Big Data in Healthcare Research: A survey study

ABSTRACT

The purpose of this study is to present a literature review that provides in-depth analytical insight into big data in health care. This was addressed by achieving three things: (a) identifying the key topics addressed in existing big data research in health care, (b) measuring associations between topics in existing studies, and (c) constructing time series profiles for the various topics addressed in big data and healthcare research. Going beyond the common review methodologies in this domain, we introduce a comprehensive literature survey methodology, based on systems theory and PRISMA framework. Using the survey methodology, 2,941 research articles that were published between 2012 and 2019 were analyzed to both synthesize and develop the findings presented in this study. Based on this study’s findings, a comprehensive overview of researchers’ interest toward different methodologies, technologies and subject areas is provided, which include the identification of substantial gaps in research for further development.

KEYWORDS:

• Big data
• healthcare
• topic modeling
• non-negative matrix factorization
• review study