Abstract
This paper explores the possibilities of adopting Business Intelligence (BI), and Geographic Information System (GIS) to build a spatial intelligence and predictive analytical approach. The proposed approach will help in solving spatial problem which faces decision makers at health sector. The proposed spatial analytical approach will cover three main health planning issues. These issues are tackling health inequalities through geospatial monitor for inequalities in distribution of health units and its services, support decision-making with predictive analytics for common health indicators, and geoprocessing for input layers through dynamic health map and motion charts to support decision making.
Highlights
The proposed spatial analytical approach will cover three main health planning issues. These issues are tackling health inequalities through geospatial monitor for inequalities in distribution of health units and its services, support decision-making with predictive analytics for common health indicators, and geoprocessing for input layers through dynamic health map and motion charts to support decision making
This paper shows that combining is the strength in predicate analysis and the ease of use makes the proposed approach ideal for healthcare professionals without extensive computer skills
The maps resulting from the proposed approach will provide decision makers with information to strengthen their disaster management capacity
Summary
BI and GIS technologies have followed separate development and implementation paths [10].Decision makers in health sector request for a more complete operational picture and the ability to be more proactive have led to the combination of these two technologies to have suitable tool for Decision Support System (DSS). A modern and effective spatial DSS having all the requisite support technologies like online analytical processing (OLAP), specialized analysis and reporting is required for future planners and decision makers; new and efficient methods are needed to integrate the related Information technologies to discover knowledge from large spatial databases [21]. OLAP and GIS system combined to develop the Spatial OLAP Visualization and Analysis Tool (SOVAT) which currently used to solve problems that faces decision maker at health sector as shown in Fig. 1[21]. Individuals who use decision support technology need a system that is capable of supporting the development of numerical-spatial routines integrated with predictive analytical tool. There is no alternative technology that could simulate this process It must be coupled with a BI that can, by itself, support development of powerful temporal-numerical routines [21]. The potential of this synergy is an approach that can significantly enhance spatial, temporal and numerical problem solving through predicative concept
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