Analyzing Two and a Half Decades of Health Insurance and Big Data Analytics Research: A Bibliometric Study

Abstract

Purpose: Health insurance and big data analytics have become increasingly intertwined in recent years, offering both opportunities and challenges for the industry. Thus, the primary aim is to utilize bibliometric analysis for comprehensive literature reviews in health insurance and big data analytics.

Design/methodology/approach: Scopus, chosen for its broad coverage, is utilized to extract 493 manuscripts meeting the inclusion criteria set (year and language) for a 25-year period. The tools employed in the study include VOSViewer and Biblioshiny package (R-programming).

Findings: An emerging trend has been observed in the field of health insurance and big data analytics for 25 years. The US has been observed as the topmost leading country to contribute to the subject under study. The Ministry of Science and Technology of Taiwan is at the top first rank of top leading institutions contributing 20 documents to the field of health insurance and big data analytics. Moreover, thematic mapping and word cloud is done to find the most relevant keywords in the study. Furthermore, co-occurrence analysis revealed the relationship of keywords for health insurance and big data mining.

Implications: The implications of the research extend beyond academic insights and have practical implications for stakeholders involved in healthcare policy, practice, and research.

Originality/Value/Implications: The novelty in the manuscript has been brought in by focusing on one of the many types of insurance, i.e., health. Moreover, big data analytics in relation to health insurance for such a range of time period serves as the original presentation of the work with regards to the matter under study.

Citation

Bisht, V., Priya, , Taneja, S. and Johri, A. (2024), "Analyzing Two and a Half Decades of Health Insurance and Big Data Analytics Research: A Bibliometric Study", Taneja, S., Kumar, P., Reepu, Kukreti, M. and Özen, E. (Ed.) Data Alchemy in the Insurance Industry, Emerald Publishing Limited, Leeds, pp. 49-64. https://doi.org/10.1108/978-1-83608-582-920241010