運用健保研究資料庫進行之第二型糖尿病研究趨勢分析：以PubMed資料庫之期刊文獻為例

Observational Researches of Type II Diabetes Mellitus using Taiwan's National Health Insurance Research Database: Literature Review Adopted from PubMed Database

10.6338/JDA.201512_10(6).0001

楊雅婷(Ya-Ting Yang)；王敬蓉(Ching-Jung Wang)；葉玲瓏(Ling-Long Ye):許怡欣(Yi-Hsin Elsa Hsu)

健保資料庫 ； 第二型糖尿病 ； National Health Insurance Research Database ； Type II Diabetes ； PubMed regression ； machine learning

Journal of Data Analysis

10卷6期（2015 / 12 / 01）

1 - 26

繁體中文

糖尿病是全球公共衛生所關注的慢性病，第二型糖尿病約佔其中90%，也是醫藥衛生常見的研究主題。台灣健保資料庫分析的研究持續在國際期刊發表，幫助我們更了解許多重大疾病的流行病學與治療型態，其中也包含了第二型糖尿病。本研究透過PubMed資料庫，搜尋運用健保資料庫分析的第二型糖尿病文獻並整理相關資訊，以掌握目前的研究趨勢。本研究主要以第二型糖尿病MeSH標題詞彙加上全民健保研究資料庫(national health insurance research database)條件進行篩選。文獻搜尋的時間為2000至2015年六月底。在23篇納入評析的研究中，世代研究佔最多數，主要的研究依變項為第二型糖尿病、心血管疾病、癌症與失智問題，最常見的自變項為長期服藥的影響，包含抗憂鬱劑、降血糖藥物等，主要控制變項，以年齡、性別、共病症等為可能的干擾因子，這些研究發現有助於第二型糖尿病的預防與管理。未來研究可考慮特定的次族群分析，或利用資料庫映射方式增加可用變項，盼能為第二型糖尿病找出更多預防與管理的醫藥保健策略。

Diabetes is one of leading chronic disease of global public health concerns. Type II diabetes (T2DM) account for 90% of diabetes population and become popular medical or health care research issue. As more researches using Taiwan's National Health Insurance Research Database (NHIRD) published in peer-reviewed journals, it helps us to realize the epidemiology and treatment pattern of major diseases, including T2DM. In order to capture the recent research trends of this topic, we attempted to use PubMed as database platform to search for relevant studies of T2DM using NHIRD. This study used type II diabetes with NHI Research Database as MeSH title as keywords. Timeframe of literature search was from 2000 till the end of June 2015. A total of 23 studies were eligible for evaluation, and most of them were cohort studies in design. The major dependent variables included T2DM, cardiovascular events, cancers, and dementia-related disease. The most frequently studied independent variables were those related to long-term medication. The control variables included age, sex, comorbidities, which were possible confounding factors. These findings are beneficial to disease prevention and management. Further studies might consider specific subgroup analysis, or analyze more useful variables by database mapping, to provide more insights for developing preventive and administrative strategies for T2DM.

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