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      Cohort profile: the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) in Korea

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          Abstract

          Purpose The National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) is a cohort of participants who participated in health screening programmes provided by the NHIS in the Republic of Korea. The NHIS constructed the NHIS-HEALS cohort database in 2015. The purpose of this cohort is to offer relevant and useful data for health researchers, especially in the field of non-communicable diseases and health risk factors, and policy-maker. Participants To construct the NHIS-HEALS database, a sample cohort was first selected from the 2002 and 2003 health screening participants, who were aged between 40 and 79 in 2002 and followed up through 2013. This cohort included 514 866 health screening participants who comprised a random selection of 10% of all health screening participants in 2002 and 2003. Findings to date The age-standardised prevalence of anaemia, diabetes mellitus, hypertension, obesity, hypercholesterolaemia and abnormal urine protein were 9.8%, 8.2%, 35.6%, 2.7%, 14.2% and 2.0%, respectively. The age-standardised mortality rate for the first 2 years (through 2004) was 442.0 per 100 000 person-years, while the rate for 10 years (through 2012) was 865.9 per 100 000 person-years. The most common cause of death was malignant neoplasm in both sexes (364.1 per 100 000 person-years for men, 128.3 per 100 000 person-years for women). Future plans This database can be used to study the risk factors of non-communicable diseases and dental health problems, which are important health issues that have not yet been fully investigated. The cohort will be maintained and continuously updated by the NHIS.

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          Data Resource Profile: The National Health Information Database of the National Health Insurance Service in South Korea

          Data resource basics The National Health Information Database (NHID) is a public database on health care utilization, health screening, socio-demographic variables, and mortality for the whole population of South Korea, formed by the National Health Insurance Service. The population included in the data is over 50 million, and the participation rate in the health screening programs was 74.8% in 2014. The NHID covers data between 2002 and 2014. Those insured by NHI pay insurance contributions and receive medical services from their health care providers. The NHIS, as the single insurer, pays costs based on the billing records of health care providers (Figure 1). To govern and carry out these processes in the NHI, the NHIS built a data warehouse to collect the required information on insurance eligibility, insurance contributions, medical history, and medical institutions. In 2012, the NHIS formed the NHID using information from medical treatment and health screening records and eligibility data from an existing database system. Figure 1. The governance of the National Health Insurance of South Korea. Data collected The eligibility database includes information about income-based insurance contributions, demographic variables, and date of death. The national health screening database includes information on health behaviors and bio-clinical variables. The health care utilization database includes information on records on inpatient and outpatient usage (diagnosis, length of stay, treatment costs, services received) and prescription records (drug code, days prescribed, daily dosage). The long-term care insurance database includes information about activities of daily living and service grades. The health care provider database includes data about the types of institutions, human resources, and equipment. In the NHID, de-identified join keys replacing the personal identifiers are used to interlink these databases. Data resource use Papers published covered various diseases or health conditions like infectious diseases, cancer, cardiovascular diseases, hypertension, diabetes mellitus, and injuries and risk factors such as smoking, alcohol consumption, and obesity. The impacts of health care and public health policies on health care utilization have been also explored since the data include all the necessary information reflecting patterns of health care utilization. Reasons to be cautious First, information on diagnosis and disease may not be optimal for identifying disease occurrence and prevalence since the data have been collected for medical service claims and reimbursement. However, the NHID also collects prescription data with secondary diagnosis, so the accuracy of the disease information can be improved. Second, the data linkage with other secondary national data is not widely available due to privacy issues in Korea. Governmental discussions on the statutory reform of data linkage using the NHID are under way. Collaboration and data access Access to the NHID can be obtained through the Health Insurance Data Service home page (http://nhiss.nhis.or.kr). An ethics approval from the researchers’ institutional review board is required with submission of a study proposal, which is reviewed by the NHIS review committee before providing data. Further inquiries on data use can be obtained by contacting the corresponding author. Funding and competing interests This work was supported by the NHIS in South Korea. The authors declare no competing interests.
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            Cohort Profile: The National Health Insurance Service-National Sample Cohort (NHIS-NSC), South Korea.

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              Fasting serum glucose level and cancer risk in Korean men and women.

              Diabetes is a serious and costly disease that is becoming increasingly common in many countries. The role of diabetes as a cancer risk factor remains unclear. To examine the relationship between fasting serum glucose and diabetes and risk of all cancers and specific cancers in men and women in Korea. Ten-year prospective cohort study of 1,298,385 Koreans (829,770 men and 468,615 women) aged 30 to 95 years who received health insurance from the National Health Insurance Corp and had a biennial medical evaluation in 1992-1995 (with follow-up for up to 10 years). Death from cancer and registry-documented incident cancer or hospital admission for cancer. During the 10 years of follow-up, there were 20,566 cancer deaths in men and 5907 cancer deaths in women. Using Cox proportional hazards models and controlling for smoking and alcohol use, the stratum with the highest fasting serum glucose (> or =140 mg/dL [> or =7.8 mmol/L]) had higher death rates from all cancers combined (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.22-1.37 in men and HR, 1.23; 95% CI, 1.09-1.39 in women) compared with the stratum with the lowest level (<90 mg/dL [<5.0 mmol/L]). By cancer site, the association was strongest for pancreatic cancer, comparing the highest and lowest strata in men (HR, 1.91; 95% CI, 1.52-2.41) and in women (HR, 2.05; 95% CI, 1.43-2.93). Significant associations were also found for cancers of the esophagus, liver, and colon/rectum in men and of the liver and cervix in women, and there were significant trends with glucose level for cancers of the esophagus, colon/rectum, liver, pancreas, and bile duct in men and of the liver and pancreas in women. Of the 26,473 total cancer deaths in men and women, 848 were estimated as attributable to having a fasting serum glucose level of less than 90 mg/dL. For cancer incidence, the general patterns reflected those found for mortality. For persons with a diagnosis of diabetes or a fasting serum glucose level greater than 125 mg/dL (6.9 mmol/L), risks for cancer incidence and mortality were generally elevated compared with those without diabetes. In Korea, elevated fasting serum glucose levels and a diagnosis of diabetes are independent risk factors for several major cancers, and the risk tends to increase with an increased level of fasting serum glucose.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2017
                24 September 2017
                : 7
                : 9
                : e016640
                Affiliations
                [1 ]National Health Insurance Service , Wonju, Korea
                [2 ]departmentBig Data Steering Department , National Health Insurance Service , Wonju, Korea
                [3 ]departmentDepartment of Preventive Medicine , Seoul National University College of Medicine , Seoul, Korea
                [4 ]departmentDepartment of Biomedical Science , Seoul National University College of Medicine , Seoul, Korea
                [5 ]Cancer Research Institute, Seoul National University College of Medicine , Seoul, Korea
                [6 ]departmentDepartment of Health Policy and Management , Seoul National University College of Medicine , Seoul, Korea
                [7 ]Institute of Health Policy and Management, Seoul National University Medical Research Center , Seoul, Korea
                [8 ]departmentDepartment of Preventive Medicine , Yonsei University College of Medicine , Seoul, Korea
                [9 ]departmentGwanak Branch , National Health Insurance Service , Seoul, Korea
                Author notes
                [Correspondence to ] Seung-Lyeal Jeong; sljeong@ 123456nhis.or.kr
                Article
                bmjopen-2017-016640
                10.1136/bmjopen-2017-016640
                5623538
                28947447
                3ae55eca-1d5c-40fb-81ae-554ef6035deb
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 28 February 2017
                : 20 July 2017
                : 26 July 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003646, National Health Insurance Service;
                Categories
                Epidemiology
                Cohort Profile
                1506
                1692
                Custom metadata
                unlocked

                Medicine
                cohort studies,risk factors,national health programs,administrative claims
                Medicine
                cohort studies, risk factors, national health programs, administrative claims

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