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만성 신경병성 통증의 약물 치료: 근거-중심의 약물 치료
조상훈,안용우,옥수민,허준영,고명연,정성희,Cho, Sang-Hoon,Ahn, Yong-Woo,Ok, Soo-Min,Huh, Joon-Young,Ko, Myung-Yun,Jeong, Sung-Hee 대한안면통증구강내과학회 2011 Journal of Oral Medicine and Pain Vol.36 No.2
Neuropathic pain is defined by "pain is initiated or caused by primary lesion or dysfunction in the nervous system" and several etiologic conditions can induce the neuropathic pains. Various groups of drugs are used to treat the neuropathic pains. Not depending on anecdotal case or habitual choice, to obtain the more effective pharmacotherapy, relative-comparison index is suggested through multiple analyses of clinical trials. Depending on relative-comparison index, first-line medications and second-line medications for neuropathic pain are recommended. To support the Quality of life in patients, selection of medication is made on such recommendations.
국민건강보험공단의 표본연구DB를 위한 비주얼 쿼리 데이터베이스 시스템 개발 연구
조상훈,김희찬,강근석,Cho, Sang-Hoon,Kim, HeeChan,Kang, Gunseog 한국통계학회 2017 응용통계연구 Vol.30 No.1
The Sample Cohort DB supplied by the National Health Insurance Service is a valuable resource for statistical studies as well as for health and medical studies. It takes significant time and effort to extract data from this Cohort DB having a large size. As such, we introduce a database system, conveniently called the National Health Insurance Service Cohort DB Extract Tool (NICE Tool), which supports several useful operations for effectively and efficiently managing the Cohort DB. For example, researchers can extract variables and cases related with study by simply clicking a computer mouse without any prior knowledge regarding SAS DATA step or SQL. We expect that NICE Tool will facilitate the faster extraction of data and eventually lead to the active use of the Cohort DB for research purposes. 국민건강보험공단에서 제공하는 표본코호트DB는 보건의료계뿐만 아니라 통계학 연구를 위한 중요한 자원이다. 일반적으로 이들 자료에서 연구에 필요한 정보를 얻기 위하여 관련 사례들을 추출하는 과정에는 많은 시간과 노력이 들게 된다. 본 논문에서는 표본코호트DB를 이용하고자 할 때 사례 추출과정에 도움을 주는 데이터베이스 시스템인 National Health Insurance Service Cohort DB Extract Tool(NICE Tool)을 소개한다. SAS의 DATA 명령문이나 SQL문에 익숙하지 않은 연구자들도 쉽게 마우스 클릭만으로 DB에서 필요한 변수들과 조건에 맞는 사례들을 추출할 수 있는 기능을 제공한다. 이 시스템을 활용하면 빠른 사례추출이 가능하여 표본코호트DB를 사용한 연구들이 더욱 활성화되리라 판단된다.
로지스틱 회귀모형을 사용한 율의 표준화 방법: 국민건강보험공단 건강검진코호트 사용
조상훈 ( Sang-hoon Cho ),강근석 ( Gunseog Kang ),김현창 ( Hyeon Chang Kim ) 한국보건정보통계학회 2017 보건정보통계학회지 Vol.42 No.1
Objectives: To illustrate an approach for standardizing rates utilizing logistic regression models that leads to the enhanced reliability of estimation with reduced calculation cost. Methods: For illustrative purposes, data regarding metabolic syndrome patients in 2013 were extracted from the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS). The detailed step-by-step calculations of age-sex adjusted prevalence rates of metabolic syndrome were demonstrated by both direct and logistic regression standardization approaches whose results were then compared. Results: Standardization of rates using logistic regression models facilitated relatively simple calculation that can be easily implemented by using widely employed analytical programs such as R, SPSS, and SAS. Treating age as a continuous variable, the logistic regression approach produced confidence intervals of age-sex adjusted prevalence rates that were much narrower as compared to confidence intervals obtained by the direct standardization. Conclusions: Standardization of rates utilizing logistic regression models may be a competitive alternative to the direct standardization in terms of computational efficiency and estimation reliability.