although COVID-19 had a tremendous impact on society as a whole, with high social costs, there were also positive effects, such as a reduction in the incidence of acute respiratory viral infections.

Citations

Citations to this article as recorded by  
  • Machine learning forecasts for seasonal epidemic peaks: Lessons learnt from an atypical respiratory syncytial virus season
    Roger A. Morbey, Daniel Todkill, Conall Watson, Alex J. Elliot, André Ricardo Ribas Freitas
    PLOS ONE.2023; 18(9): e0291932.     CrossRef

PHRP : Osong Public Health and Research Perspectives
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