| Literature DB >> 31585681 |
P Galetsi1, K Katsaliaki2, S Kumar3.
Abstract
The emergence of powerful software has created conditions and approaches for large datasets to be collected and analyzed which has led to informed decision-making towards tackling health issues. The objective of this study is to systematically review 804 scholarly publications related to big data analytics in health in order to identify the organizational and social values along with associated challenges. Key principles of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology were followed for conducting systematic reviews. Following a research path, we present the values, challenges and future directions of the scientific area using indicative examples from relevant published articles. The study reveals that one of the main values created is the development of analytical techniques which provides personalized health services to users and supports human decision-making using automated algorithms, challenging the power issues in the doctor-patient relationship and creating new working conditions. A main challenge to data analytics is data management and security when processing large volumes of sensitive, personal health data. Future research is directed towards the development of systems that will standardize and secure the process of extracting private healthcare datasets from relevant organizations. Our systematic literature review aims to provide to governments and health policy-makers a better understanding of how the development of a data driven strategy can improve public health and the functioning of healthcare organizations but also how can create challenges that need to be addressed in the near future to avoid societal malfunctions.Entities:
Keywords: Big data analytics; Decision-making; Health-medicine; Organizational and societal values; Preferred reporting items for systematic reviews and meta-analyses; Systematic review
Year: 2019 PMID: 31585681 DOI: 10.1016/j.socscimed.2019.112533
Source DB: PubMed Journal: Soc Sci Med ISSN: 0277-9536 Impact factor: 4.634