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논문 기본 정보

자료유형
학술저널
저자정보
Cho Minsung (Department of Public Health, Yonsei University Graduate School, Seoul, Republic of Korea) Lee Hyeok-Hee (Yonsei University College of Medicine, Seoul) Baek Jang-Hyun (Department of Neurology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.Department of Neurology, Severance Stroke Center, Severance Hospital, Yonsei Unive) Yum Kyu Sun (Department of Neurology, Chungbuk National University Hospital, Chungbuk National University College of Medicinee) Kim Min (Department of Internal Medicine, Chungbuk National University College of Medicine) 배장환 (충북대학교) Lee Seung-Jun (Department of Internal Medicine, Yonsei University College of Medicine) Kim Byeong-Keuk (Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, Korea.) Kim Yung Ah (Division of Digital Health, Yonsei University Health System) Yang JiHyun (Department of Medical Records, Severance Hospital, Yonsei University Health System,) Kim Dong Wook (Department of Information and Statistics, Research Institute of Natural Science, Gyeongsang National University, Jinju, Korea.) Kim Young Dae (Department of Neurology, Yonsei University College of Medicine, Seoul, Korea) 박해용 (국민건강보험공단 일산병원) Kim Kyung Won (Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea.) Park Sohee (Department of Biostatistics, Graduate School of Public Health, Yonsei University, Seoul, Korea) You Seng Chan (Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea.) Lee Hokyou (Yonsei University College of Medicine, Seoul) Kim Hyeon Chang (Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea)
저널정보
한국역학회 Epidemiology and Health Epidemiology and Health Vol.46
발행연도
2024.1
수록면
1 - 7 (7page)
DOI
10.4178/epih.e2024001

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초록· 키워드

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OBJECTIVES The escalating burden of cardiovascular disease (CVD) is a critical public health issue worldwide. CVD, especially acute myocardial infarction (AMI) and stroke, is the leading contributor to morbidity and mortality in Korea. We aimed to develop algorithms for identifying AMI and stroke events from the National Health Insurance Service (NHIS) database and validate these algorithms through medical record review. METHODS We first established a concept and definition of “hospitalization episode,” taking into account the unique features of health claims-based NHIS database. We then developed first and recurrent event identification algorithms, separately for AMI and stroke, to determine whether each hospitalization episode represents a true incident case of AMI or stroke. Finally, we assessed our algorithms’ accuracy by calculating their positive predictive values (PPVs) based on medical records of algorithm-identified events. RESULTS We developed identification algorithms for both AMI and stroke. To validate them, we conducted retrospective review of medical records for 3,140 algorithm-identified events (1,399 AMI and 1,741 stroke events) across 24 hospitals throughout Korea. The overall PPVs for the first and recurrent AMI events were around 92% and 78%, respectively, while those for the first and recurrent stroke events were around 88% and 81%, respectively. CONCLUSIONS We successfully developed algorithms for identifying AMI and stroke events. The algorithms demonstrated high accuracy, with PPVs of approximately 90% for first events and 80% for recurrent events. These findings indicate that our algorithms hold promise as an instrumental tool for the consistent and reliable production of national CVD statistics in Korea.
#Acute myocardial infarction #Stroke #Identification #Algorithm #Epidemiology

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