• Title/Summary/Keyword: 동반상병지수

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Factors affecting regular medical care utilization of cardio-cerebrovascular patients (심뇌혈관 환자의 정기적 의료이용에 영향을 미치는 요인)

  • Seo, Young-Suk;Park, Jong-Ho;Lim, Ji-Hye
    • Journal of Digital Convergence
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    • v.12 no.7
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    • pp.327-336
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    • 2014
  • This study aims to identify factors to affect regular utilization status of medical care in cardio-cerebrovascular patients. The research selected 770 cardio-cerebrovascular patients among surveyees from the Korea Health Panel 2010. We analyzed states of medical care utilization using descriptive statistics. Logistic regression analysis was used to examine the main factors associated with regular utilization status of medical care in cardio-cerebrovascular patients. In result, the significant factors associated with regular utilization status of medical care in cardio-cerebrovascular patients were age, education level, household income level. CCI, presence or absence of high risk drinking, and presence or absence of obesity. There's a high probability that patients aged between 60 and 69, equal to and higher than those of high school graduate in education level, upper middle class in household income, the higher CCI, absence of high risk drinking, presence of obesity utilize medical care services more regularly. Therefore, it is necessary to develop effective program and individualized approach for patients using lesser periodical medical care and patients with high risk drinking problem. In the future, these findings can be used an important data for healthcare policy and assessment.

The impact of comorbidity (the Charlson Comorbidity Index) on the health outcomes of patients with the acute myocardial infarction(AMI) (급성심근경색증 환자의 동반상병지수에 따른 건강결과 분석)

  • Lim, Ji-Hye;Park, Jae-Yong
    • Health Policy and Management
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    • v.21 no.4
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    • pp.541-564
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    • 2011
  • This study aimed to investigate health outcome of acute myocardial infarction (AMI) patients such as mortality and length of stay in hospital and to identify factors associated with the health outcome according to the comorbidity index. Nation-wide representative samples of 3,748 adult inpatients aged between 20-85 years with acute myocardial infarction were derived from the Korea National Hospital Discharge Injury Survey, 2005-2008. Comorbidity index was measured using the Charlson Comorbidity Index (CCI). The data were analyzed using t-test, ANOVA, multiple regression, logistic regression analysis in order to investigate the effect of comorbidity on health outcome. According to the study results, the factors associated with length of hospital stay of acute myocardial infarction patients were gender, insurance type, residential area scale, admission route, PCI perform, CABG perform, and CCI. The factors associated with mortality of acute myocardial infarction patients were age, admission route, PCI perform, and CCI. CCI with a higher length of hospital stay and mortality also increased significantly. This study demonstrated comorbidity risk adjustment for health outcome and presented important data for health care policy. In the future study, more detailed and adequate comorbidity measurement tool should be developed, so patients' severity can be adjusted accurately.

A Convergence Study in the Severity-adjusted Mortality Ratio on inpatients with multiple chronic conditions (복합만성질환 입원환자의 중증도 보정 사망비에 대한 융복합 연구)

  • Seo, Young-Suk;Kang, Sung-Hong
    • Journal of Digital Convergence
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    • v.13 no.12
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    • pp.245-257
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    • 2015
  • This study was to develop the predictive model for severity-adjusted mortality of inpatients with multiple chronic conditions and analyse the factors on the variation of hospital standardized mortality ratio(HSMR) to propose the plan to reduce the variation. We collect the data "Korean National Hospital Discharge In-depth Injury Survey" from 2008 to 2010 and select the final 110,700 objects of study who have chronic diseases for principal diagnosis and who are over the age of 30 with more than 2 chronic diseases including principal diagnosis. We designed a severity-adjusted mortality predictive model with using data-mining methods (logistic regression analysis, decision tree and neural network method). In this study, we used the predictive model for severity-adjusted mortality ratio by the decision tree using Elixhauser comorbidity index. As the result of the hospital standardized mortality ratio(HSMR) of inpatients with multiple chronic conditions, there were statistically significant differences in HSMR by the insurance type, bed number of hospital, and the location of hospital. We should find the method based on the result of this study to manage mortality ratio of inpatients with multiple chronic conditions efficiently as the national level. So we should make an effort to increase the quality of medical treatment for inpatients with multiple chronic diseases and to reduce growing medical expenses.

Factors Affecting the Registration and Access Levels of the Pilot Project for the General Physician System among People with Disabilities (장애인 건강주치의 시범사업 수요자의 등록 및 이용수준 영향 요인 분석)

  • Eunhee Choe;Yeojeong Gu;Seungji Lim
    • Health Policy and Management
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    • v.34 no.2
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    • pp.185-195
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    • 2024
  • Background: Disabled people have particularly restricted access to health care. In response to this, the pilot project for the general physician (GP) system for disabled people was implemented in 2018, based on the rights of people with disability to the Health Act in South Korea. However, its participants were 0.2% among the total of those with severe disabilities in 2021. Therefore, this study examined the factors related to registering with a GP and the access level to its services to suggest implications for activating the participation of disabled people. Methods: We analyzed factors affecting the registration with a GP and the number of using the services among the participants of the GP system during May 2018 and December 2021 by conducting hierarchical logistic regression and hierarchical regression. The data were linked with the national health insurance data to examine various predictors, including disability types, socioeconomic status, health status, and GP registration. Results: As a result of analyzing the factors affecting whether or not to register for the pilot project, those with disabilities (physical disabilities, brain lesions, visual, intellectual, mental, and autistic disability) eligible for disability care (odds ratio [OR], 4.157) than other disability, and those living in metropolitan (OR, 4.330) or cities (OR, 3.332) than rural residences were highly likely to enroll the pilot study. Health-related variables also predicted the registration status of the pilot project. The predictors related to GP enrollment types (membership type: general health or disability care, GP's affiliation: clinics or hospitals) significantly influenced levels of access to services. Conclusion: It is necessary to develop the GP project for disabled people by considering the variation in types of disability, residences, and health. Further study will be needed to investigate the impact of GPs on the level of participation among disabled people.