Epidemiology and Health

Special Article

Identification of acute myocardial infarction and stroke events using the National Health Insurance Service database in Korea: 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; Epidemiol Health. 2024;46:e2024001. Published online December 26, 2023; DOI: https://doi.org/10.4178/epih.e2024001

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Abstract

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.

Summary

Key Message
In this study, we developed algorithms to identify acute myocardial infarction (AMI) and stroke events from the Korean National Health insurance Service database. To validate them, we conducted retrospective review of medical records across 24 hospitals throughout Korea. The overall positive predictive values 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.

Citations

Citations to this article as recorded by

Incidence and case fatality rates of stroke in Korea, 2011-2020
Jenny Moon, Yeeun Seo, Hyeok-Hee Lee, Hokyou Lee, Fumie Kaneko, Sojung Shin, Eunji Kim, Kyu Sun Yum, Young Dae Kim, Jang-Hyun Baek, Hyeon Chang Kim
Epidemiology and Health.2023; : e2024003. CrossRef

Original Article

Real-world incidence of endopthalmitis after intravitreal anti-VEGF injections in Korea: findings from the Common Data Model in ophthalmology: Yongseok Mun, Seng Chan You, Da Yun Lee, Seok Kim, Yoo-Ri Chung, Kihwang Lee, Ji Hun Song, Young Gun Park, Young Hoon Park, Young-Jung Roh, Se Joon Woo, Kyu Hyung Park, Rae Woong Park, Sooyoung Yoo, Dong-Jin Chang, Sang Jun Park; Epidemiol Health. 2021;43:e2021097. Published online November 9, 2021; DOI: https://doi.org/10.4178/epih.e2021097

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Abstract Summary PDF Supplementary Material

Abstract

OBJECTIVES
The aim of this study was to evaluate the real-world incidence of endophthalmitis after intravitreal anti-vascular endothelial growth factor (VEGF) injections using data from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM).

METHODS

Patients with endophthalmitis that developed within 6 weeks after intravitreal anti-VEGF injections were identified in 3 large OMOP CDM databases.

RESULTS

We identified 23,490 patients who received 128,123 intravitreal anti-VEGF injections. The incidence rates of endophthalmitis were 15.75 per 10,000 patients and 2.97 per 10,000 injections. The incidence rates of endophthalmitis for bevacizumab, ranibizumab, and aflibercept (per 10,000 injections) were 3.64, 1.39, and 0.76, respectively. The annual incidence has remained below 5.00 per 10,000 injections since 2011 despite the increasing number of intravitreal anti-VEGF injections. Bevacizumab presented a higher incidence rate for endophthalmitis than ranibizumab and aflibercept (incidence rate ratio, 3.17; p=0.021).

CONCLUSIONS

The incidence of endophthalmitis after intravitreal anti-VEGF injections has stabilized since 2011 despite the explosive increase in anti-VEGF injections. The off-label use of bevacizumab accounted for its disproportionately high incidence of endophthalmitis. The OMOP CDM, which includes off-label uses, laboratory data, and a scalable standardized database, could provide a novel strategy to reveal real-world evidence, especially in ophthalmology.

Summary

Korean summary
- 공통데이터모델 (Observational Medical Outcomes Partnership Common Data Model, OMOP CDM)을 통해 유리체강내 항혈관내피성장인자 주입술 후 발생한 안내염의 실세계 발생률 (Real-world incidence)은 1만명 당 15.75명, 주사 1만회 당 2.97회였음을 알 수 있었다. - 베바시주맙에서 다른 항혈관내피성장인자에 비해 유리체강내 주사 후 안내염 발생 비율이 높았으며, 이는 약제의 분주로 인한 오염과 관련이 있을 것이다. - 공통데이터모델은 건강보험 청구자료가 포함하지 않는 유리체강내 베바시주맙 사용과 같은 오프라벨 의약품 사용 자료까지 포함하기 때문에, 유리체강내 항혈관내피성장인자 주입 후 발생한 안내염의 인구기반 발생률 추정을 가능케 했다.

Key Message
- The real-world incidence of endophthalmitis after intravitreal anti-vascular endothelial growth factor (VEGF) injections was 15.75 per 10,000 patients and 2.97 per 10,000 injections based on data from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). - Patients treated with bevacizumab showed a significantly higher incidence rate of post-injection endophthalmitis, which might have resulted from contamination related to the division of bevacizumab. - OMOP CDM provides insights into the population-based incidence rate of endophthalmitis since it covers off-label prescriptions including intravitreal bevacizumab, which the national claims database does not cover.

Citations

Citations to this article as recorded by

Real-World Treatment Intensity and Patterns in Patients With Myopic Choroidal Neovascularization: Common Data Model in Ophthalmology
Manh-Hung Bui, Da Yun Lee, Sang Jun Park, Kyu Hyung Park
Journal of Korean Medical Science.2023;[Epub] CrossRef
Efficacy of Injection Interval Shortening in Neovascular Age-related Macular Degeneration with Limited Response to Bimonthly Aflibercept
Min Chul Kim, Jae Hui Kim
Journal of the Korean Ophthalmological Society.2023; 64(8): 700. CrossRef
Postintravitreal Injection Endophthalmitis: Incidence, Characteristics, Management, and Outcome
Bar Davidov, Avi Ohayon, Omer Trivizki, Shulamit Schwartz, Shiri Shulman, Akio Oishi
Journal of Ophthalmology.2023; 2023: 1. CrossRef
Aflibercept

Reactions Weekly.2023; 1983(1): 23. CrossRef
Real-world treatment intensities and pathways of macular edema following retinal vein occlusion in Korea from Common Data Model in ophthalmology
Yongseok Mun, ChulHyoung Park, Da Yun Lee, Tong Min Kim, Ki Won Jin, Seok Kim, Yoo-Ri Chung, Kihwang Lee, Ji Hun Song, Young-Jung Roh, Donghyun Jee, Jin-Woo Kwon, Se Joon Woo, Kyu Hyung Park, Rae Woong Park, Sooyoung Yoo, Dong-Jin Chang, Sang Jun Park
Scientific Reports.2022;[Epub] CrossRef
Blueprint for harmonising unstandardised disease registries to allow federated data analysis: prepare for the future
Johannes A. Kroes, Aruna T. Bansal, Emmanuelle Berret, Nils Christian, Andreas Kremer, Anna Alloni, Matteo Gabetta, Chris Marshall, Scott Wagers, Ratko Djukanovic, Celeste Porsbjerg, Dominique Hamerlijnck, Olivia Fulton, Anneke ten Brinke, Elisabeth H. Be
ERJ Open Research.2022; 8(4): 00168-2022. CrossRef
Towards effective data sharing in ophthalmology: data standardization and data privacy
William Halfpenny, Sally L. Baxter
Current Opinion in Ophthalmology.2022; 33(5): 418. CrossRef

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