• Journal of Gastric Cancer
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• v.19 no.2
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• pp.212-224
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• 2019

Purpose: Splenic hilar lymph node dissection (LND) during total gastrectomy is regarded as the standard treatment for proximal advanced gastric cancer (AGC). This study aimed to investigate whether splenic hilar LND or D2 LND is essential for proximal AGC of pT2- 4aN0M0 stage. Materials and Methods: Data of curative total gastrectomies (n=370) performed from 2000 to 2010 for proximal AGC of pT2-4aN0 stage were retrospectively reviewed. Clinicopathological characteristics and long-term outcomes were compared using propensity score matching between patients who underwent splenectomy (n=43) and those who did not (n=327) and between patients who underwent D2 LND (n=122) and those who underwent D1+ LND (n=248). Results: Tumors of larger size and a more advanced T stage and significantly lower overall and relapse-free survival (P<0.001) were observed in the splenectomy group than in the 2 spleen-preserving groups. Before propensity score matching, worse overall and relapse-free survival (P<0.001) was observed in the splenectomy group than in the non-splenectomy group. After matching, although the overall survival became similar (P=0.123), relapse-free survival was worse in the splenectomy group (P=0.021). Compared with D1+ LND, D2 LND had no positive impact on the overall (P=0.619) and relapse-free survival (P=0.112) after propensity score matching. Conclusions: Splenic hilar LND with or without splenectomy may not have an oncological benefit for patients with pathological AGC with no LN metastasis.

• Journal of Trauma and Injury
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• v.37 no.1
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• pp.6-12
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• 2024

Purpose: Open pelvic bone fractures are relatively rare and are considered more severe than closed fractures. This study aimed to compare the clinical outcomes of open and closed severe pelvic bone fractures. Methods: Patients with severe pelvic bone fractures (pelvic Abbreviated Injury Scale score, ≥4) admitted at a single level I trauma center between 2016 and 2020 were retrospectively analyzed. Patients aged <16 years and those with incomplete medical records were excluded from the study. The patients were divided into open and closed fracture groups, and their demographics, treatment, and clinical outcomes were compared before and after 1:2 propensity score matching. Results: Of the 321 patients, 24 were in the open fracture group and 297 were in the closed fracture group. The open fracture group had more infections (37.5% vs. 5.7%, P<0.001) and longer stays in the intensive care unit (median 11 days, interquartile range [IQR] 6-30 days vs. median 5 days, IQR 2-13 days; P=0.005), but mortality did not show a statistically significant difference (20.8% vs. 15.5%, P=0.559) before matching. After 1:2 propensity score matching, the infection rate was significantly higher in the open fracture group (37.5% vs. 6.3%, P=0.002), whereas the length of intensive care unit stay (median 11 days, IQR 6-30 days vs. median 8 days, IQR 4-19 days; P=0.312) and mortality (20.8% vs. 27.1%, P=0.564) were not significantly different. Conclusions: The open pelvic fracture group had more infections than the closed pelvic fracture group, but mortality was not significantly different. Aggressive treatment of pelvic bone fractures is important regardless of the fracture type, and efforts to reduce infection are important in open pelvic bone fractures.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.257-265
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• 2023

This paper investigates the determinants of credit accessibility and the effect of credit on the income of farm households borrowing from Vietnam Bank for Agriculture and Rural Development, Giong Rieng District Branch, Kien Giang Province. Based on the primary data of 200 farming households who are the customer of the bank, the study applied the Probit regression model to examine determinant factors of credit accessibility of farm households and employed the Propensity score matching method to investigate the impact of credit on households' income. The findings of the Probit regression shown that three independent variables that significantly influence the access to credit of households are household size, income source, and farm size. Besides that, the Propensity score matching method results showed a difference of 23.799 million VND/year between the income of borrowing households and that of non-borrowing households at the significance level of 1%. The difference in the imcome from the interval and central matching methods are VND 24.700 million VND/year and VND 24.633 million VND/year, respectively. Given empirical findings suggetsted that several recommendations to increase the credit accessibility of farm households, thereby creating favorable conditions for improving their income.

• Health Policy and Management
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• v.25 no.1
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• pp.3-10
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• 2015

Background: Previous studies showed differences in healthcare utilization among insurance types. This study aimed to analyze the difference in healthcare utilization for percutaneous transluminal coronary angioplasty inpatients by insurance types after controlling factors affecting healthcare utilization using propensity score matching (PSM). Methods: The 2011 national inpatient sample based on health insurance claims data was used for analysis. PSM was used to control factors influencing healthcare utilization except insurance types. Length of stay and total charges were used as healthcare utilization variables. Patients were divided into National Health Insurance (NHI) and Medical Aid (MA) patients. Factors representing inpatients (gender, age, admission sources, and Elixhauser comorbidity index) and hospitals (number of doctors, number of beds, and location of hospitals) were used as covariates in PSM. Results: Tertiary hospitals didn't show significant difference in length of stay and total charges after PSM between two insurance types. However, MA patients showed significantly longer length of stay than that of NHI patients after PSM in general hospitals. Multivariate regression analysis provided that admission sources, Elixhauser comorbidity index, insurance types, number of doctors, and location of hospitals (province) had significant influences on the length of stay in general hospitals. Conclusion: Study results provided evidences that healthcare utilization was differed by insurance types in general hospitals. Health policy makers will need to prepare interventions to influence the healthcare utilization differences between insurance types.

• Genomics & Informatics
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• v.17 no.4
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• pp.47.1-47.12
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• 2019

The achievements of genome-wide association studies have suggested ways to predict diseases, such as type 2 diabetes (T2D), using single-nucleotide polymorphisms (SNPs). Most T2D risk prediction models have used SNPs in combination with demographic variables. However, it is difficult to evaluate the pure additive contribution of genetic variants to classically used demographic models. Since prediction models include some heritable traits, such as body mass index, the contribution of SNPs using unmatched case-control samples may be underestimated. In this article, we propose a method that uses propensity score matching to avoid underestimation by matching case and control samples, thereby determining the pure additive contribution of SNPs. To illustrate the proposed propensity score matching method, we used SNP data from the Korea Association Resources project and reported SNPs from the genome-wide association study catalog. We selected various SNP sets via stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and the elastic-net (EN) algorithm. Using these SNP sets, we made predictions using SLR, LASSO, and EN as logistic regression modeling techniques. The accuracy of the predictions was compared in terms of area under the receiver operating characteristic curve (AUC). The contribution of SNPs to T2D was evaluated by the difference in the AUC between models using only demographic variables and models that included the SNPs. The largest difference among our models showed that the AUC of the model using genetic variants with demographic variables could be 0.107 higher than that of the corresponding model using only demographic variables.

• Health Policy and Management
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• v.26 no.4
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• pp.343-351
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• 2016

Background: This study aims to analyze the effects of insurance types on the medical service uses for heart failure inpatients using propensity score matching (PSM). Methods: 2014 National inpatient sample based on health insurance claims data was used in the analysis. PSM was applied to control factors influencing the service uses except insurance types. Negative binomial regression was used after PSM to analyze factors that had influences on the service uses among inpatients. Subjects were divided by health insurance type, national health insurance (NHI) and medical aid (MA). Total charges and length of stay were used to represent the medical service uses. Covariance variables in PSM consist of sociodemographic characteristics (gender, age, Elixhauser comorbidity index) and hospital characteristics (hospital types, number of beds, location, number of doctors per 50 beds). These variables were also used as independent variables in negative binomial regression. Results: After the PSM, length of stay showed statistically significant difference on medical uses between insurance types. Negative binomial regression provided that insurance types, Elixhauser comorbidity index, and number of doctors per 50 beds were significant on the length of stay. Conclusion: This study provided that the service uses, especially length of stay, were differed by insurance types. Health policy makers will be required to prepare interventions to narrow the gap of the service uses between NHI and MA.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.415-445
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• 2023

Oftentimes, the time dependent treatment covariate and the time dependent confounders exist in observation studies. It is an important problem to correctly adjust for the time dependent confounders in the propensity score analysis. Recently, In the survival data, Hade et al. (2020) used a propensity score matching method to correctly estimate the treatment delay effect when the time dependent confounder affects time to the treatment time, where the treatment delay effects is defined to the delay in treatment reception. In this paper, we proposed the Cox model based marginal structural model (Cox-MSM) framework to estimate the treatment delay effect and conducted extensive simulation studies to compare our proposed Cox-MSM with the propensity score matching method proposed by Hade et al. (2020). Our simulation results showed that the Cox-MSM leads to more exact estimate for the treatment delay effect compared with two sequential matching schemes based on propensity scores. Example from study in treatment discontinuation in conjunction with simulated data illustrates the practical advantages of the proposed Cox-MSM.

• The Korean Journal of Health Service Management
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• v.11 no.3
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• pp.65-78
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• 2017

Objectives : Obesity is a worldwide health concern due to an increasing obese population. This study proposed to analyze the differences in medical costs and care utilization between obese and normal group using propensity score matching. Methods : Data were collected from the sample cohort database by the Korea National Health Insurance Corporation. Propensity score matching(PSM) was applied to control selection bias, and factors affecting obesity were used as covariates in PSM. Results : The results showed higher medical costs and care utilization in the obese group than the normal group. According to gender and medical type, there were differences in the relationships between obesity and medical charges and utilization. In particular, the differences in the female population were larger in both outpatients and inpatients than the male population. Conclusions : It is important to manage obesity, because obesity has a negative effect on national health insurance costs. These findings suggest directions for future research.

• Korean Journal of Health Education and Promotion
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• v.33 no.1
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• pp.61-70
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• 2016

Objectives: It has been well documented that people on the lower socioeconomic position are significantly more likely to smoke cigarettes. The purposes of this study were (a) to identify a potential difference of socioeconomic factors, and (b) to compare a smoking rate, one of the most representative health behavior between people with/without disabilities after the controlling socioeconomic factors. Methods: The Korea Panel Survey of Employment for People of Disabilities (2012) and the Korea National Health and Nutrition Survey (2012) were employed for calculating the smoking rates of persons with/without disabilities. Results: The results demonstrated that the socioeconomic position indicators (education, occupation and household equivalent income) of persons with disabilities were lower than persons without disabilities. The smoking rates of the persons with/without disabilities were 35.9% and 19.0% respectively before propensity score matching. After propensity score matching with the socioeconomic factors, however, ATT of people with disabilities was 0.201 which is lower than ATT of people without disabilities (0.227). Conclusions: Our findings indicated that the socioeconomic level of persons with disabilities is important to improve the smoking rates and health level regardless of their disabilities.

• Journal of Korea Technology Innovation Society
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• v.14 no.3
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• pp.689-710
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• 2011

The purpose of this paper is to positively analyze firms' innovative performance enhanced by cooperation, such as industry-university or industry-government, in service industry. We use PSM method (Propensity Score Matching) based on Korea Innovation Survey data in service industry to investigate it. This empirical study finds that cooperation with university or government partially has positive effects on firm's patent applications and innovation. So, we suggest we need various policies for research institute linkage in service industry.