PDF(Pubmed)
Abstract：
BACKGROUND: 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.
CONCLUSIONS: 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.
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.
CONCLUSIONS: 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.
摘要：
背景：关于大韩民国中风和急性心肌梗死（AMI）的流行病学信息有限。这项研究旨在开发一个国家监测系统，以使用国家索赔数据监测中风和AMI的发病率。
方法：我们使用索赔数据开发并验证了中风和AMI的识别算法。该验证涉及2阶段分层抽样方法，并对抽样病例的病历进行审查。加权阳性预测值（PPV）和阴性预测值（NPV）是根据采样结构和相应的采样率计算的。通过将算法和加权PPV和NPV应用于2018年国民健康保险服务索赔数据，估计了大韩民国的中风和AMI的发病率。
结果：总计，从2018年索赔数据库中抽取了2200例病例（1,086例中风病例和1,114例AMI病例）。算法对卒中的敏感性和特异性分别为94.3%和88.6%,对AMI的敏感性和特异性分别为97.9%和90.1%,分别。估计的病例数,包括复发事件，2018年中风为150,837例，AMI为40,529例。卒中和AMI的年龄和性别标准化发病率分别为180.2和46.1例/10万人年，分别,在2018年。
结论：本研究证明了开发基于索赔数据和识别算法的国家监测系统以监测卒中和AMI发病率的可行性。
方法：我们使用索赔数据开发并验证了中风和AMI的识别算法。该验证涉及2阶段分层抽样方法，并对抽样病例的病历进行审查。加权阳性预测值（PPV）和阴性预测值（NPV）是根据采样结构和相应的采样率计算的。通过将算法和加权PPV和NPV应用于2018年国民健康保险服务索赔数据，估计了大韩民国的中风和AMI的发病率。
结果：总计，从2018年索赔数据库中抽取了2200例病例（1,086例中风病例和1,114例AMI病例）。算法对卒中的敏感性和特异性分别为94.3%和88.6%,对AMI的敏感性和特异性分别为97.9%和90.1%,分别。估计的病例数,包括复发事件，2018年中风为150,837例，AMI为40,529例。卒中和AMI的年龄和性别标准化发病率分别为180.2和46.1例/10万人年，分别,在2018年。
结论：本研究证明了开发基于索赔数据和识别算法的国家监测系统以监测卒中和AMI发病率的可行性。
