Provider Data - HealtheConnections

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New York Sate
Practitioner Database Project
Provider Data Validation
Presented by:
Josh Schoeller, Vice President, Chief Solutions Architect
LexisNexis
February 24, 2014
Confidential Proprietary information – Not for Distribution
Problem to be Addressed: New York State does not have a comprehensive
physician or mid-level practitioner database. The current process of gathering
such information is arduous and complicated requiring users to examine
multiple local, state, and national data sources, often followed by surveys and
telephone contacts with offices, hospitals, and other entities. The need for a
common, integrated, practitioner database is greater than ever, particularly as
the state addresses the implications of federal and state reforms that will
significantly increase the demand for primary care and other services.
Gartner: "Big data are high volume, high velocity, and/or high variety
information assets that require new forms of processing to enable enhanced
decision making, insight discovery and process optimization."
Data growth challenges and opportunities are
three-dimensional:



Volume (amount of data)
Velocity (speed of data in and out)
Variety (range of data types and sources)
The necessity: to create and have access to actionable data
Confidential Proprietary information – Not for Distribution
Provider data
impacts
everything
Claims
Processing
Provider
Directories
Retention
Member
and
Provider
Satisfaction
Network
Management
At the
center of
payer
operations
Provider
EPS
Data
Financial
Accuracy
Returned
Mail and
Mailing
Aggregation
Data
Warehouse
and
Reporting
Credentialing
3
Fraud
Detection
Compliance
and
Accreditation
Customer
Service
Confidential Proprietary information – Not for Distribution
Provider data is changing all the time
The provider universe is always
changing

2.5% of provider demographics
change each month

30% of doctors change their
affiliations each year

5% of doctors change their status
each year
The pace of business leads to
additional inaccuracies

Human errors in data entry

Multi-channel delivery of incoming
transactions with errors or omissions

Data integration challenges across
data sources / organizational silos
Provider demographic data quality degrades rapidly
100%
Bad
50%
0%
Months
4
Good
3
6
9
12
15
Confidential Proprietary information – Not for Distribution
18
How is provider data being managed today?
Provider
Reported
Changes
Claims
External
Provider
Data
Files
Audit /
Re-credentialing
Provider
File
Cred / New
Providers
Reactive provider data management
5
Confidential Proprietary information – Not for Distribution
Taking a different path
6

Best practice to create a single source of truth or
Enterprise Provider Data Master

Leveraging referential data to continuously validate
provider information improves accuracy and results

Systematic updates allow resources to be redirected
from manual validation and data entry

Focusing resources on significant changes in data
speeds updates to internal provider databases
Confidential Proprietary information – Not for Distribution
Next generation provider data model
Credentialing
Information
Claims
Data
Provider
Feedback
External
Provider
Variables
Member
Feedback
Cost & Quality
Information
Enterprise Provider Data Master
(Integration and Meta Layer)
Health
Benefit
Exchange
Member
Engagement
APCD
7
MMIS
Network
Optimization
Reduced
Costs
Fraud,
Waste and
Abuse
Provider
Performance
Optimize
Quality of
Care
Enhanced
Member
Loyalty
Confidential Proprietary information – Not for Distribution
Clinical
Analytics
Operational
Efficiencies
Questions and Answers
Confidential Proprietary information – Not for Distribution
Better provider information. Right now.®
For more information
contact:
Mark Biddle
Senior Director, Sales
978-475-1551
[email protected]
Confidential Proprietary information – Not for Distribution
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