研究背景
失智症並非單一疾病，而是一種以各種認知領域受損為特徵的綜合症，導致患者獨立性和日常功能逐漸下降。過去三十年間，全球失智症各項流行病學數據不斷地攀升。此外，在研究領域中失智相關的研究也逐年增加。台灣自2000年第一篇文章使用我國健保資料為研究資料所進行的發表以來，爾後出版物數量急劇增長，其中以糖尿病，腦中風與失智症是發表主題中頻率最高的三個疾病。然而，在台灣過去二十年間鮮少有失智之疾病擷取之計量學分析與驗證研究。
研究目的
本研究目的為統整2007-2023年使用台灣健保資料庫探討與失智症相關的研究論文，並分析各個研究間失智症個案定義與擷取條件之差異。
研究方法
本研究利用醫學期刊文獻資料庫(PubMed)搜尋出2007年至2023年用台灣健康保險研究資料庫(National Health Insurance Research Database, NHIRD)發表有關失智症的研究，逐一閱讀與篩選後，以研究論文的年代、研究主題、以及期刊影響指數(impact factor, IF)與失智症個案定義作法進行分層分析。
研究結果
失智症的個案定義作法有八大類共三十種，包含了診斷碼、藥物處方紀錄、影像學檢查、臨床量表等。失智症個案定義作法隨著年代有越來越嚴格的趨勢，且達到統計上的顯著差異。多次診斷碼使用比例也越來越高，代表對於使用診斷碼作為失智症個案定義作法越來越受到重視。此外，失智症個案定義作法隨著不同研究主題會有不同的擷取方式。然而，期刊之影響指數與失智症個案定義作法的使用上並未看到統計上的顯著差異。此外，不同失智症個案定義作法估算其失智症盛行率差異甚大，例如：2018年使用第一類1次門診診斷碼作為失智症個案定義作法估計之65歲以上失智症盛行率為63.7‰，然而，我國全國社區失智症流行病學調查結果為79.9‰，若與本研究相比可以發現無論使用何種失智症個案定義作法皆低估其盛行率，尤其是使用第二類1次住院診斷碼以及第七類診斷碼且藥物處方紀錄，其65歲以上失智症盛行率分別為8.3‰和10.4‰。
研究結論
本研究綜觀過去使用健保資料發表與失智症相關的研究論文中，其失智症個案定義作法愈趨於嚴苛，且不同年代與研究主題使用的失智症個案定義作法都有差異。

Background: Dementia is not a single disease but a syndrome characterized by impairments in various cognitive domains, leading to a gradual decline in independence and daily functioning. Over the past three decades, epidemiological data on dementia have shown a significant upward trend globally. In parallel, research on dementia-related topics has steadily increased. Since the publication of the first study using the National Health Insurance Research Database(NHIRD) in 2000, there has been a rapid growth in related publications, with diabetes, stroke, and dementia being the most frequently discussed conditions. However, in Taiwan, there has been a lack of bibliometric analysis and validation studies on dementia over the past two decades. Objectives: This study aims to consolidate research articles published between 2007 and 2023 that utilized NHIRD to explore dementia-related studies and to analyze the variations in algorithms for dementia. Methods: Using the PubMed database, this study identified and screened research articles published from 2007 to 2023 that investigated dementia using NHIRD. Articles were systematically reviewed and analyzed the variations in algorithms for dementia based on publication year, research topics, journal impact factor(IF). Results: Eight categories encompassing 30 different algorithms for dementia, including diagnostic codes, prescription records, imaging examination, and clinical scales. There was a statistically significant trend toward stricter algorithms over time. The use of multiple diagnostic codes has increased, indicating growing recognition of its importance in algorithms for dementia. Additionally, algorithms for dementia varied according to research topics. However, no statistically significant differences were observed between journal IF and the algorithms for dementia. Significant variations in dementia prevalence estimates were found across different algorithms for dementia. For example, using a single outpatient diagnostic code (Category 1) estimated the prevalence of dementia among individuals aged 65 and older at 63.7‰ in 2018, whereas the nationwide community-based epidemiological survey in Taiwan reported a prevalence of 79.9‰. This study found that all algorithms for dementia underestimated dementia prevalence, particularly those using a single inpatient diagnostic code (Category 2) or a combination of diagnostic codes and prescription records (Category 7), which estimated prevalence rates of 8.3‰ and 10.4‰, respectively, for individuals aged 65 and older. Conclusion: This study provides a comprehensive review of dementia-related research using NHIRD, revealing a trend toward increasingly stringent case definition methods over time. Differences in algorithms for dementia were observed across publication years and research topics.

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