Identification of acute myocardial infarction and stroke events using the National Health Insurance Service database in Korea

• 영문명: Identification of acute myocardial infarction and stroke events using the National Health Insurance Service database in Korea
• 발행기관: 한국역학회
• 저자명: Minsung Cho Hyeok-Hee Lee Jang-Hyun Baek Kyu Sun Yum Min Kim Jang-Whan Bae Seung-Jun Lee Byeong-Keuk Kim Young Ah Kim JiHyun Yang Dong Wook Kim Young Dae Kim Haeyong Pak Kyung Won Kim Sohee Park Seng Chan You Hokyou Lee Hyeon Chang Kim
• 간행물 정보: 『Epidemiology and Health』46, 1~7쪽, 전체 7쪽
• 주제분류: 의약학 > 면역학
• 파일형태: PDF
• 발행일자: 2024.01.31

영문 초록

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.

목차

INTRODUCTION

HOSPITALIZATION EPISODE

ALGORITHMS FOR IDENTIFYING DISEASE EVENTS

VALIDATION OF THE IDENTIFICATION ALGORITHMS

DISCUSSION

CONCLUSION

NOTES

REFERENCES

키워드

Acute myocardial infarction Stroke Identification Algorithm Epidemiology