Affecting Factors of Secondhand Smoke Exposure in Korea: Focused on Different Exposure Locations

Exposure to secondhand smoke (SHS) not only can cause serious illness, but is also an economic and social burden. Contextual and individual factors of non-smoker exposure to SHS depend on location. However, studies focusing on this subject are lacking. In this study, we described and compared the factors related to SHS exposure according to location in Korea. Regarding individual factors related to SHS exposure, a common individual variable model and location-specific variable model was used to evaluate SHS exposure at home/work/public locations based on sex. In common individual variables, such as age, and smoking status showed different relationships with SHS exposure in different locations. Among home-related variables, housing type and family with a single father and unmarried children showed the strongest positive relationships with SHS exposure in both males and females. In the workplace, service and sales workers, blue-collar workers, and manual laborers showed the strongest positive association with SHS exposure in males and females. For multilevel analysis in public places, only SHS exposure in females was positively related with cancer screening rate. Exposure to SHS in public places showed a positive relationship with drinking rate and single-parent family in males and females. The problem of SHS embodies social policies and interactions between individuals and social contextual factors. Policy makers should consider the contextual factors of specific locations and regional and individual context, along with differences between males and females, to develop effective strategies for reducing SHS exposure.

Egalitarian Health Policy Preference and Its Related Factors in Korea: National Representative Sample Survey

Recently in Korea, the commercialization of health services has come to the fore, and the issue of egalitarianism/universal coverage in health is a matter for debate. This study explored the extent of Korean citizen's preference for egalitarian health policies focusing on the provision of health care service, financing and related factors. The data came from the 2011 Korean General Social Survey (KGSS) and the International Social Survey Program (ISSP). The preference for an egalitarian health policy (dependent variable) was divided into a preference for an egalitarian health services provision (ES) and a willingness to contribute (WC) to it. Each index was linearly regressed with demographic factors, socioeconomic status, ideology, and health-related factors. ES was significantly associated with an individual's egalitarianism and political liberalism, having illness/disability, having no additional private health insurance, and their perception of health insurance coverage. WC was associated with age, sex, household income, education, egalitarianism, and their perception of health insurance coverage. There were evidently different factors between ES and WC, mainly socioeconomic factors. WC was strongly influenced by socioeconomic status, whereas ES seemed to be linked more closely to economic affordability. Moreover, the results showed that Korean citizens prefer ES but do not like WC. These results deserve great attention, and the authorities should keep it in perspective. If the government wants to make a successful attempt to change the healthcare system through public policy, it will need to take public preferences into account.

Individual and Socioeconomic Contextual Effects on Depressive Symptom in Korea: Multilevel Analysis of Cross-sectional Nationwide Survey

This study was aimed to examine the relationship between individual, socioeconomic context and depressive symptom among Korean population. Data were the Korean Community Health Survey (KCHS), a nationwide survey collected from 253 local communities including 230,715 adults aged 19 yr or over. To identify depressive symptom, the Center for Epidemiologic Studies Depression scale (CES-D) was used. This study employed multilevel logistic regression to analyze the hierarchical data that included individual and community level variables. The results of this study showed that people in the highest level of community income had a higher risk of depressive symptom compared with people in the lowest (OR, 1.6; 95% CI, 1.4-1.9). In a chi-square test for trend, the prevalence of depressive symptom was significantly increased with increased level of community income among all groups of the family income (P<0.001). Moreover a significant interaction was found between household income and community mean income (OR, 0.98; 95% CI, 0.97-0.99). Among individual level variables, age, sex, education, income, living alone, and the number of illnesses were associated with depressive symptom. This study identified that the level of community income has an inverse association, and its effect is especially stronger among low income individuals.

Individual and Socioeconomic Contextual Effects on Depressive Symptom in Korea: Multilevel Analysis of Cross-sectional Nationwide Survey

This study was aimed to examine the relationship between individual, socioeconomic context and depressive symptom among Korean population. Data were the Korean Community Health Survey (KCHS), a nationwide survey collected from 253 local communities including 230,715 adults aged 19 yr or over. To identify depressive symptom, the Center for Epidemiologic Studies Depression scale (CES-D) was used. This study employed multilevel logistic regression to analyze the hierarchical data that included individual and community level variables. The results of this study showed that people in the highest level of community income had a higher risk of depressive symptom compared with people in the lowest (OR, 1.6; 95% CI, 1.4-1.9). In a chi-square test for trend, the prevalence of depressive symptom was significantly increased with increased level of community income among all groups of the family income (P<0.001). Moreover a significant interaction was found between household income and community mean income (OR, 0.98; 95% CI, 0.97-0.99). Among individual level variables, age, sex, education, income, living alone, and the number of illnesses were associated with depressive symptom. This study identified that the level of community income has an inverse association, and its effect is especially stronger among low income individuals.

Data Mining Application in Customer Relationship Management for Hospital Inpatients / 대한의료정보학회지

OBJECTIVES: This study aims to discover patients loyal to a hospital and model their medical service usage patterns. Consequently, this study proposes a data mining application in customer relationship management (CRM) for hospital inpatients. METHODS: A recency, frequency, monetary (RFM) model has been applied toward 14,072 patients discharged from a university hospital. Cluster analysis was conducted to segment customers, and it modeled the patterns of the loyal customers' medical services usage via a decision tree. RESULTS: Patients were divided into two groups according to the variables of the RFM model and the group which had significantly high frequency of medical use and expenses was defined as loyal customers, a target market. As a result of the decision tree, the predictable factors of the loyal clients were; length of stay, certainty of selectable treatment, surgery, number of accompanying treatments, kind of patient room, and department from which they were discharged. Particularly, this research showed that when a patient within the internal medicine department who did not have surgery stayed for more than 13.5 days, their probability of being a classified as a loyal customer was 70.0%. CONCLUSIONS: To discover a hospital's loyal patients and model their medical usage patterns, the application of data-mining has been suggested. This paper suggests practical use of combining segmentation, targeting, positioning (STP) strategy and the RFM model with data-mining in CRM.

Selecting the Best Prediction Model for Readmission / 예방의학회지

OBJECTIVES: This study aims to determine the risk factors predicting rehospitalization by comparing three models and selecting the most successful model. METHODS: In order to predict the risk of rehospitalization within 28 days after discharge, 11 951 inpatients were recruited into this study between January and December 2009. Predictive models were constructed with three methods, logistic regression analysis, a decision tree, and a neural network, and the models were compared and evaluated in light of their misclassification rate, root asymptotic standard error, lift chart, and receiver operating characteristic curve. RESULTS: The decision tree was selected as the final model. The risk of rehospitalization was higher when the length of stay (LOS) was less than 2 days, route of admission was through the out-patient department (OPD), medical department was in internal medicine, 10th revision of the International Classification of Diseases code was neoplasm, LOS was relatively shorter, and the frequency of OPD visit was greater. CONCLUSIONS: When a patient is to be discharged within 2 days, the appropriateness of discharge should be considered, with special concern of undiscovered complications and co-morbidities. In particular, if the patient is admitted through the OPD, any suspected disease should be appropriately examined and prompt outcomes of tests should be secured. Moreover, for patients of internal medicine practitioners, co-morbidity and complications caused by chronic illness should be given greater attention.