Shipi Kankane
Prashanth Nakirekommula
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Applying analytics and risk- management capabilities to health
insurance through LexisNexis data platforms.
Databases on 250 million people in the U.S. sampled from 35 billion
public records.
Data analysis using its supercomputer platform, which is built on
top of open-source platform (High Performance Computing Cluster)
Allows for fast queries of "massive amounts of big data.”
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Earlier Situation: Pay and Chase model insufficient and unsustainable
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Current Solution:
◦ Proactive - identifies and mitigates fraud throughout
business workflow
◦ Identify fraud patterns and risk indicators as they
emerge.
Traditional Method:
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Single claim
Claim Edit
No pattern identification
Predictive Modeling
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Metrics
Scores
Detect inherent risks
Definition: Predictive Analysis translates data
into descriptive or predictive models using
various forms of statistical analysis techniques
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Classification and Regression Trees (CART)
Chi Square Automatic Interaction Detection
(CHAID) .
Linear and logistic regression models
Analysis of variance
Discriminate analysis.
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Early detection of fraud, waste and abuse
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Prioritized results with fewer false positives
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Alerts concerning adverse changes in the status of
individuals or entities
Consistent control over risk, quality and costs using
automated screening and monitoring
Lower claims losses, better financial management than
traditional “post-payment only” methods
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Understand your data –
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Determine your population makeup –
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Discover relationships in your data –
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Build a model –
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Use model against actual records –
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Identify anomalies –
Information etc.
Patient demographics, Hospital
issues, representativeness
between various variables identified in Step 1
Sampling
Relations
Rule induction and based on step 3
predictive power
Outliers
Test for
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SAS datamining tool – tree based model ,
multianalytics approach
IBM SPSS modeler – rule induction
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Neil Versel , Data Mining Snares Health Insurance
Fraud, InformationWeek , November 15 ,2011
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LexisNexis® Health Care Solutions for Fraud, Waste and
Abuse Prevention retrieved from lexisnexis.com
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HPCC Systems (www.hpccsystems.com)
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IBM Software Business Analytics, IBM Corporation, May
2011