The World Health Organisation estimates that 92 per cent of the world’s population does not have access to clean air. The World Bank in 2013 estimated that only air pollution (AP) was responsible for a $225bn cost in lost productivity. The purpose of this paper is to contribute to the current scholarly debate on the value of Big Data for effective healthcare management. Its focus on cardiovascular disease (CVD) in developing countries, a major cause of disability and premature death and a subject of increasing research in recent years, makes this research particularly valuable.
In order to assess the effects of AP on CVD in developing countries, the city of Bangalore was selected as a case study. Bangalore is one of the fastest growing economies in India, representative of the rapidly growing cities in the developing world. Demographic, AP and CVD data sets covering more than 1m historic records were obtained from governmental organisations. The spatial analysis of such data sets allowed visualisation of the correlation between the demographics of the city, the levels of pollution and deaths caused by CVDs, thus informing decision making in several sectors and at different levels.
Although there is increasing concern in councils and other responsible governmental agencies, resources required to monitor and address the challenges of pollution are limited due to the high costs involved. This research shows that with developments in the domains of Big Data, Internet of Things and smart cities, opportunities to monitor pollution result in high volumes of data. Existing technologies for data analytics can empower decision makers and even the public with knowledge on pollution. This paper has demonstrated a methodological approach for the collection and visual representation of Big Data sets allowing for an understanding of the spread of CVDs across the city of Bangalore, enabling different stakeholders to query the data sets and reveal specific statistics of key hotspots where action is required.
This research has been conducted to demonstrate the value of Big Data in generating a strategic knowledge-driven decision-support system to provide focused and targeted interventions for environmental health management. This case study research is based on the use of a geographic information system for the visualisation of a Big Data set collected from Bangalore, a region in India seriously affected by pollution.
Chinnaswamy, A., Papa, A., Dezi, L. and Mattiacci, A. (2019), "Big data visualisation, geographic information systems and decision making in healthcare management", Management Decision, Vol. 57 No. 8, pp. 1937-1959. https://doi.org/10.1108/MD-07-2018-0835
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