The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Leveraging Big Data Analytics to Reduce Healthcare Costs
Abstract
The healthcare sector deals with large volumes of electronic data related to patient services. This article describes two novel applications that leverage big data to detect fraud, abuse, waste, and errors in health insurance claims, thus reducing recurrent losses and facilitating enhanced patient care. The results indicate that claim anomalies detected using these applications help private health insurance funds recover hidden cost overruns that aren't detectable using transaction processing systems. This article is part of a special issue on leveraging big data and business analytics.
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Cites
Business intelligence and analytics: from big data to big impact
Chen, H., Chiang, R. H. L., & Storey, V. C. (2012) · MIS Quarterly · doi:10.2307/41703503 · Cited by 6,250
Cited by
Wang, Y., Kung, L., & Byrd, T. A. (2018) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2015.12.019 · Cited by 1,571
How to improve firm performance using big data analytics capability and business strategy alignment?
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016) · International Journal of Production Economics · doi:10.1016/j.ijpe.2016.08.018 · Cited by 1,624
Big data analytics in supply chain management between 2010 and 2016: Insights to industries
Tiwari, S., Wee, H. M., & Daryanto, Y. (2018) · Computers & Industrial Engineering · doi:10.1016/j.cie.2017.11.017 · Cited by 582
An integrated big data analytics-enabled transformation model: application to health care
Wang, Y., Kung, L., Wang, W. Y. C., & Cegielski, C. G. (2018) · Information & Management · doi:10.1016/j.im.2017.04.001 · Cited by 508
Aceto, G., Persico, V., & Pescapé, A. (2018) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2018.02.008 · Cited by 504
Metadata
- Authors
- Srinivasan, U., & Arunasalam, B.
- Venue
- IT Professional
- Published
- 2013-11
- Volume
- 15
- Issue
- 6
- Pages
- 21-28
- ISSN
- 1520-9202 (ISSN-L)
- OpenAlex
- W1984111244
- Cited by
- 178
- References
- 1
- FWCI
- 33.91
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
