Leading HealthTech Provider Relies on Sigma to Optimize Claim Acceptance
Company Size
1,000+
Region
- America
Country
- United States
Product
- Sigma
- Snowflake
Tech Stack
- Cloud Data Warehouses
- Spreadsheet Interface
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Healthcare & Hospitals
Applicable Functions
- Business Operation
Use Cases
- Predictive Quality Analytics
- Process Control & Optimization
- Regulatory Compliance Monitoring
Services
- Data Science Services
- System Integration
About The Customer
The customer is a top 10 healthcare technology company in the United States, specializing in Electronic Health Records (EHR) solutions. The company partners with medical organizations to drive clinical and financial results. With a vast amount of data, including 100 million rows of claims data, the company’s Rules team is responsible for implementing rules that reduce denials based on payer processing requirements. The company aims to optimize its claim acceptance rate and deliver a higher level of service to its clients.
The Challenge
The healthcare technology company faced significant challenges in optimizing its claim acceptance rate due to scale limitations and an inability to anticipate changing data needs. The Rules team struggled to identify which rules caused billing errors and resolve claims on the first pass. Obtaining data extracts for analysis in Excel involved a lot of back and forth with the data team, taking up to 30 days to see if new rules improved or negatively impacted the claim acceptance rate. This lack of timely access to data hindered the Rules team’s effectiveness, prevented the company from expanding its scope of work for clients, and impeded their ability to deliver a higher level of service.
The Solution
The company adopted Sigma, a cloud-native solution purpose-built for Snowflake and cloud data warehouses. This provided the Rules team with direct access to live, governed data in Snowflake, ensuring everyone works with the same current data. Sigma’s unlimited scale and speed allowed the team to analyze billions of rows of claims data quickly, identifying the cause of denials and trends or patterns. Sigma’s spreadsheet interface enabled self-service data exploration, allowing the Rules team to model the impact of new rules before implementation, ensuring they positively impact claims acceptance.
Operational Impact
Quantitative Benefit
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