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Milliman MedInsight Announces Big Data Initiative

Data Confidence Model is optimized to give healthcare data miners better access to big data

MedInsight tops 15 billion healthcare records, 126 million healthcare members


News provided by

Milliman, Inc.

Sep 23, 2013, 08:00 ET

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SEATTLE, Sept. 23, 2013 /PRNewswire/ -- Milliman, Inc., one of the premier global consulting and actuarial firms, announced today the formal launch of a big data initiative. The MedInsight Data Confidence Model is a data management methodology that helps clients leverage concepts of big data for business performance improvement and transparency.

MedInsight is Milliman's popular healthcare analytic platform used by over 200 health plans, employers, at-risk providers/ACOs, state governments, community health coalitions, and third party administrators. Consistently recognized for its superior data integration and warehousing capabilities, MedInsight has continually developed and perfected its Data Confidence Model since 1997.

The MedInsight Data Confidence Model is applied as a client data warehouse is being created, and it is then leveraged on an ongoing basis for client data management. It includes both automated and manual processes to identify anomalies or irregularities in client data sets. Milliman aggregates data in innovative ways and compares the results against ranges of quality norms Milliman has developed over 15 years. Much like a lab test, each data metric in client data sets has a normal range. Results outside those norms often indicate a need for further investigation and/or remediation. The Data Confidence Model helps with common big data issues such as:

  • Inconsistencies in how data was formatted and entered
  • Relational integrity problems between components of the data
  • Data volume consistency issues
  • Duplication of data
  • Integration and cross walking of data from multiple data source providers
  • Reasonableness of the metrics created by the system

Successful management of healthcare cost and quality for a single organization requires transparency into cost and quality data. In order to be effective, transparency requires integration of large volumes of high-quality and timely data – key components of the big data movement.  The complexity of big data requires advanced data integration and quality assurance techniques in order for the underlying information to be reliable.

"MedInsight's business has grown dramatically over the past four years, and we now maintain and process more than 15 billion healthcare records for 126 million healthcare members," said Kent Sacia, Milliman Principal and MedInsight's founder. "Supporting one of the largest healthcare claim data sets in the U.S. requires sophisticated data management techniques. Our MedInsight Data Confidence Model gives clients the confidence they need to rely on the data and information within their MedInsight data warehouses," added Sacia.

The MedInsight Data Confidence Model is a critical component to help tackle the most difficult challenge of healthcare analytics – giving companies high confidence in making decisions by ensuring that the data that goes into the system is accurate.

For more information about Milliman's MedInsight products, go to http://www.medinsight.milliman.com.

About Milliman
Milliman is among the world's largest providers of actuarial and related products and services. The firm has consulting practices in healthcare, property & casualty insurance, life insurance and financial services, and employee benefits. Founded in 1947, Milliman is an independent firm with offices in major cities around the globe. For further information, visit milliman.com

SOURCE Milliman, Inc.

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