• Journal of the Korean Society of Mechanical Technology
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• v.13 no.1
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• pp.1-9
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• 2011

The present study aimed to compare and analyze the particulars of and difference in medical expenses and their composition ratio for 2,026 patients hospitalized at 2 types of medical institutions (443 at a clinic and 1,583 at a hospital) in Jeonju-si, Jeollabuk-do under coverage of automobile insurance during 2009. From the analysis, it became evident that there were differences in individual characters of inpatients covered by automobile insurance, and details, composition and composition ratio of medical treatment for them depending on types of medical institutions. There was no difference, however, between the total and average medical expenses per capita even when markup rate was applied to the automobile insurance by types of hospitals. The ratio of radiotherapy and physical therapy in the composition of medical expenses was found to be extraordinarily high in clinics compared to that of hospitals. The composition ratio of the fixed cost including charge for hospitalization also turned out to be fairly high in all medical institutions.

• Quality Improvement in Health Care
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• v.12 no.2
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• pp.61-71
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• 2006

• 가정의 벗
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• v.37 no.4 s.428
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• pp.28-29
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• 2004

지난해 9월 정부에서는 진료비 지원대상에 포함되는 희귀난치성질환에 페브리병 등 3개 질환을 추가해 모두 11개 질환으로 늘리기로 했다고 발표했다. 그러나 100여 종이 넘는 희귀난치성질환을 앓고 있는 환자와 가족에게 희망을 주기에는 아직 역부족이 아닐까.

• The Journal of the Korean dental association
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• v.36 no.5 s.348
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• pp.372-379
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• 1998

• Korea Journal of Hospital Management
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• v.19 no.2
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• pp.99-105
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• 2014

• Health Policy and Management
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• v.11 no.3
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• pp.46-70
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• 2001

Medical Aid expenditure Increased rapidly at a higher rate than that of Medical Insurance during the period 1992-1999. To establish an effective cost containment strategy, knowledge of the cause and the nature of the increase of Medical Aid expenditure is required. The purpose of this study was to analyze increasing rates of Medical Aid expenditure by the components of medical expenses. Data were collected using the Medical Aid Statistical Yearbook during the period of 1992-1999. The major findings were as follows: 1. The annual mean increasing rate of Medical Aid expenditure between 1992 and 1999 was 22.8%, which exceeding that of Medical Insurance expenditure (17.5%) between 1992 and 1999. Since 1998, Medical Aid expenditure increased even more rapidly than in previous years, with the increase in number of Medical Aid beneficiaries. 2. Of Medical Aid expenditure, that of inpatient and outpatient annually increased 24.2% and 22.8% respectively and that of type 1 and type 2 increased annually 28.8% (outpatient) ∼29.9% (inpatient), 14.3% (outpatient) ∼ 15.5% (inpatient). Therefore, Medical Aid expenditure of inpatient and type 1 led the increase of Medical Aid expenditure. 3. Between 1992 and 1997, the frequencies of utilization per beneficiary and the charges per case positively contributed to the increase of Medical Aid expenditure while the number of beneficiaries contributed negatively, but since 1998, the number of beneficiaries increased and positively contributed to the increase of Medical Aid expenditure. 4. According to the analysis of the charges per case, the increase of the price index led to the increase of the charges per case but the days of medication and service intensity also contributed to the increase of the charges per case variably by year. Considering the above findings, factors associated with the Medical Aid system affected the increase of Medical Aid expenditure in addition to the general factors of the increase in medical expenditure. In conclusion, it appears that a more intensive cost containment strategy is required to control rapidly increasing Medical Aid expenditure. For this, more precise analysis and development of policy considering the effect of the number of beneficiaries and the increase of price index is needed.

• Convergence Security Journal
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• v.23 no.1
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• pp.89-95
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• 2023

In order to help reduce the medical expenses of patients with auto insurance accidents, this study predicted the treatment period, which is the most important factor in the medical expenses of patients in their 40s and 50s, and analyzed the factors affecting the treatment period. To this end, a mechine learning model using five algorithms such as Decision Tree was created, and its performance was compared and analyzed between models. There were three algorithms that showed good performance including Decison Tree, Gradient Boost, and XGBoost. In addition, as a result of analyzing the factors affecting the prediction of the treatment period, the type of hospital, the treatment area, age, and gender were found. Through these studies, easy research methods such as the use of AutoML were presented, and we hope that the results of this study will help policies to reduce medical expenses for automobile insurance accidents.

• The Korean Journal of Applied Statistics
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• v.28 no.4
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• pp.663-683
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• 2015

The change of the population pyramid due to low fertility and rapid aging threatens the financial sustainability of National Health Insurance. We construct statistical models for prevalence rates and medical expenses using National Health Insurance Service (NHIS) sample cohort data from 2002-2013. We then project yearly expenditures and income of national health insurance until 2060 that considers various assumptions in regards to future population structure and economic conditions. We adopt a VECM-LC model for prevalence rates and the double exponentially smoothing method for the per capita co-payment of healthcare expense (in which the two models are institution-disease-sex-age specific) to project of national health insurance expenditures. We accommodate various assumptions of economic situations provided by the national assembly and government to produce a financial projection for national health insurance. Two assumptions of dependents ratios are used for the projection of national health insurance income to conduct two future population structures by the two assumptions of aging progresses and various assumptions on economic circumstances as in the expenditure projection. The health care deficit is projected to be 20-30 trillion won by 2030 and 40-70 trillion won by 2060 in 2015 constant price.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.696-706
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• 2017

This study is to examine health care utilization and morbidity of disabled and non-disabled children in Korea to evaluate the health disparities. We used medical claim data of 2010 from the National Health Insurance Service-National Sample Cohort data. As a result of the analysis, the disabled children are not in good health condition because they have more frequency of medical service use, hospitalization rate, and more number of diseases and spent more on medical expenses than non-disabled children. Patterns of the most frequent disease differ from significantly between disable and non-disabled. Disabled children had a higher prevalence of selected birth defects and selected health conditions associated with physical disability and a lower prevalence of selected infection disease than children without disability. In conclusion, Health policy changes that would extend the access to health service for children with disabilities characterized by frequent medical care, hospitalization, excessive medical expenditure and complex diseases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1504-1510
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• 2010

According to a research analysis of the factors which affect the medical utilization fee after an increase of health insurance benefits for patients with serious illnesses based on 225 patients over 6 months, both before and after the increase of benefits, from January, 1st, 2005 to June 30th, and also from January, 1st, 2006 to June 30th. In terms of genders, 67.8% of males were affected, whereas only 32.2% of females were effected, a much higher rate of men than women. Men also had higher rates before and after the increase of benefits. Out of 5 categories related to medication and treatment, radiation testing was the most expensive at about 5,300,000, operation fees were 590,000, and costs of other testing approximately 200,000 with the least expensive category being 120,000 for medication. By looking at the relationship between the fees and increase of benefits, medication was a hospital charge (p<0.01), injection fees were hospital charges (p<0.01), operation fees were hospital charges (p<0.01). Medication fees (p<0.01) and injection fees (p<0.01) were found to be related.