eviCore Benefits from Advanced Data Analysis
Dramatic process improvements and easier, faster analytical models
There is an extraordinary amount of data associated with benefits management in healthcare. From medical procedures, to insurance claims, to patient data—numerous streams of data enter the business at any given time. As a benefits organization increases its number of insured members, it becomes paramount that it leverages the constant influx of data to achieve operational efficiency.
eviCore Healthcare, a leader in medical benefits management, was looking for a way to leverage its data to achieve more efficient authorization processes with a lean team and minimal IT involvement. The previous approach involved multi-month cycles with IT normalizing the data, and inconsistent ways of implementing models into production. To scale its data efforts and achieve a more streamlined process, eviCore needed an end-to-end advanced analytics solution, from data blending to modeling.
The company chose TIBCO Spotfire® Data Science.
Dramatic Process Improvements
eviCore Healthcare is now able to deploy advanced analytics solutions across business units easily and efficiently. The process of preparing and modeling data for a particular unit is centralized within the Spotfire® Data Science platform, and allows business users to maintain governance over the entire process without putting stress on their data science team.
Business analysts at eviCore are able to access the power of predictive analytics through the Spotfire Data Science platform, and can make determinations for authorizing medical procedures based on new data. For the first time, eviCore analysts can receive the input and approvals of various stakeholders in the analytics process from one platform, allowing them to deploy predictive models into production without wasted cycles.
"We were able to achieve 500% process improvement with the Spotfire Data Science Platform," says Matt Cunningham, EVP, M&A, Integration & Value Improvement Projects.
Easier, Faster Analytical Model Development and Deployment
The Spotfire Data Science solution helped eviCore close the gap between model development and operationalization. The company is now able to export the models developed in the Spotfire platform into a form that its IT infrastructure can consume and feed into a real-time scoring engine. Analyst teams can easily understand a business unit's problem, process their data, construct a model, and deploy that model into production in a matter of weeks, without hiring people with specialized PhDs. Previously, the data processing step alone would take several months, and required both data science and IT resources to complete.
Useful, Operational, and Actionable Data Science
The Spotfire Data Science system allowed eviCore's data science and analyst teams to tackle data problems in partnership with the business. Business domain experts can now harness the power of predictive analytics without being data science experts. The Spotfire platform allows users to access, explore, and analyze data from disparate sources quickly, without needing to involve IT, generally a significantly lengthy lifecycle. Most importantly, the Spotfire Data Science system makes the output of advanced analytics useful, operational, and actionable. Analysts can quickly ascertain the value of their models and export them for use without needing to write complex code.
"We've gone from a reporting organization to an insights-oriented organization," says Mr. Cunningham.
eviCore's success with operational efficiency has inspired their teams to extend data science use cases across business units. The integrated approach to discovery, model development, and model deployment within the Spotfire Data Science platform has opened the analytics lifecycle to multiple stakeholders. "Having the modelers integrate with both the IT users and the business users is key to the efficiency process for us," said Cunningham. "Further, working on deploying these concepts in different business unit teams will give us scale on the models themselves, with future growth."