- Identifying Adverse Events Using International Classification of Diseases, Tenth Revision Y Codes in Korea: A Cross-sectional Study
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Minsu Ock, Hwa Jung Kim, Bomin Jeon, Ye-Jee Kim, Hyun Mi Ryu, Moo-Song Lee
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J Prev Med Public Health. 2018;51(1):15-22. Published online January 4, 2018
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DOI: https://doi.org/10.3961/jpmph.17.118
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- Objectives
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.
Methods 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.
Results 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%).
Conclusions 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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- Accuracy assessment of patient safety incident (PSI) codes and present-on-admission (POA) indicators: a cross-sectional analysis using the Patient Safety Incidents Inquiry (PSII) in Korea
Jeehee Pyo, Eun Young Choi, Seung Gyeong Jang, Won Lee, Minsu Ock BMC Health Services Research.2024;[Epub] CrossRef - Development of the Korean Patient Safety Incidents Code Classification System
Eun Young Choi, Jeehee Pyo, Young-Kwon Park, Minsu Ock, Sukyeong Kim Journal of Patient Safety.2023; 19(1): 8. CrossRef - Use of a hospital administrative database to identify and characterize community-acquired, hospital-acquired and drug-induced acute kidney injury
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Eunkyeong Choi, Siin Kim, Hae Sun Suh Journal of Clinical Medicine.2022; 11(21): 6248. CrossRef - Feasibility of Capturing Adverse Events From Insurance Claims Data Using International Classification of Diseases, Tenth Revision, Codes Coupled to Present on Admission Indicators
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
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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
- Zolpidem Use and Risk of Fracture in Elderly Insomnia Patients
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Dong-Yoon Kang, Soyoung Park, Chul-Woo Rhee, Ye-Jee Kim, Nam-Kyong Choi, Joongyub Lee, Byung-Joo Park
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J Prev Med Public Health. 2012;45(4):219-226. Published online July 31, 2012
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DOI: https://doi.org/10.3961/jpmph.2012.45.4.219
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17,343
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To evaluate the risk of fractures related with zolpidem in elderly insomnia patients. MethodsHealth claims data on the entire South Korean elderly population from January 2005 to June 2006 were extracted from the Health Insurance Review and Assessment Service database. We applied a case-crossover design. Cases were defined as insomnia patients who had a fracture diagnosis. We set the hazard period of 1 day length prior to the fracture date and four control periods of the same length at 5, 10, 15, and 20 weeks prior to the fracture date. Time independent confounding factors such as age, gender, lifestyle, cognitive function level, mobility, socioeconomic status, residential environment, and comorbidity could be controlled using the casecrossover design. Time dependent confounding factors, especially co-medication of patients during the study period, were adjusted by conditional logistic regression analysis. The odds ratios and their 95% confidence intervals (CIs) were estimated for the risk of fracture related to zolpidem. ResultsOne thousand five hundred and eight cases of fracture were detected in insomnia patients during the study period. In our data, the use of zolpidem increased the risk of fracture significantly (adjusted odds ratio [aOR], 1.72; 95% CI, 1.37 to 2.16). However, the association between benzodiazepine hypnotics and the risk of fracture was not statistically significant (aOR, 1.00; 95% CI, 0.83 to 1.21). Likewise, the results were not statistically significant in stratified analysis with each benzodiazepine generic subgroup. ConclusionsZolpidem could increase the risk of fracture in elderly insomnia patients. Therefore zolpidem should be prescribed carefully and the elderly should be provided with sufficient patient education.
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