Case Study

Leading HealthTech Provider Relies on Sigma to Optimize Claim Acceptance

Use Case: Claim Acceptance Rate Optimization

A top 10 healthcare technology company in the U.S. partners with medical organizations to drive clinical and financial results. Like just about every company today, large and small, this Electronic Health Records (EHR) solution provider has a lot of data, including 100 million rows of claims data.

The company’s Rules team is responsible for implementing rules that reduce denials into its proprietary system based on payer processing requirements. Developing these rules requires row-level data so the team can understand which claims were denied and why by diagnosis codes (DX). However, the company’s system had scale limitations, which meant the data had to be aggregated to a single DX code or a subset of claims. This resulted in a continuous back and forth between the Rules and BI teams as they tried to find the right data, making it impossible to effectively analyze the data and optimize the claim acceptance rate. In short:

  • Scale limitations and an inability to anticipate changing data needs prevented the Rules team from identifying which rules caused billing errors and resolving claims on the first pass.
  • Obtaining data extracts for analysis in Excel took a lot of back and forth with the data team as they determined exactly what was needed and it took 30 days to see if new rules improved the claim acceptance rate or negatively impacted it.
  • 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.

With Sigma, the Rules team has improved the first pass resolve rate and expanded its scope of work for clients.

Direct access to Snowflake

Sigma was purpose-built for Snowflake and cloud data warehouses. The Rules team now has direct access to live, governed data in Snowflake, ensuring that everyone is always working with the same current data – no more risky, stale extracts, data sprawl, or conflicting insights – and the data stays safe in Snowflake.

Unlimited scale and speed

Sigma is a cloud-native solution delivering unlimited scale at cloud speed – no summaries or aggregates necessary. The Rules team can now easily analyze billions of rows of claims data, enabling them to quickly identify the cause of denials and trends or patterns, as well as ways to optimize the process and deliver a higher level of service.

Self-service data exploration

Sigma’s spreadsheet interface makes iterative ad hoc analytics available to anyone, especially those that are accustomed to analyzing data in spreadsheets. Today, the Rules team can easily model the impact of new rules before implementation to ensure they work in the way intended and positively impact claims acceptance.

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