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Cited by 178

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

Srinivasan, Uma, Arunasalam, Bavani·2013·IT Professional

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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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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CoChat. (2026). Citation check: Leveraging Big Data Analytics to Reduce Healthcare Costs. https://app.cochat.ai/papers/10.1109/mitp.2013.55
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Srinivasan, U., & Arunasalam, B. (2013). Leveraging Big Data Analytics to Reduce Healthcare Costs. IT Professional. https://doi.org/10.1109/mitp.2013.55

Data sources

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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.