Hospital distribution in a metropolitan city: assessment by a geographical information system grid modelling approach

  • Kwang-Soo Lee | Department of Health Administration, College of Health Sciences, Yonsei University, Wonju, Gwangwondo, Korea, Republic of.
  • Kyeong-Jun Moon Department of Health Administration, Graduate School, Yonsei University, Wonju, Gwangwondo, Korea, Republic of.


Grid models were used to assess urban hospital distribution in Seoul, the capital of South Korea. A geographical information system (GIS) based analytical model was developed and applied to assess the situation in a metropolitan area with a population exceeding 10 million. Secondary data for this analysis were obtained from multiple sources: the Korean Statistical Information Service, the Korean Hospital Association and the Statistical Geographical Information System. A grid of cells measuring 1 × 1 km was superimposed on the city map and a set of variables related to population, economy, mobility and housing were identified and measured for each cell. Socio-demographic variables were included to reflect the characteristics of each area. Analytical models were then developed using GIS software with the number of hospitals as the dependent variable. Applying multiple linear regression and geographically weighted regression models, three factors (highway and major arterial road areas; number of subway entrances; and row house areas) were statistically significant in explaining the variance of hospital distribution for each cell. The overall results show that GIS is a useful tool for analysing and understanding location strategies. This approach appears a useful source of information for decision-makers concerned with the distribution of hospitals and other health care centres in a city.


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Original Articles
hospital, health care, geographical information system, grid method, strategy, location, South Korea.
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How to Cite
Lee, K.-S., & Moon, K.-J. (2014). Hospital distribution in a metropolitan city: assessment by a geographical information system grid modelling approach. Geospatial Health, 8(2), 537-544.