J Periodontal Implant Sci.  2016 Jun;46(3):207-217. 10.5051/jpis.2016.46.3.207.

Geographic information system analysis on the distribution of patients visiting the periodontology department at a dental college hospital

• Jeong B
• Joo HT
• Shin HS
• Lim MH
• Park JC

• KMID: 2382984
• DOI: http://doi.org/10.5051/jpis.2016.46.3.207

Abstract

PURPOSE
The 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.
METHODS
Basic 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.
RESULTS
The 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.
CONCLUSIONS
The 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.

Keyword

Epidemiology; Geographic information systems; Periodontal diseases

MeSH Terms

Epidemiology
Geographic Information Systems*
Humans
Logistic Models
Male
Parturition
Patient Care
Periodontal Diseases
Social Class
Spatial Regression

Figure

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  Figure 1 Color-coded local R2 values for each district. The regression model performance of the geographically weighted regression analysis is high in regions that are close to the hospital (indicated with red dots). This implies that the variables are better explained in closer regions.

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  Figure 2 Color-coded local GWR coefficients for the distance from the center of the region to the adjacent toll gate. In regions that are far from the hospital (indicated with red dots), the number of patients increases with an increase in the distance from the adjacent toll gate.

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  Figure 3 Local average age of patients visiting the Department of Periodontology, Dankook University Dental Hospital. A majority of the regions have a local average age of 50–69 years.

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  Figure 4 Color-coded local male ratio of patients visiting the Department of Periodontology, Dankook University Dental Hospital. A male dominance can be observed for most of the regions.

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