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September 16, 2016
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Hadoop for Health Insurance: Hortonworks-Knowledgent: Partnering for Success with Payers!

Hadoop for Health Insurance:

The future of the healthcare industry rests in the promise of collecting, analyzing and taking action on the output of larger amounts of information. Through the advancements in big data, machine learning and advanced analytics, healthcare organizations can leverage and manipulate data to improve overall member health, reduce costs, improve quality and manage clinical and financial risk.

Market Leaders are Performing Advanced Analytics on Hadoop

For early-adopting enterprises, the value behind Hadoop’s next- generation architecture rests in the fact that it stages and enables big data to be used for advanced analytic use cases. As Data Science matures, more and more enterprises are turning towards machine learning techniques commonly known as predictive and prescriptive analytics to automate and improve analytical decision-making. Predictive and prescriptive analytics, when performed on a Hadoop ecosystem, allow organizations to correlate large and valuable data sets with future outcomes, use current and historical data to predict which outcomes will occur next, and suggest the optimal action that should be undertaken based upon the predicted outcomes as well as the costs and constraints of each action.

Partnering for Success

Knowledgent and Hortonworks have partnered on numerous programs to enable healthcare organizations to drive advanced analytic insights from their large stores of data. These projects have included the instantiation of a Hortonworks Hadoop Data Lake along with other components of the big data ecosystem.

The two Data Science projects listed below were jointly deployed at top-3 health insurance companies:

  • Increasing Risk-Adjusted Revenue: One of the nation’s largest payers sought to improve their Risk-Adjusted (RAPS) Revenue by understanding which members have an unreported disease condition that would increase their Risk Score. Using machine-learning analytics, Knowledgent narrowed down the client’s substantial pool of Medicare Advantage members into the small subset with the highest ROI for RAPS chart chasing pursuits, uncovering a potential 8-figure revenue lift.
  • Member Segmentation: One of the most powerful and well-known use cases of machine learning technology is the ability to segment members into cohorts, or groups sharing similar characteristics. Knowledgent has worked with a number of clients to segment their members into cohorts, and then to identify the optimal channel and messaging for intervention for each member segment. This optimizes spend on outreach for marketing, customer experience, and care delivery, by targeting the intervention. These programs have succeeded in increasing Member engagement rates by over 99%.

“The advancements of big data technology are allowing for a much larger set of capabilities to be deployed to Hadoop environments. Our Partnership and collaboration with Hortonworks has been a testament to these new capabilities and have allowed a number of our Payer clients to realize tremendous operational savings and revenue enhancements.”

Matthew Arellano, Healthcare Portfolio Partner, Knowledgent

The Future of Healthcare IT will be Built on Hadoop

Knowledgent and Hortonworks see a future of Healthcare IT involving deriving value from Internet of Things streaming data feeds, the expansion of machine learning to foster deep learning through neural networks and cognitive computing, and secure, transactional blockchain technologies that provide the necessary balance between security and distribution of personal health data. Each of these innovations will exponentially increase the volume of data being analyzed, the speed in which the data is coming in, and the processing power that is required to compute the data. The result will be increased enterprise reliance on the next-generation Hadoop ecosystem in order to cost-effectively manage data with these complex requirements.

“Previously, many of the use cases providing a competitive advantage to our Payer customers were not possible both technically (due to the size and variety of data) and economically (due to the cost of storing and processing data). Hortonworks’ partnership with Knowledgent has enabled leading Payers to take advantage of the power of Hadoop architecture’s in combination with partners with proven industry knowledge.”

Richard Proctor, GM Global Healthcare, Hortonworks

 Conclusion

The current Hadoop environment is built to support many of the advanced analytics needs of today’s healthcare enterprises. When considering the potential value that can be ascertained from advanced analytics it is not surprising that the analytics industry is vastly growing. In the current state, machine learning and enterprise search are pioneering advanced analytics. The future state will evolve advanced analytics and empower the IoT movement, cognitive computing and deep learning, and blockchain infrastructure. However, before jumping into the world of advanced analytics and it’s large data sets on which it relies, it’s critical to start with a foundational infrastructure that is robust enough to handle high volumes of data being landed at a high velocity with large variances in formatting.

Knowledgent & Hortonworks will be exhibiting at the IM Symposium in Detroit September 25th-28th. http://www.imsymposium2016.com/

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