• Health Policy and Management
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• v.33 no.3
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• pp.355-362
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• 2023

Background: Financial efficiency in monetary units and operational efficiency in non-monetary units are separately classified and evaluated. This is done to prevent the duplication of monetary units and non-monetary units in inputs and outputs. In addition, analyses are conducted to determine the factors that affect each aspect of efficiency. To prevent duplication of monetary and non-monetary units in inputs and outputs, financial efficiency, consisting of monetary units, and operational efficiency, comprising non-monetary units, are separately classified and evaluated. Furthermore, an analysis is conducted to identify the factors that affect each aspect of efficiency. Methods: This study conducted a panel analysis of 34 regional public hospitals and influencing factors on efficiency for 5 years from 2015 to 2019. Financial efficiency and operational efficiency were calculated through data envelopment analysis. Moreover, multiple regression analysis was conducted to identify the factors that influence both financial efficiency and operational efficiency. Results: The factors that affect financial efficiency include the number of medical institutions within the treatment area and the ratio of patients receiving medical care. Additionally, operational efficiency is influenced by the type of medical institution, the number of medical institutions within the treatment area, and the number of nursing positions per 100 beds. Conclusion: In order for regional public hospitals to faithfully fulfill their functions and roles as regional base public hospitals, several measures are necessary. Firstly, continuous monitoring and reasonable support are required to ensure efficient operation and performance. Secondly, a financial support plan tailored to the characteristics of local medical centers is needed. Additionally, local medical centers should strive to enhance their own efficiency.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• Health Policy and Management
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• v.34 no.3
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• pp.282-292
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• 2024

Background: This study aimed to identify the relationship between regional health outcomes and the living population, which may reflect the characteristics of population migration in Seoul. Methods: This study used raw data on cause of death statistics from Statistics Korea's Micro Data Integration Service. To identify the independent variable, the living population, we used living population data provided by Korean Telecom for 25 districts of Seoul. The control variables were based on the four domains of SDoH (social determinants of health; economic stability, healthcare access and quality, neighborhood and built environment, and social and community context). Panel generalized estimating equations (GEE) analysis was used to determine the relationship between living population and regional health outcomes. Results: The panel GEE analysis showed that all mortality-related health outcomes (avoidable, preventable, and treatable mortality) had a statistically significant negative relationship with the living population. This indicated that an increase in living population had a positive effect on mortality-related health outcomes. Conclusion: The identification of a notable relationship between regional health outcomes and population density underscores the utility of incorporating living population metrics as key indicators in the development of policies aimed at mitigating health disparities. Moreover, this finding advocates for strategic expansions of local infrastructure, with a particular emphasis on areas characterized by low living populations.

• Journal of Food Hygiene and Safety
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• v.36 no.1
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• pp.68-76
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• 2021

Foodborne outbreaks frequently occur worldwide and result in huge economic losses. It is the therefore important to estimate the costs associated with foodborne diseases to minimize the economic damage. At the same time, it is difficult to accurately estimate the economic loss from foodborne disease due to a wide variety of cost components. In Korea, there are a limited number of analytical studies attempting to estimate such costs. In this study we investigated the components of economic cost used in foreign countries to better estimate the cost of foodborne disease in Korea. Seven recent studies investigated the cost components used to estimate the cost of foodborne disease in humans. This study categorized the economic loss into four types of cost: direct costs, indirect costs, food business costs, and government administration costs. The healthcare costs most often included were medical (outpatient) and hospital costs (inpatient). However, these cost components should be selected according to the systems and budgets of medical services by country. For non-healthcare costs, several other studies considered transportation costs to the hospital as an exception to the cost of inpatient care. So, further discussion is needed on whether to consider inpatient care costs. Among the indirect costs, premature mortality, lost productivity, lost leisure time, and lost quality of life/pain, grief and suffering costs were considered, but the opportunity costs for hospital visits were not considered in any of the above studies. As with healthcare costs, government administration costs should also be considered appropriate cost components due to the difference in government budget systems, for example. Our findings will provide fundamental information for economic analysis associated with foodborne diseases to improve food safety policy in Korea.

• Health Policy and Management
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• v.34 no.2
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• pp.196-210
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• 2024

Background: In January 2018, revised elderly fixed outpatient copayment for the elderly were implemented. When people ages 65 years and older receive outpatient treatment at clinic-level medical institutions (clinic, dental clinic, Korean medicine clinic), with medical expenses exceeding 15,000 won but not exceeding 25,000 won, their copayment rates have decreased differentially from 30%. This study aimed to examine the changes of health utilization of elderly after revised elderly fixed outpatient copayment. Methods: We used Korea health panel data from 2016 to 2018. The time period is divided into before and after the revised elderly fixed outpatient copayment. We conducted Poisson segmented regression to estimate the changes in outpatient utilization and inpatient utilization and conducted segmented regression to estimate the changes in medical expenses. Results: Immediately after the revised policy, the number of clinic and Korean medicine outpatient visits of medical expenses under 15,000 won decreased. But the number of clinic outpatient visits in the range of 15,000 to 20,000 won and Korean medicine clinic in the range of 20,000 to 25,000 won increased. Copayment in outpatient temporarily decreased. The inpatient admission rates and total medical expenses temporarily decreased but increased again. Conclusion: We confirmed the temporary increase in outpatient utilization in the medical expense segment with reduced copayment rates. And a temporary decrease in medical expenses followed by an increase again. To reduce the burden of medical expense among elderly in the long run, efforts to establish chronic disease management policies aimed at preventing disease occurrence and deterioration in advance need to continue.

• Health Policy and Management
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• v.34 no.3
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• pp.249-260
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• 2024

Background: The Republic of Korea's aging population escalates medical and long-term care costs. While prior research has suggested that long-term care might reduce these costs, these studies had limitations in their subjects and duration, making it difficult to generalize the results. This study aims to evaluate cost changes between the long-term care group and the general older adults group after addressing these limitations. Methods: A cohort was derived from the 2015 national population using stratified sampling. Subsequently, 15,114 individuals (7,557 in each group) were identified through 1:1 propensity score matching. The study employed a difference-in-differences analysis to explore variances in medical costs and long-term care benefits post-utilization of long-term care services. Results: Compared to the general older adults group, the long-term care group experienced a reduction in monthly per capita total medical costs by 56,459 Korean won (KRW). Although costs at tertiary and general hospitals increased, those related to long-term care hospitals decreased by 90,687 KRW. Including long-term care benefits, overall expenditures increased by 948,038 KRW. Conclusion: The analysis reveals that the long-term care group faces higher medical costs in acute care than the general older adults group, emphasizing a greater need for medical services within this group. To meet the increasing medical demands of the long-term care group, a collaborative strategy linking community resources, healthcare, and long-term care facilities is imperative. Additionally, developing and implementing preventive health habit management strategies for middle-aged and older adults is essential to diminish the future requirement for long-term care.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.155-174
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• 2022

From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (