Case Studies Leading HealthTech Provider Relies on Sigma to Optimize Claim Acceptance

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	Leading HealthTech Provider Relies on Sigma to Optimize Claim Acceptance

Leading HealthTech Provider Relies on Sigma to Optimize Claim Acceptance

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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.

About 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.

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.

Impact #1	The Rules team now has direct access to live, governed data in Snowflake, eliminating the need for risky, stale extracts and conflicting insights.
Impact #2	Sigma’s unlimited scale and speed allow the team to analyze billions of rows of claims data quickly, identifying the cause of denials and trends or patterns.
Impact #3	The spreadsheet interface of Sigma enables self-service data exploration, allowing the Rules team to model the impact of new rules before implementation.

Impact #1

The Rules team now has direct access to live, governed data in Snowflake, eliminating the need for risky, stale extracts and conflicting insights.

Impact #2

Sigma’s unlimited scale and speed allow the team to analyze billions of rows of claims data quickly, identifying the cause of denials and trends or patterns.

Impact #3

The spreadsheet interface of Sigma enables self-service data exploration, allowing the Rules team to model the impact of new rules before implementation.

Benefit #1	Data extraction time reduced from 30 days to real-time access.
Benefit #2	Ability to analyze billions of rows of claims data without summaries or aggregates.

Benefit #1

Data extraction time reduced from 30 days to real-time access.

Benefit #2

Ability to analyze billions of rows of claims data without summaries or aggregates.

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Overview

Leading HealthTech Provider Relies on Sigma to Optimize Claim Acceptance

Operational Impact

Quantitative Benefit