PurposeThe aim of this study is to analyze and visualize the distribution of patients visiting the periodontology department at a dental college hospital, using a geographic information system (GIS) to utilize these data in patient care and treatment planning, which may help to assess the risk and prevent periodontal diseases.MethodsBasic patient information data were obtained from Dankook University Dental Hospital, including the unit number, gender, date of birth, and address, down to the dong (neighborhood) administrative district unit, of 306,656 patients who visited the hospital between 2007 and 2014. The data of only 26,457 patients who visited the periodontology department were included in this analysis. The patient distribution was visualized using GIS. Statistical analyses including multiple regression, logistic regression, and geographically weighted regression were performed using SAS 9.3 and ArcGIS 10.1. Five factors, namely proximity, accessibility, age, gender, and socioeconomic status, were investigated as the explanatory variables of the patient distribution.ResultsThe visualized patient data showed a nationwide scale of the patient distribution. The mean distance from each patient’s regional center to the hospital was 30.94±29.62 km and was inversely proportional to the number of patients from the respective regions. The distance from a regional center to the adjacent toll gate had various effects depending on the local distance from the hospital. The average age of the patients was 52.41±12.97 years. Further, a majority of regions showed a male dominance. Personal income had inconsistent results between analyses.ConclusionsThe distribution of patients is significantly affected by the proximity, accessibility, age, gender and socioeconomic status of patients, and the patients visiting the periodontology department travelled farther distances than those visiting the other departments. The underlying reason for this needs to be analyzed further.

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This study attempted to examine the economic effects of leading urban regeneration areas, with the leading urban regeneration area in Gunsan as a case study. To examine the economic effects of the urban regeneration project in Gunsan, the study utilized the floating population and revenue data of SKT. Then, it compared variations in accordance with changes in time periods in relation to the leading urban regeneration area and other areas for comparison. Additionally, revenue figures were sorted by business type to confirm which ones were affected by the implementation of the urban regeneration project. The study identified increased revenue figures for the business types of transportation, lodging, and real estate in the leading urban regeneration area, along with an increase in the floating population compared to the period of reference. Conversely, the revenue figures for the food service industry tended to increase only for confectioneries, bakeries, rice cakes, and cakes; snack bars; and teahouses, coffee shops, and cafes. These figures indicated that outsiders visited the area for travel and tended to consume snack foods. However, the economic ripple effect from the inflow of tourists has been confirmed as being limited to businesses such as bakeries, cafes, and snack bars. Although the inflow of outside populations, which was expected to revitalize the regional economy of Gunsan, has achieved results to a certain extent, a plan must be formulated to draw out the spending of tourists.

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