Access to healthcare is a determinant of the wellbeing of the people. Planning the location and distribution of health facilities to ensure efficiency and equity in the face of limited resources can be challenging, especially where the type of care requires expensive equipments and specialists. This study attempts to provide a spatial decision support system (SDSS) to select specific locations for provision of mental health care out of existing health centres. The SDSS in this study uses a geographic information system (GIS) and location-allocation models. The data used in the SDSS include the coordinates of the location of the mental health facilities, the coordinates and population of the settlements and data on the roads and footpaths in the study area. The empirical results from the application of the SDSS framework shows that the average distance travelled in the existing configuration of mental health care centres (MHC) could be reduced from 15.3 km to 14 km by adopting a model plan. It is also shown that 74.85% of the settlements are more than ten kilometers from the nearest MHC. In order to minimize travel distance and maximize coverage of the population the minimize facilities, model option of the SDSS shows that 21 facilities are required to ensure that the average travel distance is 9.4km and that 98.6% of the settlements are not more than 20 km from the nearest MHC. Decision makers can use the SDSS discussed in this study to achieve efficiency or equity in the provision of health services. Thus it is hoped that health planners would adopt these techniques and tools to make their location decisions more efficient, reduce inequities and be rational in the use of resources. Key Words: Mental Health Facilities, Spatial Decision Support System, Location Allocation Models, Location Efficiency, Location Equity
CITATION STYLE
Otun, O. W. (2017). A spatial decision support system for special health facility location planning in developing regions. Ethiopian Journal of Environmental Studies and Management, 9(1), 829. https://doi.org/10.4314/ejesm.v9i1.3s
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