• Journal of agricultural medicine and community health
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• v.26 no.1
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• pp.19-35
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• 2001

This study was conducted to investigate the internal changes and the countermeasure for performance improvement by Separation of Prescribing and Dispensing Practice (SPDP) in Health Center. Data were collected from two sources: Performance report before and after SPDP of 25 Health Centers in Kyongsangbuk-do and 6 Health Centers in Daegu-City and self-administerd questionnaire survey of 221 officials at health center. The results of this study were summarized as follows: Twenty-four health centers(77.4%) of 31 health centers took convenience measures for medical treatment of citizens and convenience measures were getting map of pharmacy, improvement of health center interior, introduction of order communication system in order. After the SPDP in health centers, 19.4% of health centers increased doctors and 25.8% decreased pharmacists. 58.1% of health centers showed that number of medical treatments were decreased. 96.4%, 80.6% 80.6% 96.7% of health centers showed that number of prescriptions, total medical treatment expenses, amounts paid by the insureds and the expenses to purchase drugs, respectively, were decreased. More than fifty percent(54.2%) of health centers responded that the relative importance of health works increased compared to medical treatments after the SPDP, and number of patients decreased compared to those in before the SPDP. And there was a drastic reduction in number of prescriptions, total medical treatment expenses, amounts paid by insureds, the expenses to purchase drugs after the SPDP. Above fifty percent(57.6%) of officers at health center responded that the function of medical treatment should be reduced after the SPDP. Fields requested improvement in health centers were 'development of heath works contents'(62.4%), 'rearrangement of health center personnel'(51.6%), 'priority setting for health works'(48.4%), 'restructuring the organization'(36.2%), 'quality impro­vement for medical services'(32.1%), 'replaning the budgets'(23.1%) in order. And to better the image of health centers, health center officers replied that 'health information management'(60.7%), 'public relations for health center'(15.8%), 'kindness of health center officers'(15.3%) were necessary in order. Health center officers suggested that 'vaccination program', 'health promotion', 'maternal and children health', 'communicable disease management', 'community health planning' were relatively important works, in order, performed by health center after SPDP. In the future, medical services in health centers should be cut down with a momentum of the SPDP so that health centers might reestablish their functions and roles as public health organizations, but quality of medical services must be improved. Also health centers should pay attention to residents for improving health through 'vaccination program', 'health promotion', 'mother-children health', 'acute and chronic communicable disease management', 'community health planning', 'oral health', 'chronic degenerative disease management', etc. And there should be a differentiation of relative importance between health promotion services and medical treatment services by character of areas(metropolitan, city, county).

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."