Best Practices for Data Convergence in Healthcare

Predictive & Prescriptive Analytics for Payers and Providers

Is your organization at the analytics crossroads? Have you made strides collecting and sharing massive amounts of data from electronic health records, insurance claims, and health information exchanges but found these efforts made little impact on efficiency, patient outcomes, or costs?

Analytics is the missing link to make sense of the volume of data generated during the delivery of healthcare. Cognizant and MapR have built a framework for ingesting, linking, and enriching this data to fuel analytics, enabling dramatic improvements in healthcare. By addressing common issues such as readmissions, payment fraud, and claims inefficiency, companies can save hundreds of millions of dollars and, more importantly, significantly improve patient health.

On Wednesday, May 17, 2017 experts from Cognizant and MapR discussed the following:

  • Analyzing new data sources using big data workflows to make faster decisions that improve patient health
  • Using streams to support event-driven care and real-time detection of claims fraud
  • Identifying new methods of analyzing data, such as image classification and graph analysis, to lower readmission rates and prevent disease

Additional Resources


Jack Norris Big Data Strategy & Solutions Cognizant

Sameer Nori SVP, Data and Applications MapR

Joe Blue Director of Data Science MapR