Dataset Information

Introducing big data analysis using data from National Health Insurance Service.

ABSTRACT: Among the different providers of health care big data in Korea, the data provided by the National Health Insurance Database include the medical information of all the citizens who have subscribed to medical insurance. As such, the data have representativeness and completeness. In order to conduct research using these National Health Insurance Database data, it is necessary to understand the characteristics of the claim data to avoid various biases, and to control confounding variables when making various operational definitions in the planning stage of the research. Moreover, without a proper understanding of the big data, it is possible during the analysis and data interpretation to mistakenly interpret the correlation between variables as a causal relationship. Therefore, in order to help advanced medical science, which reflects the medical reality such as medical expenses and number of hospital visits by clearly recognizing and analyzing the characteristics and limitations of health care big data, this author has dealt with the use of data sharing services provided by the National Health Insurance Database.

SUBMITTER: Ahn E

PROVIDER: S-EPMC7280883 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Introducing big data analysis using data from National Health Insurance Service.

Ahn EunJin E

Korean journal of anesthesiology 20200513 3

Among the different providers of health care big data in Korea, the data provided by the National Health Insurance Database include the medical information of all the citizens who have subscribed to medical insurance. As such, the data have representativeness and completeness. In order to conduct research using these National Health Insurance Database data, it is necessary to understand the characteristics of the claim data to avoid various biases, and to control confounding variables when makin ...[more]

PMID: 32506896

Similar Datasets

Project description:ObjectivesTo analyse the relationship between health need, insurance coverage, health service availability, service use, insurance claims and out-of-pocket spending on health across Indonesia.DesignSecondary analysis of nationally representative quantitative data. We merged four national data sets: the National Socioeconomic Survey 2018, National Census of Villages 2018, Population Health Development Index 2018 and National Insurance Records to end 2017. Descriptive analysis and linear regression were performed.SettingIndonesia has one of the world's largest single-payer national health insurance schemes. Data are individual and district level; all are representative for each of the country's 514 districts.ParticipantsAnonymised secondary data from 1 131 825 individual records in the National Socioeconomic Survey and 83 931 village records in the village census. Aggregate data for 220 million insured citizens.Primary outcome measuresHealth service use and out-of-pocket payments, by health need, insurance status and service availability. Secondary outcome: insurance claims.ResultsSelf-reported national health insurance registration (60.6%) is about 10% lower compared with the insurer's report (71.1%). Insurance coverage is highest in poorer areas, where service provision, and thus service use and health spending, are lowest. Inpatient use is higher among the insured than the uninsured (OR 2.35, 95% CI 2.27 to 2.42), controlling for health need and access), and poorer patients are most likely to report free inpatient care (53% in wealth quintile 1 vs 41% in Q5). Insured patients spend US$ 3.14 more on hospitalisation than the uninsured (95% CI 1.98 to 4.31), but the difference disappears when controlled for wealth. Lack of services is a major constraint on service use, insurance claims and out-of-pocket spending.ConclusionsThe Indonesian public insurance system protects many inpatients, especially the poorest, from excessive spending. However, others, especially in Eastern Indonesia cannot benefit because few services are available. To achieve health equity, the Indonesian government needs to address supply side constraints and reduce structural underfunding.

Project description:ObjectivesDementia is common in people over the age of 65 years, with 80% of people with dementia older than 75 years. Previous studies have linked dementia to late-life depression, but the association between dementia and mid-life depression is poorly understood. Depression is a preventable and treatable medical condition, which means it is a modifiable factor that can potentially prevent or delay dementia. This study aimed to identify the association between dementia and depression within the life course.DesignA nationwide, retrospective propensity score matched cohort study associating dementia with depression. Depression diagnosed between the ages of 45 and 64 years was classified as 'mid-life' and 'late-life' if diagnosed at 65 years or older. Patients were considered to have depression when one or more International Statistical Classification of Diseases and Related Health Problems, 10th revision codes for depression were recorded as primary or secondary diagnosis.SettingNational Health Insurance Service-National Sample Cohort database of the National Health Insurance Service in South Korea, containing patient data from 2002 to 2013.ParticipantsThe study included 1824 and 374 852 patients in the case and control groups, respectively. A logistic regression analysis with complex sampling design was performed after adjusting for covariates, using the propensity score matching method without callipers, with a 1:1 nearest neighbour matching algorithm.Primary and secondary outcome measuresThe association of mid-onset and late-onset depression with dementia in terms of sociodemographic characteristics, such as sex and age, within the Korean population.ResultsDementia was significantly associated with the presence of depression (OR=2.20, 95% CI=1.53-3.14); in particular, female patients with depression and patients aged 45-64 years with depression had increased odds of dementia (OR=2.65, 95% CI=1.78-3.93 and OR=2.72, 95% CI=1.41-5.24, respectively) CONCLUSION: Depression is an associated factor for dementia, especially among people aged 45-64 years (mid-life).

Project description:BackgroundStudies using Taiwan's National Health Insurance (NHI) claims data have expanded rapidly both in quantity and quality during the first decade following the first study published in 2000. However, some of these studies were criticized for being merely data-dredging studies rather than hypothesis-driven. In addition, the use of claims data without the explicit authorization from individual patients has incurred litigation.ObjectiveThis study aimed to investigate whether the research output during the second decade after the release of the NHI claims database continues growing, to explore how the emergence of open access mega journals (OAMJs) and lawsuit against the use of this database affect the research topics and publication volume and to discuss the underlying reasons.MethodsPubMed was used to locate publications based on NHI claims data between 1996 and 2017. Concept extraction using MetaMap was employed to mine research topics from article titles. Research trends were analyzed from various aspects, including publication amount, journals, research topics and types, and cooperation between authors.ResultsA total of 4473 articles were identified. A rapid growth in publications was witnessed from 2000 to 2015, followed by a plateau. Diabetes, stroke, and dementia were the top 3 most popular research topics whereas statin therapy, metformin, and Chinese herbal medicine were the most investigated interventions. Approximately one-third of the articles were published in open access journals. Studies with two or more medical conditions, but without any intervention, were the most common study type. Studies of this type tended to be contributed by prolific authors and published in OAMJs.ConclusionsThe growth in publication volume during the second decade after the release of the NHI claims database was different from that during the first decade. OAMJs appeared to provide fertile soil for the rapid growth of research based on NHI claims data, in particular for those studies with two or medical conditions in the article title. A halt in the growth of publication volume was observed after the use of NHI claims data for research purposes had been restricted in response to legal controversy. More efforts are needed to improve the impact of knowledge gained from NHI claims data on medical decisions and policy making.

Dataset Information

Introducing big data analysis using data from National Health Insurance Service.

Publications

Introducing big data analysis using data from National Health Insurance Service.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets