The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Challenges and Opportunities of Big Data in Health Care: A Systematic Review
Open accessAbstract
BACKGROUND: Big data analytics offers promise in many business sectors, and health care is looking at big data to provide answers to many age-related issues, particularly dementia and chronic disease management. OBJECTIVE: The purpose of this review was to summarize the challenges faced by big data analytics and the opportunities that big data opens in health care. METHODS: A total of 3 searches were performed for publications between January 1, 2010 and January 1, 2016 (PubMed/MEDLINE, CINAHL, and Google Scholar), and an assessment was made on content germane to big data in health care. From the results of the searches in research databases and Google Scholar (N=28), the authors summarized content and identified 9 and 14 themes under the categories Challenges and Opportunities, respectively. We rank-ordered and analyzed the themes based on the frequency of occurrence. RESULTS: The top challenges were issues of data structure, security, data standardization, storage and transfers, and managerial skills such as data governance. The top opportunities revealed were quality improvement, population management and health, early detection of disease, data quality, structure, and accessibility, improved decision making, and cost reduction. CONCLUSIONS: Big data analytics has the potential for positive impact and global implications; however, it must overcome some legitimate obstacles.
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Cites
Big data analytics in healthcare: promise and potential
Raghupathi, W., & Raghupathi, V. (2014) · Health Information Science and Systems · doi:10.1186/2047-2501-2-3 · Cited by 3,034
Hillestad, R., Bigelow, J., Bower, A., Girosi, F., Meili, R., Scoville, R., & Taylor, R. (2005) · Health Affairs · doi:10.1377/hlthaff.24.5.1103 · Cited by 1,675
Mohr, D. C., Burns, M. N., Schueller, S. M., Clarke, G., & Klinkman, M. (2013) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2013.03.008 · Cited by 693 · cited 10×
“It enables providers to track healthy behaviors and helps patients in monitoring their respective conditions [25,32,33].”
BackgroundInfluentialBaker, T. B., Gustafson, D. H., & Shah, D. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.2925 · Cited by 221
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The practical implementation of artificial intelligence technologies in medicine
He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019) · Nature Medicine · doi:10.1038/s41591-018-0307-0 · Cited by 2,246
The use of Big Data Analytics in healthcare
Batko, K., & Ślęzak, A. (2022) · Journal of Big Data · doi:10.1186/s40537-021-00553-4 · Cited by 593
Concurrence of big data analytics and healthcare: a systematic review
Mehta, N., & Pandit, A. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.03.013 · Cited by 494
Big Data and Machine Learning Based Secure Healthcare Framework
Kaur, P., Sharma, M., & Mittal, M. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2018.05.020 · Cited by 218
Artificial Intelligence in U.S. Health Care Delivery
Sahni, N. R., & Carrus, B. (2023) · New England Journal of Medicine · doi:10.1056/nejmra2204673 · Cited by 175
Metadata
- Authors
- Kruse, C. S., Goswamy, R., Raval, Y., & Marawi, S.
- Venue
- JMIR Medical Informatics
- Publisher
- JMIR Publications Inc.
- Published
- 2016-11-21
- Volume
- 4
- Issue
- 4
- Pages
- e38
- ISSN
- 2291-9694 (ISSN-L)
- OpenAlex
- W2549346488
- Cited by
- 394
- References
- 4
- FWCI
- 9.74
- Type
- journal article
- Language
- en
- Open access
- gold
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