背景:真实世界的数据,如索赔,电子病历(EMR),和电子健康记录(EHR),越来越多地用于临床流行病学。了解现有方法的现状可以帮助设计高质量的流行病学研究。
目的:我们进行了全面的叙述性文献综述,以阐明索赔的二次使用,EMR,和EHR在日本的临床流行病学。
方法:我们在PubMed中搜索了2006年1月1日至2021年6月30日(搜索日期)的同行评审出版物,符合以下3个纳入标准:索赔的参与,EMR,EHR,或医疗收据数据;提到日本;并于2006年1月1日至2021年6月30日公布。过滤了符合以下6个排除标准中任何一个的合格文章:评论文章;非疾病相关文章;日本人口不是样本的文章;没有索赔的文章,EMR,或EHR;全文不可用;以及没有统计分析的文章。对标题的调查,摘要,合格文章的全文自动或手动进行,从中收集了7类关键信息。信息包括组织,研究设计,实际数据类型,数据库,疾病,结果,和统计方法。
结果:本叙述性文献综述共确定了620篇合格文章。7个类别的结果表明,大多数研究是由学术机构进行的(n=429);队列研究是纵向测量适当患者结局的主要设计(n=533);594项研究使用索赔数据;数据库的使用集中在著名的商业和公共数据库中;感染(n=105),心血管疾病(n=100),肿瘤(n=78),营养和代谢疾病(n=75)是研究最多的疾病;大多数研究都集中在测量治疗模式(n=218),生理或临床特征(n=184),和死亡率(n=137);和多变量模型是常用的(n=414)。这些多变量建模研究中的大多数(375/414,90.6%)是针对混杂因素调整进行的。Logistic回归是评估许多结果的首选,除住院或住院时间和资源使用或费用外,两者都常用线性回归。
结论:本文献综述提供了对索赔使用现状和趋势的良好理解,EMR,和日本临床流行病学中的EHRs数据。结果显示了关于不同结果的适当统计方法,日本特定的疾病地区趋势,以及现有研究中缺乏对人工智能技术的使用。在未来,将对国内相关研究与世界范围内的研究进行更精确的比较,以阐明日本的具体地位和挑战.
BACKGROUND: Real-world data, such as claims, electronic medical records (EMRs), and electronic health records (EHRs), are increasingly being used in clinical epidemiology. Understanding the current status of existing approaches can help in designing high-quality epidemiological studies.
OBJECTIVE: We conducted a comprehensive narrative literature
review to clarify the secondary use of claims, EMRs, and
EHRs in clinical epidemiology in Japan.
METHODS: We searched peer-reviewed publications in PubMed from January 1, 2006, to June 30, 2021 (the date of search), which met the following 3 inclusion criteria: involvement of claims, EMRs, EHRs, or medical receipt data; mention of Japan; and published from January 1, 2006, to June 30, 2021. Eligible articles that met any of the following 6 exclusion criteria were filtered:
review articles; non-disease-related articles; articles in which the Japanese population is not the sample; articles without claims, EMRs, or EHRs; full text not available; and articles without statistical analysis. Investigations of the titles, abstracts, and full texts of eligible articles were conducted automatically or manually, from which 7 categories of key information were collected. The information included organization, study design, real-world data type, database, disease, outcome, and statistical method.
RESULTS: A total of 620 eligible articles were identified for this narrative literature
review. The results of the 7 categories suggested that most of the studies were conducted by academic institutes (n=429); the cohort study was the primary design that longitudinally measured outcomes of proper patients (n=533); 594 studies used claims data; the use of databases was concentrated in well-known commercial and public databases; infections (n=105), cardiovascular diseases (n=100), neoplasms (n=78), and nutritional and metabolic diseases (n=75) were the most studied diseases; most studies have focused on measuring treatment patterns (n=218), physiological or clinical characteristics (n=184), and mortality (n=137); and multivariate models were commonly used (n=414). Most (375/414, 90.6%) of these multivariate modeling studies were performed for confounder adjustment. Logistic regression was the first choice for assessing many of the outcomes, with the exception of hospitalization or hospital stay and resource use or costs, for both of which linear regression was commonly used.
CONCLUSIONS: This literature
review provides a good understanding of the current status and trends in the use of claims, EMRs, and EHRs data in clinical epidemiology in Japan. The results demonstrated appropriate statistical methods regarding different outcomes, Japan-specific trends of disease areas, and the lack of use of artificial intelligence techniques in existing studies. In the future, a more precise comparison of relevant domestic research with worldwide research will be conducted to clarify the Japan-specific status and challenges.