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2 "Dong Wook Kim"
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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
  • 4,501 View
  • 107 Download
  • 1 Crossref
AbstractAbstract AbstractSummary PDF
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
The Validity and Reliability of Characterizing Epilepsy Based on an External Review of Medical Records
Bong Su Kang, Hae-Kwan Cheong, Ki-Young Jung, Sang Hyeon Jang, Jae Kook Yoo, Dong Wook Kim, Soo-Eun Chung, Seo-Young Lee
Epidemiol Health. 2013;35:e2013006.   Published online August 23, 2013
DOI: https://doi.org/10.4178/epih/e2013006
  • 17,876 View
  • 128 Download
  • 9 Crossref
AbstractAbstract PDF
Abstract
<sec><title>OBJECTIVES</title><p>Our goal is to validate diagnosing and characterizing epilepsy based on a medical record survey by external reviewers.</p></sec><sec><title>METHODS</title><p>We reviewed medical records from 80 patients who received antiepileptic drugs in 2009 at two hospitals. The study consisted of two steps; data abstraction by certified health record administrators and then verification by the investigators. The gold standard was the results of the survey performed by the epileptologists from their own hospital.</p></sec><sec><title>RESULTS</title><p>The specificity was more than 90.0% for diagnosis and activity, and for new-onset seizures. The sensitivity was 97.0% or more for diagnosis and activity and 66.7-75.0% for new-onset epilepsy. This method accurately classified epileptic syndromes in 90.2-92.9% of patients, causes in 85.4-92.7%, and age of onset in 78.0-81.0%. Kappa statistics for inter-rater reliability and test-retest reliability ranged from 0.641-0.975, which means substantial to near-perfect agreement in all items.</p></sec><sec><title>CONCLUSIONS</title><p>Our data suggest that epilepsy can be well identified by external review of medical records. This method may be useful as a basis for large-scale epidemiological research.</p></sec>
Summary

Citations

Citations to this article as recorded by  
  • The association between early childhood onset epilepsy and attention-deficit hyperactivity disorder (ADHD) in 3237 children and adolescents with Autism Spectrum Disorder (ASD): a historical longitudinal cohort data linkage study
    Lauren Carson, Valeria Parlatini, Tara Safa, Benjamin Baig, Hitesh Shetty, Jacqueline Phillips-Owen, Vibhore Prasad, Johnny Downs
    European Child & Adolescent Psychiatry.2023; 32(11): 2129.     CrossRef
  • Risk of COVID-19 Infection and of Severe Complications Among People With Epilepsy
    Joonsang Yoo, Jee Hyun Kim, Jimin Jeon, Jinkwon Kim, Tae-Jin Song
    Neurology.2022;[Epub]     CrossRef
  • The bumpy road to achieve reliability of clinical profile characteristics in psychosis and related disorders
    Steven Berendsen, Mirjam J. van Tricht, Amy Tedja, Thijs J. Burger, Mariken B. de Koning, Lieuwe de Haan
    International Journal of Methods in Psychiatric Research.2021;[Epub]     CrossRef
  • Staging and profiling for schizophrenia spectrum disorders: Inter-rater reliability after a short training course
    Steven Berendsen, Jasper W. van der Paardt, Henricus L. Van, Marion van Bruggen, Hans Nusselder, Margje Jalink, Olav R. de Peuter, Jaap Peen, Mirjam J. van Tricht, Lieuwe de Haan
    Progress in Neuro-Psychopharmacology and Biological Psychiatry.2020; 99: 109856.     CrossRef
  • The new definition and classification of seizures and epilepsy
    Jessica J. Falco-Walter, Ingrid E. Scheffer, Robert S. Fisher
    Epilepsy Research.2018; 139: 73.     CrossRef
  • Presentation and management of community-onset vs hospital-onset first seizures
    Emma Foster, Sarah Holper, Zhibin Chen, Patrick Kwan
    Neurology Clinical Practice.2018; 8(5): 421.     CrossRef
  • Estimating the Prevalence of Treated Epilepsy Using Administrative Health Data and Its Validity: ESSENCE Study
    Seo-Young Lee, Soo-Eun Chung, Dong Wook Kim, So-Hee Eun, Hoon Chul Kang, Yong Won Cho, Sang Do Yi, Heung Dong Kim, Ki-Young Jung, Hae-Kwan Cheong
    Journal of Clinical Neurology.2016; 12(4): 434.     CrossRef
  • Early Antiretroviral Therapy Is Protective Against Epilepsy in Children With Human Immunodeficiency Virus Infection in Botswana
    David Bearden, Andrew P. Steenhoff, Dennis J. Dlugos, Dennis Kolson, Parth Mehta, Sudha Kessler, Elizabeth Lowenthal, Baphaleng Monokwane, Gabriel Anabwani, Gregory P. Bisson
    JAIDS Journal of Acquired Immune Deficiency Syndromes.2015; 69(2): 193.     CrossRef
  • Clinical characteristics of patients with treated epilepsy in Korea: A nationwide epidemiologic study
    Dong Wook Kim, Seo‐Young Lee, Soo‐Eun Chung, Hae‐Kwan Cheong, Ki‐Young Jung
    Epilepsia.2014; 55(1): 67.     CrossRef

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