Leading Medical Group Case Study

Key Metrics

The deployment of analytics pods enabled this organization to increase their speed to insight significantly, allowing them to make data-driven decisions and improve patient outcomes.

Background:

A leading medical group in the United States struggled to integrate data from multiple sources in a timely manner and produce the insights needed to optimize their business and revenue. They did not have the right number of experts across data engineers, analysts, and reporting specialists to complete required analyses.

Solution:

Radiant Healthcare deployed a team of experts to create analytics pods. These pods were responsible for extracting, processing, and analyzing data from various sources.

Radiant’s data engineers built pipelines to extract data from a variety of sources, including electronic health records (EHRs) and claims databases into semantic engines and PowerBI/Tableau. They also developed algorithms to process the data quickly and accurately, which allowed them to generate insights in near real-time.

Outcomes:

The deployment of analytics pods enabled this organization to increase their speed to insight significantly, allowing them to make data-driven decisions and improve patient outcomes. Clearly defined semantic layers permitted modular reuse of data components so that analytics are more composable.

In addition, deploying analytics pods allowed the team to reduce labor costs and improve scalability. By automating data processing and analysis, they were able to reduce the time and resources required to generate insights by 50%.