Build and manage predictive clinical models for integration into Epic

About the Customer:

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Healthcare Provider ($5B+ market cap)

Consistently ranked under top 15 providers in the US

In North America with over 45 hospitals and >2+ million patients

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What is their starting point / ecosystem / tech stack ?

• Azure
• Epic
• Interface Engine
• Python
• R

Predera Benefit

• One stop platform for building, deploying and managing AI models
• Continuous Improvement based on feedback from data scientists, experts and clinical staff
• Business stakeholders can overwrite the output from AI models even in production environment using a sophisticated rule engine

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Evaluation

• Easy to install and setup
• Business stakeholders can teach AI for Fraud Engines in 8 hours
• Able to migrate all existing ML models and rules in less than a week
• Integrated with data stores on AWS/ GCP - no extra support needed from IT/ data teams
• Didn’t need to re-write workflow integration as it directly integrates with Slack and Hipchat for feedback from Customer support
• Dedicated expert level support for onboarding

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Business Impact

• Business stakeholder -> fraud analysts -> customer support representatives  loop was tightened, reducing the feedback time by  80%
• Saved 280 hours of stakeholder productivity per year
• Reduced time to resolution of Fraud by 75% from ~20 mins to ~5 mins
• Handle more fraud queues and volume with less people

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ROI

“We would need two full-time data scientists with knowledge of marketing and acquisition campaigns for 6 months just to build out our Fraud Engine capability let alone the rest of monitoring and continuous automatic improvement provided by Predera. We could spend $300,000 to do that, or just buy Predera and have a mature Fraud and AI / ROI management platform today”