Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Google Cloud
- Document AI
- Assured Workloads
Tech Stack
- Machine Learning
- Cloud Computing
Implementation Scale
- Pilot projects
Impact Metrics
- Productivity Improvements
- Cost Savings
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Machine Learning
- Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
- Healthcare & Hospitals
- Software
Applicable Functions
- Business Operation
Services
- Cloud Planning, Design & Implementation Services
- System Integration
About The Customer
Covered California is a state service dedicated to increasing the number of insured Californians, improving healthcare quality, lowering costs, and reducing health disparities. It offers a competitive marketplace where residents can choose high-value health plans and providers, with options for affordable healthcare based on income. The organization plays a crucial role in connecting Californians to quality, affordable health insurance, significantly reducing the number of uninsured residents in the state. Covered California is committed to innovation and improving the healthcare experience for both residents and employees.
The Challenge
In 2014, nearly 20% of California's 39 million residents lacked access to basic health insurance. By 2024, this number had decreased to just under 8%, largely due to Covered California, a state service bridging the gap between uninsured residents and affordable health insurance. The challenge was the time-consuming and manual process of verifying eligibility documents, which required residents to submit identity and income documents. Covered California staff processed most documents by hand, leading to delays and additional work when incorrect forms were submitted. This manual process was inefficient and created extra work for both staff and consumers.
The Solution
Covered California partnered with Deloitte and Google Cloud to automate the document verification process using Document AI. This AI-powered solution uses machine learning to automate the repetitive task of verifying resident information, improving the speed and accuracy of data extraction. The solution was tested in a pilot program, achieving a document verification rate of 80-96% depending on document type, with an average of 84%. This was a significant improvement over the legacy system's 28-30% automated verification rate. The new system also simplifies security and compliance with Assured Workloads, supporting FedRAMP compliance and ensuring all network traffic is private and encrypted.
Operational Impact
Quantitative Benefit
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