The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Creating Value In Health Care Through Big Data: Opportunities And Policy Implications
Abstract
Big data has the potential to create significant value in health care by improving outcomes while lowering costs. Big data's defining features include the ability to handle massive data volume and variety at high velocity. New, flexible, and easily expandable information technology (IT) infrastructure, including so-called data lakes and cloud data storage and management solutions, make big-data analytics possible. However, most health IT systems still rely on data warehouse structures. Without the right IT infrastructure, analytic tools, visualization approaches, work flows, and interfaces, the insights provided by big data are likely to be limited. Big data's success in creating value in the health care sector may require changes in current polices to balance the potential societal benefits of big-data approaches and the protection of patients' confidentiality. Other policy implications of using big data are that many current practices and policies related to data use, access, sharing, privacy, and stewardship need to be revised.
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Cites
Porter, M. E. (2010) · New England Journal of Medicine · doi:10.1056/nejmp1011024 · Cited by 5,084
Americans Do IT Better: US Multinationals and the Productivity Miracle
Bloom, N., Sadun, R., & Reenen, J. V. (2012) · American Economic Review · doi:10.1257/aer.102.1.167 · Cited by 1,028
From genetic privacy to open consent
Lunshof, J. E., Chadwick, R., Vorhaus, D. B., & Church, G. M. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2360 · Cited by 464
The Anatomy of Health Care in the United States
Moses, H., Matheson, D. H. M., Dorsey, E. R., George, B. P., Sadoff, D., & Yoshimura, S. (2013) · JAMA · doi:10.1001/jama.2013.281425 · Cited by 327
Web-scale pharmacovigilance: listening to signals from the crowd
White, R. W., Tatonetti, N. P., Shah, N. H., Altman, R. B., & Horvitz, E. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001482 · Cited by 199
Cusack, C. M., Hripcsak, G., Bloomrosen, M., Rosenbloom, S. T., Weaver, C. A., Wright, A., Vawdrey, D. K., Walker, J., & Mamykina, L. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001093 · Cited by 103
Early Results of the Meaningful Use Program for Electronic Health Records
Wright, A. T., Henkin, S., Feblowitz, J. C., McCoy, A. B., Bates, D. W., & Sittig, D. F. (2013) · New England Journal of Medicine · doi:10.1056/nejmc1213481 · Cited by 96
Cited by
Medical big data: promise and challenges
Lee, C. H., & Yoon, H.-J. (2017) · Kidney Research and Clinical Practice · doi:10.23876/j.krcp.2017.36.1.3 · Cited by 594
Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology
Wiens, J., & Shenoy, E. S. (2018) · Clinical Infectious Diseases · doi:10.1093/cid/cix731 · Cited by 574
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
Li, X., Gu, Y., Dvornek, N., Staib, L. H., Ventola, P., & Duncan, J. S. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101765 · Cited by 480
Exploring the path to big data analytics success in healthcare
Wang, Y., & Hajli, N. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.08.002 · Cited by 429
Metadata
- Authors
- Roski, J., Bo-Linn, G. W., & Andrews, T. A.
- Venue
- Health Affairs
- Publisher
- Health Affairs Publishing, LLC
- Published
- 2014-07
- Volume
- 33
- Issue
- 7
- Pages
- 1115-1122
- ISSN
- 0278-2715 (ISSN-L)
- 1544-5208
- OpenAlex
- W2144148628
- Cited by
- 320
- References
- 7
- FWCI
- 54.48
- Type
- journal article
- Language
- en
- Open access
- closed
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- Roski, J., Bo-Linn, G. W., & Andrews, T. A. (2014). Creating Value In Health Care Through Big Data: Opportunities And Policy Implications. Health Affairs. https://doi.org/10.1377/hlthaff.2014.0147
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
