Space Based Application For The Inventory, Distribution And Analysis Of Healthcare Facilities In Nasarawa State, Nigeria

Abstract

The study aimed at carrying out the inventory, distribution and analysis of healthcare facilities in Nasarawa state using remote sensing and geographic information system (GIS) techniques. Field mapping was conducted and coordinates with attributes of these healthcare facilities were recorded. GIS analysis using multiple ring buffer and cluster extension of the spatial analysis tool in ArcGIS 10.8 version was used. Result revealed a total of 1,119 healthcare facilities distributed across the state. Out of which 807 are government primary healthcare, while 227 are private primary and 24 government secondary whereas 60 are private secondary and one tertiary healthcare facility. Result also revealed significant disparities in the distribution of government tertiary healthcare facilities across the local government areas with only having such facility in the whole of Nasarawa State. This indicates limited access to specialized healthcare services. The general trend of health facilities in Nasarawa state is towards clustering because these facilities are intended to reside close to settlements and thus will present some degree of clustering though the level may differ between different types of facilities. The buffer analysis in secondary healthcare showed a wide number of settlements by local government that need more present of secondary healthcare facility in Nasarawa state showing good accessibility of health care facility to the settlement within 1 km and 10 km radius. The government own primary healthcare facilities record a z-score of -17.52725 and 0.677488 nearest neighbour ratio suggesting a very strong trend towards clustering, and from the analysis, there is a less than 1% chance of randomness or dispersion. This indicates that there is a lot needs to be done to ensure a more dispersed and competitive distribution of these facilities. The private primary healthcare facilities have a z-score of -18.527370 and nearest neighbour ratio of 0.357209, which shows very significant clustering alongside an identical 1% probability of random distribution. This clearly indicates that there is need for strategic planning and resource allocation to the health sector to ensure an equitable, dispersed and competitive distribution of these facilities. The findings from this study have implications for the actualization of the United Nations’ health-related Sustainable Development Goal (SDG-3) and also to achieve the Universal health coverage.