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© 2017 SCIO Health Analytics®. All rights reserved.
433 South Main St., Suite 203, West Hartford, CT 06110P: 1.860.676.8808 | F: 1.860.676.8848
E: info@SCIOhealthanalytics.comwww.sciohealthanalytics.com
LEVEL OF SOPHISTICATED USE OF ANALYTICS/DATA
TYPES OF ANALYTIC RESOURCES USED
Survey reveals organizations rely on narrow swatch of data, thus creating a big hurdle in effectively predicting and preventing claim FWA with advanced profiling & analytics.
SURVEY RESULTS
BIG DATA CHALLENGES
SOURCES OF DATA USED TO IDENTIFY POTENTIAL FWA PATTERNS1
2
3
CLAIMS DATA PROVIDER DEMOGRAPHICS
MEMBER DEMOGRAPHICS
BEHAVIORAL/ATTITUDINAL DATA
OTHERS
98% 68% 51% 31% 31%
ADVANCEDOUTCOMES REALIZED FROM MULTI SOURCE
DATA
IN PROGRESSIMPLEMENTING A VARIETY OF MULTI
SOURCE DATA
EARLY ONCONSIDERING USE OF
NON TRADITIONAL ANALYTICS / DATA
NOT SURE
35% 34% 17% 14%
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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
INTERNAL TEAM + EXTERNAL VENDOR TOOL
INTERNAL TEAM NOT SURE EXTERNAL VENDOR TOOL. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
?
51% 34%
8% 7%
Source: SCIO-led webinar titled ‘Predicting and Preventing Claim Fraud, Waste and Abuse with Advanced Profiling & Analytics’.
Even though FWA is a growing challenge, nearly all of the respondents rely on claims data (98%) to identify potential FWA patterns while far fewer leverage other types of information.
Organizations are still not optimally using a full range of data – as only 35% of poll participants cited realizing FWA outcomes from multi-source data.
About half of all respondents use a combination of internal teams and external vendor tools in the FWA efforts, which means that about half either are not sure of what their organizations use or don’t use either. This hampers the efficient use of available data.
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