PurposeThe National Health Insurance Service (NHIS)-Senior was set up to provide high-quality longitudinal data that can be used to explore various aspects of changes in the socio-economical and health status of older adults, to predict risk factors and to investigate their health outcomes.ParticipantsThe NHIS-Senior cohort, a Korean nationwide retrospective administrative data cohort, is composed of older adults aged 60 years and over in 2002. It consists of 558 147 people selected by 10% simple random sampling method from a total of 5.5 million subjects aged 60+ in the National Health Information Database. The cohort was followed up through 2015 for all subjects, except for those who were deceased.Findings to dateThe healthcare utilisation and admission rates were the highest for acute upper respiratory infections and influenza (75.2%). The age-standardised (defined with reference to the world standard population) mortality rate for 10 years (through 2012) was 4333 per 100 000 person-years. Malignant neoplasms were the most common cause of death in both sexes (1032.1 per 100 000 person-years for men, 376.7 per 100 000 person-years for women). A total of 34 483 individuals applied for long-term care service in 2008, of whom 17.9% were assessed as grade 1, meaning that they were completely dependent on the help of another person to live daily life.Future plansThe data are provided for the purposes of policy and academic research under the Act on Promotion of the Provision and Use of Public Data in Korea. The NHIS-Senior cohort data are only available for Korean researchers at the moment, but it is possible for researchers outside the country to gain access to the data by conducting a joint study with a Korean researcher. The cohort will be maintained and continuously updated by the NHIS.

Background: Mortality of coronavirus disease 2019 (COVID-19) is a major concern for quarantine departments in all countries. This is because the mortality of infectious diseases determines the basic policy stance of measures to prevent infectious diseases. Early screening of high-risk groups and taking action are the basics of disease management. This study examined the correlation of comorbidities on the mortality of patients with COVID-19. Methods: We constructed epidemiologic characteristics and medical history database based on the Korean National Health Insurance Service Big Data and linked COVID-19 registry data of Korea Centers for Disease Control & Prevention (KCDC) for this emergent observational cohort study. A total of 9,148 patients with confirmed COVID-19 were included. Mortalities by sex, age, district, income level and all range of comorbidities classified by International Classification of Diseases-10 based 298 categories were estimated. Results: There were 3,556 male confirmed cases, 67 deaths, and crude death rate (CDR) of 1.88%. There were 5,592 females, 63 deaths, and CDR of 1.13%. The most confirmed cases were 1,352 patients between the ages of 20 to 24, followed by 25 to 29. As a result of multivariate logistic regression analysis that adjusted epidemiologic factors to view the risk of death, the odds ratio of death would be hemorrhagic conditions and other diseases of blood and blood-forming organs 3.88-fold (95% confidence interval [CI], 1.52-9.88), heart failure 3.17-fold (95% CI, 1.88-5.34), renal failure 3.07-fold (95% CI, 1.43-6.61), prostate malignant neoplasm 2.88-fold (95% CI, 1.01-8.22), acute myocardial infarction 2.38-fold (95% CI, 1.03-5.49), diabetes was 1.82-fold (95% CI, 1.25-2.67), and other ischemic heart disease 1.71fold (95% CI, 1.09-2.66). Conclusion: We hope that this study could provide information on high risk groups for preemptive interventions. In the future, if a vaccine for COVID-19 is developed, it is expected that this study will be the basic data for recommending immunization by selecting those with chronic disease that had high risk of death, as recommended target diseases for vaccination.

We constructed the family tree database (DB) by using a new family code system that can logically express interpersonal family relationships and by comparing and complementing health insurance eligibility data and resident register data of the National Health Information Database (NHID). In the family tree DB, Parents and grandparents are matched for more than 95% of those who were born between 2010 and 2017. Codes for inverse relationships and extended relationships are generated using sequences of the three-digit basic family codes. The family tree DB contains variables such as sex, birth year, family relations, and degree of kinship (maximum of 4) between subjects and family members. Using the family tree DB, we find that prevalence rates of hypertension, diabetes, ischemic heart disease, cerebrovascular disease, and cancer are higher for those with family history. The family tree DB may omit some relationships due to incomplete past data, and some family relations cannot be uniquely determined because the source data only contain relationships between head and members of the household. The family tree DB is a part of the NHID, and researchers can submit requests for data on the website at http://nhiss.nhis.or.kr. Requested data will be provided after approval from the data service review board. However, the family tree DB can be limitedly provided for studies with high public value in order to maximize personal information protection.

External quality assessment (EQA) is a commonly used tool to track the performance of laboratory tests. In Korea, EQA participation is not mandatory, and even basic data about EQA participation are not available. We used data of a 10-year period extracted from two databases (2009–2018): (1) the database of the National Health Insurance Service to calculate the number of medical institutions that claimed health insurance benefits, and (2) the database of the Korean Association of External Quality Assessment Service to calculate the number of medical institutions participating in EQA. The proportion of institutions that made claims for the performance of laboratory testing throughout the 10 years were 73.6%–76.0% for clinics, 91.9%–97.5% for long-term care hospitals, 97.9%–99.5% for small to medium hospitals, 99.6%–100% for general hospitals, and 100% for tertiary hospitals. The mean EQA participation rate of institutions that performed laboratory testing for the 10 years was 1.9% for clinics, 3.1% for long-term care hospitals, 27.7% for small to medium hospitals, 96.6% for general hospitals, and 100% for tertiary hospitals. The mean EQA participation of clinics, long-term care hospitals, and small to medium hospitals are increasing but is still not sufficient. Regulatory approaches are needed to increase participation rates. This result would be used for health policymaking on the quality improvement of laboratory tests.

Birthweight is a strong determinant of a neonate’s health. The SARS-CoV-2 pandemic’s impact on birthweight has not been investigated in-depth, with inconsistent conclusions from initial studies. To assess changes in preterm birth and inappropriate birthweight between the SARS-CoV-2 pandemic and pre-pandemic periods. A nationwide birth micro-data consisted with exhaustive census of all births in 2011–2020 in South Korea was accessed to examine whether the mean birthweight and rates of under/overweight births changed significantly during the SARS-CoV-2 pandemic year (2020) compared to those of the pre-pandemic period (2011–2019). A total of 3,736,447 singleton births were analyzed. Preterm birth was defined as < 37 weeks of gestation. Low birthweight (LBW) and macrosomia were defined as birthweights < 2.5 kg and ≥ 4.0 kg, respectively. Small for gestational age (SGA) and large for gestational age (LGA) were defined as birthweights below the 10th and above 90th percentiles for sex and gestational age, respectively. Inappropriate birthweight was defined as one or more LBW, macrosomia, SGA, or LGA. Generalized linear models predicted birth outcomes and were adjusted for parental age and education level, marital status, parity, gestational age, and months from January 2011. There were 3,481,423 and 255,024 singleton births during the pre-pandemic and pandemic periods, respectively. Multivariable generalized linear models estimated negative associations between the pandemic and preterm birth (odds ratio [OR], 0.968; 95% confidence interval [CI] 0.958–0.978), LBW (OR: 0.967, 95% CI 0.956–0.979), macrosomia (OR: 0.899, 95% CI 0.886–0.912), SGA (OR: 0.974, 95% CI 0.964–0.983), LGA (OR: 0.952, 95% CI 0.945–0.959), and inappropriate birthweight (OR: 0.958, 95% CI 0.952–0.963), indicating a decline during the pandemic compared to pre-pandemic period. An 8.98 g decrease in birthweight (95% CI 7.98–9.99) was estimated during the pandemic. This is the largest and comprehensive nationwide study to date on the impact of the SARS-CoV-2 pandemic on preterm birth and inappropriate birthweight. Birth during the pandemic was associated with lower odds of being preterm, underweight, and overweight. Further studies are required to understand the dynamics underlying this phenomenon.