The Current Status of Secondary Use of Claims, Electronic Medical Records, and Electronic Health Records in Epidemiology in Japan: Narrative Literature Review

Abstract

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.