Top 3 Predictive Analytics Opportunities for Healthcare

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Speaker: 
Sriram Parthasarathy
Chief Product Owner
Logi Analytics

Sriram Parthasarathy is Chief Product Owner of the Predictive Analytics platform at Logi Analytics. He works with customers to embed Predictive Insights directly in to the applications business users use on a daily basis. Sriram has over 20 years of experience in designing enterprise and OEM Analytical products. Prior to Logi Analytics, Sriram was with MicroStrategy for 15 years, where, as an early employee, he was integral to building & launching several product / modules. As a practicing Data Scientist, Sriram is passionate about making it easy for business users to predict what is going to happen and take preventive actions. In his free time, Sriram coaches kids for competitive Math and Science competitions.




 
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Sponsored by: Logi Analytics
Delivering compelling applications with analytics at their core has never been more crucial—or more complex.  For over 17 years, Logi has helped companies embed sophisticated dashboards and reports in their applications. Logi is the only developer grade analytics platform on the market, and is rated the #1 embedded analytics platform by Dresner Advisory Services.



February 21st, 2019 1:00PM ET

Healthcare applications tap into vast amounts of data, from health records and clinical trials to billings and claims. Endless data means  endless opportunities to improve patient outcomes, increase regulatory compliance, and protect against fraud—especially with the power of predictive analytics.

Predictive analytics uses historical data and machine learning to answer the question: “What is most likely to happen based on my current data, and how can I change that outcome?” New predictive analytics tools are easy to use, even without expertise in R, Python, or statistical modeling. Application teams are able to predict future trends and improve outcomes across the board. 

Join the webinar to see:
  • Practical strategies for finding and defining predictive problems
  • Examples of how predictive analytics solves common challenges in clinical workflows, invoicing and claims, and hospital utilization
  • A live demo of how any application team can assemble data, build a predictive model, distribute insights, and empower their users to take action