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Spatial planning of health-care facilities and equal access to primary health care: a case of GIS (Geographic Information System) use in Bangkok

Date: Poster sessions
Source: Forum 11
Authors: Nopadon Sahachaisaeree, Head of the Department of Urban and Regional Planning (DURP) PhD Programme, King Mongkut Institute of Technology, Ladkrabang, Thailand


The problems of primary health care shortages in Bangkok have been intensified by a population explosion. The concentration of medical facilities within Bangkok's central business district further complicates patients' travel problems. Such dilemmas could be solved by careful spatial planning of primary health-care service facilities.

This research aims to: 1) elucidate the factors affecting the patients' choice of the type of facilities; 2) to model the spatial pattern of the patients' travel behaviour from the collected data; and 3) to reach the service catchment areas for each type of primary health-care facility, using a Geographic Information System (GIS) approach. Using GIS and the data obtained from phase I of this study, a spatial model of primary health care was constructed, in accordance with the current government's `equal access to primary health-care' programme.

Based on Walter Christaller's `Central Place Theory', this research assumes three primary variables affecting the travel patterns of patients: 1) the range of treatment in a particular facility; 2) patients' attributes; and 3) acquaintance with medical personnel. A structured questionnaire was utilized to obtain the primary data, while locational data from the Bangkok Metropolitan Administration was used to identify the spatial location of each health-care facility. The results were used to represent the patients' decision-making pattern in choosing primary health-care services.

The research findings were able to model the patients' travel patterns by means of GIS buffering, to establish the catchment areas of public/private hospitals, health- care centres, and medical clinics. Out-of-reach areas were then identified. Modeling according to the type of sickness and patient, and personal attributes were also charted to identify the respective groups' travel patterns. The study then compared the carrying capacity of health-care facilities and the spatial organization of population (population density) to identify the out-of-service areas and the patient assignment in order to maintain `equal access to primary health care'.

One can conclude from this study that modeling could be helpful for the prediction of health-care sufficiency and the planning of the spatial organization of facilities in the future.