Health sector and application of big data: A case study of India

Aim: The paper aims to study and present the case study of the health sector of India. The paper also aims to identify the opportunities for the application of Big data in the health sector. The major stakeholders of the system viz. doctors, hospitals, clinics, insurance companies, pharmaceutical companies, research, and development organizations, industries manufacturing medical instruments, laboratories, medical data analysts, and many more are utilizing big data and predictive analytics in their critical decision making. The predicted revenue was expected to reach 280 billion by 2020 as per the statistics given by the Indian Brand Equity Foundation. Research methods: A critical review has been conducted using electronic sources between 2015 and 2020, limited to English language articles and reports published from 2015 onwards. The reviews will be classified to identify the opportunities for future application of Big Data. Conclusions: The paper presents a trend in the use of Big Data Analysis in the health sector. The paper also explores and identifies the areas of future application of big data to increase the efficacy of the system. Originality/value of the article: This is an original piece of article in the context of India in terms of documenting the big data applications in the health sector and identifying the opportunities for the future application of the same. Implications of the research: This research holds a significant contribution towards the implications of the application of Big Data in the health sector. The newly identified areas of the health sector, which can be improved by using the big data analytics, are important for the policy makers of the organizations, including the Government. Limitations of the research: The research has been conducted based on the secondary data, which area available in the public domain. However, due to COVID 19, there could have been more innovations in the health sector in terms of using the big data, which may not have been published or are available in the public domain. Also, collection of the primary data in terms of an interview with the administrators/management can be explored in the future study.