Data Science Drives Better Healthcare Pricing

A healthcare organization focused on creating provider solutions was looking for ways to help patients find the most cost effective healthcare services in their area. The challenge they faced was that they had large amounts of data that they needed to leverage in order to provide recommendations to their customers. They did not have an easy way to access the different data sources and data formats. The data scientists were also spending too much time getting the data prepped for analysis versus actually doing the analysis.

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We worked with this company’s development and data teams to create an Azure solution that provides a single point of consolidated data access for the data scientists. This solution leveraged Azure Data Factory to create the scheduled jobs to pull data from an Azure SQL database, Cosmos Document database, and file drops and push to SFTP locations. We also leveraged Azure Data Lake Analytics with USQL to perform data consolidation and transformation.  This transformed data was then pulled into an Azure SQL Data Warehouse to provide the data scientists the ability to discover and analyze information using tools like Power BI.

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This solution enabled the data scientists to spend most of their time identifying and making the best recommendations on customer prices based upon historical data and national trends. This brought down the costs for each customer as they were looking for healthcare service in their area.

Their Azure Data Platform solution was hosted entirely in the cloud which minimized the initial investment needed to get the solution up and running and made ongoing support much simpler for the team.

The Azure Data Warehouse also allowed the company to only pay for what they used and shut down the Data Warehouse when it was not in use to reduce costs.

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