Systematic review of research using insurance claim data in Korea




Poster session 3 Friday: Evidence Tools / Evidence synthesis - creation, publication and updating in the digital age


Friday 15 September 2017 - 12:30 to 14:00


All authors in correct order:

Lee H1, Park JH2
1 SNUBH, Korea South
2 NHIS, Korea South
Presenting author and contact person

Presenting author:

Heeyoung Lee

Contact person:

Abstract text
Background: Korean health insurance claim data has accumulated 15 years of medical use data of whole nation. All medicines, procedures and activities are recorded in accordance with fee for service under NHIS (National Health Insurance Service). The health examinations and cancer screening data for all citizens are also included. Recently, a database for research has been established and a variety of big data studies are being conducted.

Objectives: The purpose of this study is to provide a systematic review of the current state of research using the claims data of Korean health insurance.

Methods: We conducted a systematic search using the keyword 'Health insurance' and 'Korea' using Pubmed and 9 Korean literature databases such as Koreamed. Year, disease, theme, research method, and compared the definitions of each variable used in the study.

Results: A total of 1252 papers were selected, published since 1987, and began to increase since 2005, with 289 published in 2016. The most common themes were 123 articles of cancer. Number of articles about infection is 56 and cerebrovascular disease is 52. The study on medical expenses and medical use without disease classification was classified into general health policy and articles about this theme are 232. Patient definition was analysed for cardiovascular disease and varied according to the paper.

Conclusions: There is a lot of research using health insurance data, which makes it possible to do various analyzes with less expense and effort than patient research. However, the problem is that the research method is not standardised and the patient definition is not accurate due to limitations of the claim data. Therefore, if data analysis criteria and precautions are presented by analysing existing research methods and results, it will be possible to improve the quality of research and enhance the utilisation of policies in the future.