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Big data analytics in health: an overview and bibliometric study of research activity
Author(s) -
Galetsi Panagiota,
Katsaliaki Korina
Publication year - 2020
Publication title -
health information and libraries journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.779
H-Index - 38
eISSN - 1471-1842
pISSN - 1471-1834
DOI - 10.1111/hir.12286
Subject(s) - scopus , data science , big data , analytics , health informatics , bibliometrics , field (mathematics) , computer science , knowledge management , citation , medline , medicine , medical education , world wide web , public health , data mining , political science , pathology , mathematics , pure mathematics , law
Objective The study presents an overview of the research activity in Big Data Analytics (BDA) in the field of health and demonstrates the existing knowledge through related examples. The objective is to inform health librarians about the nature and magnitude of the technological innovations in health information analysis tools, its influence, and where and how further material could be searched. Methods We performed a bibliometric and co‐citation analysis within a total of 804 papers published between 2000 and 2016 and retrieved from the Web of Science and Scopus databases. Using the NVivo text analysis software, we identified the stakeholders of BDA in health and innovative decision support systems in the field. Results Our findings show a tremendous increase in published papers after 2014. Most of them are relevant to neurology and medical oncology. The stakeholders are clinicians, researchers, patients, administrators, IT specialists, vendors and policymakers. New BDA tools in medicine are mostly developed for disease monitoring purposes while they utilise visualisation to identify disease patterns and statistical analysis of past data for making predictions. Conclusions Health analytics provide a unique opportunity for advancing health information research and medical decision making. It provides health information professionals with new tools in problem‐solving offering new perspectives in prognosis and diagnosis of diseases.