EVALUATING THE IMAGE OF HEALTHCARE HUBS ONLINE – A CROSS SECTIONAL ANALYSIS OF GOOGLE AND FACE BOOK REVIEWS OF PRIVATE HOSPITALS OF KOLKATA, EASTERN INDIA
The purpose of this paper is to map perceived image of major healthcare hubs of Kolkata, Eastern India. Kolkata as the gateway of Eastern India is a favourite destination among the migrating patients of South Asia while travelling outside the city to access better healthcare opportunity is the common among locales of the city. Acknowledging the significance of crowed-sourced platform and significance of social media data mining this study examines the differences among the perception between medical tourists and local visitors seeking healthcare at the major hospitals of the Kolkata, Eastern India. This study used both quantitative and qualitative data to identify the virtual image of the major healthcare hubs of the Kolkata. Through extensive field visit the major medical hubs of the city has been demarcated. The Google and Facebook reviews of these individual hospitals have been collected for the period 2013–2017 for the detailed analysis. Perceptions of both inbound medical tourists and local visitors have been taken into consideration to evaluate the online image of the major medical tourism hubs of the city. The results reveals the significance of the social data mining in evaluating the quality healthcare infrastructure of the city. The growing field of medical tourism around the world has high demand for database to formulate public policy and to deliver high service quality to the medical travellers without compromising the need of neighbourhood community. This study uniquely highlights the dual role of internet and GIS that could together strengthen the medical tourism information system for the prospective consumer and at the same time provides significance of the crowd-sourced database with field validation that could be used by professionals and policy maker for sustenance of medical tourism which will strengthen the healthcare sector of the city in long run.