analysis was used to determine the relationship between the concentration of each tumor marker and lung cancer diagnosis. The diagnostic efficiencies of tumor markers were evaluated using receiver operating characteristic curve analysis and areas under the curve (AUCs) were calculated. The optimal cut-offs for CYFRA 21-1 and CEA were also estimated.RESULTS: Age, CYFRA 21-1, and CEA concentrations were independently associated with lung cancer diagnosis. Diagnostic efficiency of each tumor marker and its' combination was different according to the histological types of lung cancer. For non-small cell lung cancer, the AUCs for the two-marker combination were the highest: 0.8661 and 0.7559 for total and age-matched controls, respectively. For squamous cell carcinoma, the AUCs for CYFRA 21-1 were the highest: 0.9245 and 0.8428 for total and age-matched controls, respectively. The sensitivity and specificity of CYFRA 21-1 and CEA for lung cancer diagnosis were improved when the cutoffs determined based on this study were applied.CONCLUSIONS: CYFRA 21-1 and CEA could be useful markers for diagnosing lung cancer and single or combination of markers may be useful according to different histological types of lung cancer.]]>
Area Under Curve ; Biomarkers, Tumor ; Carcinoembryonic Antigen ; Carcinoma, Non-Small-Cell Lung ; Carcinoma, Squamous Cell ; Diagnosis ; Keratin-19 ; Lung Neoplasms ; Lung ; Medical Records ; Multivariate Analysis ; Retrospective Studies ; ROC Curve ; Sensitivity and Specificity

BACKGROUND: Although effective care for type 2 diabetes (T2DM) is well known, considerable inadequate care has been still existed. Variations in achievement of the recommended quality indicators inT2DM care among small areas are not well known in Korea. This study examined the quality of care T2DM care and its geographical variations. METHODS: We used the national health insurance database and national health screening database. Seven quality indicators were used to evaluate continuity of care (medication possession ratio), process of care (hemoglobin A1c test, lipid profile, microalbuminuria test, and eye examination), and intermediate outcome (blood pressure control, and low-density lipoprotein control). Crude and age-standardized proportions were calculated for each 252 districts in Korea. RESULTS: All quality indicators failed to achieve the recommended level. Only about 3% and 15% of the patients underwent eye examination and microalbuminuria test, respectively. Other indicators ranged from 48% to 68%. Wide variation in the quality existed among districts and indicators. Eye examination and microalbuminuria test varied the most showing tenfold (0.9%–9.2%) and fourfold (6.3%–28.9%) variation by districts, respectively. There were 32.4 and 42.7 percentage point gap between the best and the worst districts in hemoglobin A1c test and blood pressure control, respectively. CONCLUSION: Considerable proportion of T2DM patients were not adequately managed and quality of care varied substantially district to district. To improve the quality of diabetes care, it is necessary to identify the poor performance areas and establish a well-coordinated care system tailored to the need of the district.
Blood Pressure ; Continuity of Patient Care ; Diabetes Mellitus ; Humans ; Korea ; Lipoproteins ; Mass Screening ; National Health Programs ; Quality of Health Care ; Small-Area Analysis

PURPOSE: We aimed to describe the temporal trends and district-level geographical variations in cancer incidences throughout Korea during 1999-2013. MATERIALS AND METHODS: Data were obtained from the Korean National Cancer Incidence Database. We calculated the age-standardized cumulative cancer incidences according to sex and geographical region (metropolitan cities, provinces, and districts) for three 5-year periods (1999-2003, 2004-2008, and 2009-2013). Each quintile interval contained the same number of regions. Disease maps were created to visualize regional differences in the cancer incidences. RESULTS: Substantial differences in cancer incidences were observed according to district and cancer type. The largest variations between geographical regions were found for thyroid cancer among both men and women. There was little variation in the incidences of stomach, colorectal, and lung cancer according to geographical region. Substantially elevated incidences of specific cancers were observed in Jeollanam-do (thyroid); Daejeon (colorectum); Jeollanam-do, Gyeongsangbuk-do, and Chungcheongbuk-do (lung); Seocho-gu, Gangnam-gu and Seongnam, Bundang-gu (breast and prostate); Chungcheong and Gyeongsang provinces (stomach); Ulleung-gun and the southern districts of Gyeongsangnam-do and Jeollanam-do (liver); and along the Nakdonggang River (gallbladder and biliary tract). CONCLUSION: Mapping regional cancer incidences in Korea allowed us to compare the results according to geographical region. Our results may facilitate the development of infrastructure for systematic cancer incidence monitoring, which could promote the planning and implementation of region-specific cancer management programs.
Chungcheongbuk-do ; Female ; Geographic Locations ; Gyeonggi-do ; Gyeongsangbuk-do ; Gyeongsangnam-do ; Humans ; Incidence* ; Jeollanam-do ; Korea* ; Lung Neoplasms ; Male ; Rivers ; Small-Area Analysis ; Stomach ; Thyroid Neoplasms

OBJECTIVES: The accurate measurement of geographic patterns of health care utilization is a prerequisite for the study of geographic variations in health care utilization. While several measures have been developed to measure how accurately geographic units reflect the health care utilization patterns of residents, they have been only applied to hospitalization and need further evaluation. This study aimed to evaluate geographic indices describing health care utilization. METHODS: We measured the utilization rate and four health care utilization indices (localization index, outflow index, inflow index, and net patient flow) for eight major procedures (coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, surgery after hip fracture, knee replacement surgery, caesarean sections, hysterectomy, computed tomography scans, and magnetic resonance imaging scans) according to three levels of geographic units in Korea. Data were obtained from the National Health Insurance database in Korea. We evaluated the associations among the health care utilization indices and the utilization rates. RESULTS: In higher-level geographic units, the localization index tended to be high, while the inflow index and outflow index were lower. The indices showed different patterns depending on the procedure. A strong negative correlation between the localization index and the outflow index was observed for all procedures. Net patient flow showed a moderate positive correlation with the localization index and the inflow index. CONCLUSIONS: Health care utilization indices can be used as a proxy to describe the utilization pattern of a procedure in a geographic unit.
Angioplasty, Balloon, Coronary ; Arteries ; Cesarean Section ; Delivery of Health Care* ; Female ; Hip ; Hospitalization ; Humans ; Hysterectomy ; Insurance ; Knee ; Korea ; Magnetic Resonance Imaging ; National Health Programs ; Patient Acceptance of Health Care* ; Pregnancy ; Proxy ; Small-Area Analysis ; Transplants

OBJECTIVES: We aimed to evaluate the effect of geographic units of analysis on measuring geographic variation in medical services utilization. For this purpose, we compared geographic variations in the rates of eight major procedures in administrative units (districts) and new areal units organized based on the actual health care use of the population in Korea. METHODS: To compare geographic variation in geographic units of analysis, we calculated the age-sex standardized rates of eight major procedures (coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, surgery after hip fracture, knee-replacement surgery, caesarean section, hysterectomy, computed tomography scan, and magnetic resonance imaging scan) from the National Health Insurance database in Korea for the 2013 period. Using the coefficient of variation, the extremal quotient, and the systematic component of variation, we measured geographic variation for these eight procedures in districts and new areal units. RESULTS: Compared with districts, new areal units showed a reduction in geographic variation. Extremal quotients and inter-decile ratios for the eight procedures were lower in new areal units. While the coefficient of variation was lower for most procedures in new areal units, the pattern of change of the systematic component of variation between districts and new areal units differed among procedures. CONCLUSIONS: Geographic variation in medical service utilization could vary according to the geographic unit of analysis. To determine how geographic characteristics such as population size and number of geographic units affect geographic variation, further studies are needed.
Angioplasty, Balloon, Coronary ; Arteries ; Cesarean Section ; Delivery of Health Care ; Female ; Hip ; Hysterectomy ; Korea ; Magnetic Resonance Imaging ; National Health Programs ; Population Density ; Pregnancy ; Small-Area Analysis ; Transplants

OBJECTIVES: This study shows the issues that should be considered when applying standardized rates using Community Health Survey(CHS) data. METHODS: We analyzed 2008 CHS data. In order to obtain the reliability of standardized rates, we calculated z-score and rank correlation coefficients between direct standardized rate and indirect standardized rate for 31 major indices. Especially, we assessed the change of correlations according to population composition (age and sex), and characteristics of the index. We used Mantel-Haenszel chi-square to quantify the difference of population composition. RESULTS: Among 31 major indices, 29 indices' z-score and rank correlation coefficients were over 0.9. However, regions with larger differences in population composition showed lower reliability. Low reliability was also observed for the indices specific to subgroups with small denominator such as 'permanent lesion from stroke', and the index with large regional variations in age-related differences such as 'obtaining health examinations'. CONCLUSIONS: Standardized rates may have low reliability, if comparison is made between areas with extremely large differences in population composition, or for indicies with large regional variations in age-related differences. Therefore, the special features of standardized rates should be considered when health state are compared among areas.
Adolescent ; Adult ; Age Distribution ; Aged ; Female ; Health Status ; Humans ; Male ; Middle Aged ; Population Surveillance/*methods ; Republic of Korea/epidemiology ; Small-Area Analysis ; Young Adult

OBJECTIVES: This study was performed to compare the standardized mortality ratios among different small areas and to explore the usefulness of standardized mortality ratios in South Korea. METHODS: To calculate the standardized mortality ratio (SMR), we obtained the national deaths certificate data (2004-2006) and national registration population data (2003-2006), and these were provided by the National Statistical Office. The small areas (Eup.Myoun.Dong) were based on the subdivisions of counties. Among the 3,580 small areas classified by the National Statistical Office, 3,571 areas were included in this study. The basic statistics and decile distributions of the SMRs for all the regional levels were calculated, and the small area maps were also produced for some selected regions. To evaluate the precision of SMR, we calculated the 95% confidence intervals of the SMR in selected small areas. RESULTS: The mean and the standard deviation of the SMRs among all small areas were 100.8 and 17.0, respectively. The range was 30.6-211.7 and the inter-quartile range was 20.7. Seoul metropolitan city displayed the lowest mean SMR among 16 regions in South Korea, and 34.6 percent of the small area SMRs belonged to the first decile(the lowest group). On the contrary, the mean SMR of Gyeongsangnam province was highest, and 26.1 percent of the small area SMRs belonged to the tenth decile(the highest group). In some areas, the precision of the SMR, which was calculated by the 95% confidence intervals, remained questionable, yet it was quite stable for almost areas. CONCLUSIONS: The standardized mortality ratios can be useful for allocating health resources at the small area level in Korea.
Death Certificates ; *Healthcare Disparities ; Humans ; Korea/epidemiology ; Mortality/*trends ; Public Health ; *Small-Area Analysis

OBJECTIVES: The principal objective of this study was to determine the relationship between maternal exposure to air pollution and low birth weight and to propose a possible environmental health surveillance system for low birth weight. METHODS: We acquired air monitoring data for Seoul from the Ministry of Environment, the meteorological data from the Korean Meteorological Administration, the exposure assessments from the National Institute of Environmental Research, and the birth data from the Korean National Statistical Office between January 1, 2002 and December 31, 2003. The final birth data were limited to singletons within 37~44 weeks of gestational age. We defined the Low Birth Weight (LBW) group as infants with birth weights of less than 2500g and calculated the annual LBW rate by district. The air monitoring data were measured for CO, SO2, NO2, and PM10 concentrations at 27 monitoring stations in Seoul. We utilized two models to evaluate the effects of air pollution on low birth weight: the first was the relationship between the annual concentration of air pollution and low birth weight (LBW) by individual and district, and the second involved a GIS exposure model constructed by Arc View 3.1. RESULTS: LBW risk (by Gu, or district) was significantly increased to 1.113(95% CI=1.111~1.116) for CO, 1.004 (95% CI=1.003~1.005) for NO2, 1.202(95% CI=1.199~ 1.206) for SO2, and 1.077(95% CI=1.075~1.078) for PM10 with each interquartile range change. Personal LBW risk was significantly increased to 1.081(95% CI=1.002~1.166) for CO, 1.145(95% CI=1.036~1.267) for SO2, and 1.053(95% CI=1.002~1.108) for PM10 with each interquartile range change. Personal LBW risk was increased to 1.003(95% CI=0.954~1.055) for NO2, but this was not statistically significant. The air pollution concentrations predicted by GIS positively correlated with the numbers of low birth weights, particularly in highly polluted regions. CONCLUSIONS: Environmental health surveillance is a systemic, ongoing collection effort including the analysis of data correlated with environmentally-associated diseases and exposures. In addition, environmental health surveillance allows for a timely dissemination of information to those who require that information in order to take effective action. GIS modeling is crucially important for this purpose, and thus we attempted to develop a GIS-based environmental surveillance system for low birth weight.
Air Pollutants/*adverse effects ; Air Pollution/*adverse effects ; Environmental Monitoring/*methods ; Female ; Humans ; *Infant, Low Birth Weight ; Infant, Newborn ; Korea/epidemiology ; Maternal Exposure/*adverse effects ; Pregnancy ; Small-Area Analysis

This study aims to find factors that affect variations in cesarean section frequency rates among OBGY clinics in Metropolitan areas. The factors include patient, medical supplier characteristics and economic factors. This study is a cross-sectional analysis using health insurance delivery claims from July to December 2000 and files of the NHIC(national health insurance corporation). Multiple regression was used to analyze the dependent variable of cesarean section frequency rate at each clinic. The results are as follows : Cesarean section frequency rate is increasing in proportion to the number of the following patients : repeated caesarean section, disproportion, obstructed labour, fetal distress, emergency caesarean section and self-employed patients. There are geographic variations as well. Cesarean section frequency rates are higher in Inchon and Gyonggi province than in Seoul. The higher number of total delivery the clinic has, the lower rate of cesarean section it has. Clinics with high frequency rates in 1999 showed higher rates the next year. Further research is required to develop evidence based delivery modes and change strategies for increasing normal delivery and activating midwife clinics.
Cesarean Section* ; Cross-Sectional Studies ; Emergencies ; Female ; Fetal Distress ; Humans ; Incheon ; Insurance, Health ; Midwifery ; Pregnancy ; Seoul ; Small-Area Analysis

OBJECTIVES: The Study of Small Area Variation(SAV) is most interesting issue in the health care researches. Most studies of SAV have been concluded the existences of variation on the basis of the magnitude of variation without statistical testing. But it is difficult to explain the existence of variation with this way because variation indicies are easily influenced by several parameters and also their distribution are skewed. So, it needs for the study to investigate the distribution of these indices and develop the statistical testing model. METHODS: This study was planned to analyze on the distribution of variation indices such as Extremal Quotient(EQ), Coefficient of Variation(CV), Systematic Component of Variation(SCV) and compare the statistical power among indicies. The simulations was performed on the basis of several assumptions and compared to the empirical data. RESULTS: Main findings can be summarized as follows. 1. If other conditions are constant, the more number of regions, the larger 95 percentile of EQ. But under same situation, 95 percentile of CV and SCV were slightly decreased. 2. If the size of regional population or utilization rate were increased, 95 percentile of all statistics were decreased. Also in the cases of small population size and low utilization rate, 95 percentiles of EQ showed various change contrast to the little change of CV. 3. If the difference at the size of regional population were increased, 95 percentiles of EQ and SCV were increased contrast to the little difference of CV 4. If the utilization rate were increased, 95 percentiles of all indicies were increased. But under the same difference of utilization rate, the power of CV and SCV were increased comparing to no change of the power of EQ. 5. Usually the power of EQ were lower than that of CV or SCV and it is similar between CV and SCV. CONCLUSIONS: Therefore, we suggest that in selecting the variation indicies at the SAV, CV or SCV are superior than EQ in terms of significance level and power.
Health Services Research ; Population Density ; Small-Area Analysis* ; Statistical Distributions*