2020 EDSIG Proceedings: Abstract Presentation

Interdisciplinary Evaluation of Big Data Analytics in Healthcare: A Systematic Literature Review

Rachida Parks
Quinnipiac University

Zhuoqi Dong
Quinnipiac University

Abstract
There is no doubt that analytics provide stakeholders with the ability to go beyond reducing costs to enabling epidemic predictions, reducing preventable deaths, and improving quality of life. This is why healthcare organizations feel an urgency to embrace a digital transformation that relies on robust analytics capabilities to stay relevant and competitive. However, due to the fragmented nature of the healthcare sector, most analytics initiatives operate, unfortunately in silos. The growing and largely unstructured and scattered literature across various academic disciplines calls for a systematic literature review to assess the current state of the literature, identify gaps, and outline future research directions. For this systematic literature review, we follow processes and guidelines that are replicable, transparent and rigorous (Watson 2015). Using PubMed, Science Direct, CINAHL, EBSCO, Emerald, ProQuest/ABI inform Collection, Academic Search Complete, ACM, and Google Scholar, we conducted a systematic literature search of peer-reviewed journals published between 2010 and 2020. We searched titles, abstracts, and keywords for the terms: ("big data" OR “analytics”) AND (“medical” OR “healthcare”). Screening identified 1236 entries. All entries were imported into the RefWorks, a citation management software. We used RefWorks to store the articles and Excel for the analysis. This working paper identifies five themes: 1) Healthcare analytics application areas which include pandemic and disease prevention, cost reduction and error minimization, and hospitals and public health operations and practices; 2) Healthcare analytics challenges & concerns that encompass data quality and storage; Security, privacy, ethics and risk analytics; data processing and lack of actionable knowledge; 3) Tools and methods technology which includes types of analytics approaches (descriptive, predictive, diagnostic and prescriptive analytics), big data analytics platforms, and common big data analytics tools and technologies; 4) Healthcare analytics curriculum and; 5) Healthcare analytics in developing countries. This study represents a major step toward a better understanding of data analytics in field of healthcare. The role of big data analytics in healthcare have been constantly evolving. Big data analytics is more than the technical application of analytical tools. Effective big data analytics require successful application of several complex factors. If any one of these factors are overlooked or if their application is poorly executed, failure can ensure. These factors include but are not limited to an analytics strategy, analytics translators, leadership, analytics platform, or potential ethical, social, and regulatory implications. This current review defines the current state of the literature and proposes a bold research agenda that provides researchers and practitioners with insights towards specifics opportunities for new research in healthcare analytics.