Estimating Baseline Incidence of Conditions Potentially Associated with Vaccine Adverse Events: a Call for Surveillance System Using the Korean National Health Insurance Claims Data

Background@#Vaccines against coronavirus disease 2019 (COVID-19) are raising concerns about vaccine safety, particularly in the context of large-scale immunization. To address public concerns, we measured the baseline incidence rates of major conditions potentially related to vaccine-related adverse events (VAEs). We aimed to provide a basis for evaluating VAEs and verifying causality. @*Methods@#Conditions of interest were selected from the US Vaccine Adverse Event Reporting System Table of Reportable Events and a recent report from a European consortium on vaccine surveillance. We used the National Health Insurance Service database in Korea to identify the monthly numbers of cases with these conditions. Data from January 2006 to June 2020 were included. Prediction models were constructed from the observed incidences using an autoregressive integrated moving average. We predicted the incidences of the conditions and their respective 95% confidence intervals (CIs) for January through December 2021. In addition, subgroup analysis for the expected vaccination population was conducted. @*Results@#Mean values (95% CIs) of the predicted monthly incidence of vasovagal syncope, anaphylaxis, brachial neuritis, acute disseminated encephalomyelitis, Bell's palsy, Guillain-Barré syndrome, encephalopathy, optic neuritis, transverse myelitis, immune thrombocytopenic purpura, and systemic lupus erythematosus in 2021 were 23.89 (19.81– 27.98), 4.72 (3.83–5.61), 57.62 (51.37–63.88), 0.03 (0.01–0.04), 8.58 (7.90–9.26), 0.26 (0.18– 0.34), 2.13 (1.42–2.83), 1.65 (1.17–2.13), 0.19 (0.14–0.25), 0.75 (0.61–0.90), and 3.40 (2.79– 4.01) cases per 100,000 respectively. The majority of the conditions showed an increasing trend with seasonal variations in their incidences. @*Conclusion@#We measured the incidence of a total of 11 conditions that could potentially be associated with VAEs to predict the monthly incidence in 2021. In Korea, conditions that could potentially be related to VAEs occur on a regular basis, and an increasing trend is observed with seasonality.

Estimating Baseline Incidence of Conditions Potentially Associated with Vaccine Adverse Events: a Call for Surveillance System Using the Korean National Health Insurance Claims Data

Background@#Vaccines against coronavirus disease 2019 (COVID-19) are raising concerns about vaccine safety, particularly in the context of large-scale immunization. To address public concerns, we measured the baseline incidence rates of major conditions potentially related to vaccine-related adverse events (VAEs). We aimed to provide a basis for evaluating VAEs and verifying causality. @*Methods@#Conditions of interest were selected from the US Vaccine Adverse Event Reporting System Table of Reportable Events and a recent report from a European consortium on vaccine surveillance. We used the National Health Insurance Service database in Korea to identify the monthly numbers of cases with these conditions. Data from January 2006 to June 2020 were included. Prediction models were constructed from the observed incidences using an autoregressive integrated moving average. We predicted the incidences of the conditions and their respective 95% confidence intervals (CIs) for January through December 2021. In addition, subgroup analysis for the expected vaccination population was conducted. @*Results@#Mean values (95% CIs) of the predicted monthly incidence of vasovagal syncope, anaphylaxis, brachial neuritis, acute disseminated encephalomyelitis, Bell's palsy, Guillain-Barré syndrome, encephalopathy, optic neuritis, transverse myelitis, immune thrombocytopenic purpura, and systemic lupus erythematosus in 2021 were 23.89 (19.81– 27.98), 4.72 (3.83–5.61), 57.62 (51.37–63.88), 0.03 (0.01–0.04), 8.58 (7.90–9.26), 0.26 (0.18– 0.34), 2.13 (1.42–2.83), 1.65 (1.17–2.13), 0.19 (0.14–0.25), 0.75 (0.61–0.90), and 3.40 (2.79– 4.01) cases per 100,000 respectively. The majority of the conditions showed an increasing trend with seasonal variations in their incidences. @*Conclusion@#We measured the incidence of a total of 11 conditions that could potentially be associated with VAEs to predict the monthly incidence in 2021. In Korea, conditions that could potentially be related to VAEs occur on a regular basis, and an increasing trend is observed with seasonality.

Comparison of District-level Smoking Prevalence and Their Income Gaps from Two National Databases: the National Health Screening Database and the Community Health Survey in Korea, 2009–2014

BACKGROUND: We compared age-standardized prevalence of cigarette smoking and their income gaps at the district-level in Korea using the National Health Screening Database (NHSD) and the Community Health Survey (CHS). METHODS: Between 2009 and 2014, 39,049,485 subjects participating in the NHSD and 989,292 participants in the CHS were analyzed. The age-standardized prevalence of smoking and their interquintile income differences were calculated for 245 districts of Korea. We examined between-period correlations for the age-standardized smoking prevalence at the district-level and investigated the district-level differences in smoking prevalence and income gaps between the two databases. RESULTS: The between-period correlation coefficients of smoking prevalence for both genders were 0.92–0.97 in NHSD and 0.58–0.69 in CHS, respectively. When using NHSD, we found significant income gaps in all districts for men and 244 districts for women. However, when CHS was analyzed, only 167 and 173 districts for men and women, respectively, showed significant income gaps. While correlation coefficients of district-level smoking prevalence from two databases were 0.87 for men and 0.85 for women, a relatively weak correlation between income gaps from the two databases was found. CONCLUSION: Based on two databases, income gaps in smoking prevalence were evident for nearly all districts of Korea. Because of the large sample size for each district, NHSD may provide stable district-level smoking prevalence and its income gap and thus should be considered as a valuable data source for monitoring district-level smoking prevalence and its socioeconomic inequality.

Prevalence of Overweight and Income Gaps in 245 Districts of Korea: Comparison Using the National Health Screening Database and the Community Health Survey, 2009–2014

BACKGROUND: We compared age-standardized overweight prevalence and their income gaps at the level of district in Korea using the National Health Screening Database (NHSD) and the Community Health Survey (CHS). METHODS: We analyzed 39,093,653 subjects in the NHSD and 926,580 individuals in the CHS between 2009 and 2014. For the comparison of body mass index (BMI) distributions, data from 26,100 subjects in the Korea National Health and Nutrition Examination Survey (KNHANES) were also analyzed. We calculated the age-standardized overweight prevalence and its interquintile income gap at the district level. We examined the magnitudes of the between-period correlation for age-standardized overweight prevalence. The differences in overweight prevalence and its income gap between the NHSD and the CHS were also investigated. RESULTS: The age-adjusted mean BMI from the CHS was lower than those from the NHSD and the KNHANES. The magnitudes of the between-period correlation for overweight prevalence were greater in the NHSD compared to the CHS. We found that the district-level overweight prevalence in the NHSD were higher in all districts of Korea than in the CHS. The correlation coefficients for income gaps in overweight prevalence between the two databases were relatively low. In addition, when using the NHSD, the district-level income inequalities in overweight were clearer especially among women than the inequalities using the CHS. CONCLUSION: The relatively large sample size for each district and measured anthropometric data in the NHSD are more likely to contribute to valid and reliable measurement of overweight inequality at the district level in Korea.

Level of Agreement and Factors Associated With Discrepancies Between Nationwide Medical History Questionnaires and Hospital Claims Data / 예방의학회지

OBJECTIVES: The objectives of this study were to investigate the agreement between medical history questionnaire data and claims data and to identify the factors that were associated with discrepancies between these data types. METHODS: Data from self-reported questionnaires that assessed an individual's history of hypertension, diabetes mellitus, dyslipidemia, stroke, heart disease, and pulmonary tuberculosis were collected from a general health screening database for 2014. Data for these diseases were collected from a healthcare utilization claims database between 2009 and 2014. Overall agreement, sensitivity, specificity, and kappa values were calculated. Multiple logistic regression analysis was performed to identify factors associated with discrepancies and was adjusted for age, gender, insurance type, insurance contribution, residential area, and comorbidities. RESULTS: Agreement was highest between questionnaire data and claims data based on primary codes up to 1 year before the completion of self-reported questionnaires and was lowest for claims data based on primary and secondary codes up to 5 years before the completion of self-reported questionnaires. When comparing data based on primary codes up to 1 year before the completion of self-reported questionnaires, the overall agreement, sensitivity, specificity, and kappa values ranged from 93.2 to 98.8%, 26.2 to 84.3%, 95.7 to 99.6%, and 0.09 to 0.78, respectively. Agreement was excellent for hypertension and diabetes, fair to good for stroke and heart disease, and poor for pulmonary tuberculosis and dyslipidemia. Women, younger individuals, and employed individuals were most likely to under-report disease. CONCLUSIONS: Detailed patient characteristics that had an impact on information bias were identified through the differing levels of agreement.

Using the National Health Information Database of the National Health Insurance Service in Korea for Monitoring Mortality and Life Expectancy at National and Local Levels

This study explores whether the National Health Information Database (NHID) can be used to monitor health status of entire population in Korea. We calculated the crude mortality rate and life expectancy (LE) at birth across the national, provincial, and municipal levels using the NHID eligibility database from 2004 to 2015, and compared the results with the corresponding values obtained from the Korean Statistical Information Service (KOSIS) of Statistics Korea. The study results showed that the ratio of crude mortality rate between the two data was 0.99. The absolute difference between the LE of the two data was not more than 0.5 years, and did not exceed 0.3 years in gender specific results. The concordance correlation coefficients (CCC) between the crude mortality rates from NHID and the rates from KOSIS ranged 0.997–0.999 among the municipalities. For LE, the CCC between the NHID and KOSIS across the municipalities were 0.990 in 2004–2009 and 0.985 in 2010–2015 among men, and 0.952 in 2004–2009 and 0.914 in 2010–2015 among women, respectively. Overall, the NHID was a good source for monitoring mortality and LE across national, provincial, and municipal levels with the population representativeness of entire Korean population. The results of this study indicate that NHID may well contribute to the national health promotion policy as a part of the health and health equity monitoring system.

Effects of Diabetic Case Management on Knowledge, Self-Management Abilities, Health Behaviors, and Health Service Utilization for Diabetes in Korea

PURPOSE: This study aimed to evaluate the effects of a case management program for diabetics, using a pre-post comparison design. MATERIALS AND METHODS: The study population comprised 6007 diabetics who received case management intervention in 2006 and were sampled nationwide in Korea. Before and after the intervention, the study population answered questions regarding their knowledge of diabetes, self-management ability, and health behaviors. Body mass index (BMI) was also calculated. Healthcare service utilization for diabetes was extracted from health insurance claim data from 2005 to 2007. RESULTS: The case management program significantly improved the study population's knowledge of diabetes and ability to self-manage nutrition, blood glucose monitoring, foot and oral care, and medications. This program also significantly changed the study population's health behaviors regarding smoking, alcohol drinking, and exercise, and BMI was positively affected. In the over-serviced subgroup, there was a significant decrease in the number of consultations (mean=7.0; SD=19.5) after intervention. Conversely, in the under-serviced subgroup, there was a significant increase in the number of consultations (mean=3.2; SD=7.9) and the days of prescribed medication (mean=66.4; SD=120.3) after intervention. CONCLUSION: This study showed that the case management program led the study population to improve their knowledge, self-management ability, health behaviors, and utilization of health care. It is necessary in future studies to evaluate the appropriateness of healthcare usage and clinical outcome by using a control group to determine the direct effectiveness of this case management program.

Effects of Hospital Nurse Staffing on in-hospital Mortality, Pneumonia, Sepsis, and Urinary Tract Infection in Surgical Patients

PURPOSE: This study was done to examine relationships between nurse staffing level and postsurgical patient outcomes using inpatient database from the National Health Insurance. METHODS: Records of 111,491 patients who received one of 12 types of surgery between January and December, 2009 were identified and analyzed in this study. Nurse staffing level was measured using adjusted nurse staffing grades from 0 to 7. Patient outcomes were defined as in-hospital mortality, or pneumonia, sepsis, or urinary tract infection after surgery. Logistic regression analyses estimated by Generalized Estimation Model, were used to analyze the association between nurse staffing level and patient outcomes. RESULTS: An inverse relationship was found between nurse staffing and patient mortality. Compared with patients who were cared for in hospitals with the highest nurse staffing (Grades 0-1), increases in the odds of dying were found in those with Grades 6-7 [OR (odds ratio)=2.99, 95% CI (confidence interval)=1.94-4.60], those with Grades 4-5 (OR=1.78, 95% CI=1.24-2.57) and those with Grades 2-3 (OR=1.57, 95% CI=1.25-1.98). Lower nurse staffing level was also associated with higher number of cases in pneumonia and sepsis. CONCLUSION: Policies for providing adequate nurse staffing is required to enhance quality of care and lead to better perioperative patient outcomes.

Current Status and Reasons for the Location Change of Primary Medical Institutions in Korea / 예방의학회지

OBJECTIVES: To understand the current status of the opening, closing and relocation of primary medical institutes in Korea and identify the underlying decision factors. METHODS: Sources of analyzed data included the medical institutional master file at the National Health Insurance Corporation (1998, 2000) and Regional Statistic Annual Bulletins. To investigate changes including the opening, closing and relocation, a total of primary medicalinstitutions (16,757 in 1998, 19,267 in 2000) were analysed. RESULTS: Between 1998 and 2000, there was a 15.0% (2,510) increase in the number of primary medical institutions and the rate of increase in the rural area was higher than the urban area, and higher for specialty clinics than primary practice. However, these findings did not suggestany improvement in the maldistribution of primary medical institutions. During the time period studied, newly opened and closed primary medical institutions numbered 4,085 and 1,573, respectively. Additionally, institutions thatrelocated numbered 2,729, or 16.3%of all primary medical institutions in operation in 1998. These openings and closings were more frequent among young doctors. As a result of our analysis on the underlying regional factors forrelocation, the factors that were statistically significant were local per capita tax burden and the number of schools per ten thousand persons. In the case of institutional factors, movements were significantly associated with gender and the location of primary medical institutions. CONCLUSIONS: In order to establish effective long-term intervention for primary medical institutions, further study and monitoring of primary medical institutions and the dentification of factors influencing opening location and relocation is necessary.