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Moo-Song Lee 2 Articles
Identifying Adverse Events Using International Classification of Diseases, Tenth Revision Y Codes in Korea: A Cross-sectional Study
Minsu Ock, Hwa Jung Kim, Bomin Jeon, Ye-Jee Kim, Hyun Mi Ryu, Moo-Song Lee
J Prev Med Public Health. 2018;51(1):15-22.   Published online January 4, 2018
  • 6,940 View
  • 196 Download
  • 9 Crossref
AbstractAbstract PDFSupplementary Material
The use of administrative data is an affordable alternative to conducting a difficult large-scale medical-record review to estimate the scale of adverse events. We identified adverse events from 2002 to 2013 on the national level in Korea, using International Classification of Diseases, tenth revision (ICD-10) Y codes.
We used data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC). We relied on medical treatment databases to extract information on ICD-10 Y codes from each participant in the NHIS-NSC. We classified adverse events in the ICD-10 Y codes into 6 types: those related to drugs, transfusions, and fluids; those related to vaccines and immunoglobulin; those related to surgery and procedures; those related to infections; those related to devices; and others.
Over 12 years, a total of 20 817 adverse events were identified using ICD-10 Y codes, and the estimated total adverse event rate was 0.20%. Between 2002 and 2013, the total number of such events increased by 131.3%, from 1366 in 2002 to 3159 in 2013. The total rate increased by 103.9%, from 0.17% in 2002 to 0.35% in 2013. Events related to drugs, transfusions, and fluids were the most common (19 446, 93.4%), followed by those related to surgery and procedures (1209, 5.8%) and those related to vaccines and immunoglobulin (72, 0.3%).
Based on a comparison with the results of other studies, the total adverse event rate in this study was significantly underestimated. Improving coding practices for ICD-10 Y codes is necessary to precisely monitor the scale of adverse events in Korea.


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    BMC Health Services Research.2024;[Epub]     CrossRef
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    Eun Young Choi, Jeehee Pyo, Young-Kwon Park, Minsu Ock, Sukyeong Kim
    Journal of Patient Safety.2023; 19(1): 8.     CrossRef
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    Eunkyeong Choi, Siin Kim, Hae Sun Suh
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    Juyoung Kim, Eun Young Choi, Won Lee, Hae Mi Oh, Jeehee Pyo, Minsu Ock, So Yoon Kim, Sang-il Lee
    Journal of Patient Safety.2022; 18(5): 404.     CrossRef
  • The Korea National Patient Safety Incidents Inquiry Survey: Characteristics of Adverse Events Identified Through Medical Records Review in Regional Public Hospitals
    Min Ji Kim, Hee Jung Seo, Hong Mo Koo, Minsu Ock, Jee-In Hwang, Sang-Il Lee
    Journal of Patient Safety.2022; 18(5): 382.     CrossRef
  • Use of ICD‐10‐CM T codes in hospital claims data to identify adverse drug events in Taiwan
    Ya‐Fang Cheng, Chi‐Yuan Cheng, Szu‐Hsuan Wang, Yu‐Ting Lin, Tzu‐Cheng Tsai
    Journal of Clinical Pharmacy and Therapeutics.2021; 46(2): 476.     CrossRef
  • Perceptions of Hospital Health Information Managers Regarding Present on Admission Indicators in Korea: A Qualitative Study
    Jee-Hee Pyo, Eun-Young Choi, Hae-Mi Oh, Won Lee, Ju-Young Kim, Min-Su Ock, So-Yoon Kim, Sang-Il Lee
    Quality Improvement in Health Care.2020; 26(1): 23.     CrossRef
  • Variation between hospitals and reviewers in detection of adverse events identified through medical record review in Korea
    Sukyeong Kim, Ho Gyun Shin, A E Jeong Jo, Ari Min, Minsu Ock, Jee-In Hwang, Youngjin Jeong, Moon Sung Park, Jong Bouk Lee, Tae I K Chang, Eunhyang Song, Heungseon Kim, Sang-Il Lee
    International Journal for Quality in Health Care.2020; 32(8): 495.     CrossRef
Cardiovascular Health Metrics and All-cause and Cardiovascular Disease Mortality Among Middle-aged Men in Korea: The Seoul Male Cohort Study
Ji Young Kim, Young-Jin Ko, Chul Woo Rhee, Byung-Joo Park, Dong-Hyun Kim, Jong-Myon Bae, Myung-Hee Shin, Moo-Song Lee, Zhong Min Li, Yoon-Ok Ahn
J Prev Med Public Health. 2013;46(6):319-328.   Published online November 28, 2013
  • 15,099 View
  • 158 Download
  • 53 Crossref
AbstractAbstract PDF

This study estimated the association of cardiovascular health behaviors with the risk of all-cause and cardiovascular disease (CVD) mortality in middle-aged men in Korea.


In total, 12 538 men aged 40 to 59 years were enrolled in 1993 and followed up through 2011. Cardiovascular health metrics defined the following lifestyle behaviors proposed by the American Heart Association: smoking, physical activity, body mass index, diet habit score, total cholesterol, blood pressure, and fasting blood glucose. The cardiovascular health metrics score was calculated as a single categorical variable, by assigning 1 point to each ideal healthy behavior. A Cox proportional hazards regression model was used to estimate the hazard ratio of cardiovascular health behavior. Population attributable risks (PARs) were calculated from the significant cardiovascular health metrics.


There were 1054 total and 171 CVD deaths over 230 690 person-years of follow-up. The prevalence of meeting all 7 cardiovascular health metrics was 0.67%. Current smoking, elevated blood pressure, and high fasting blood glucose were significantly associated with all-cause and CVD mortality. The adjusted PARs for the 3 significant metrics combined were 35.2% (95% confidence interval [CI], 21.7 to 47.4) and 52.8% (95% CI, 22.0 to 74.0) for all-cause and CVD mortality, respectively. The adjusted hazard ratios of the groups with a 6-7 vs. 0-2 cardiovascular health metrics score were 0.42 (95% CI, 0.31 to 0.59) for all-cause mortality and 0.10 (95% CI, 0.03 to 0.29) for CVD mortality.


Among cardiovascular health behaviors, not smoking, normal blood pressure, and recommended fasting blood glucose levels were associated with reduced risks of all-cause and CVD mortality. Meeting a greater number of cardiovascular health metrics was associated with a lower risk of all-cause and CVD mortality.



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JPMPH : Journal of Preventive Medicine and Public Health