A Health Plan’s Data Modernization Journey With OmniData

Creating a Unified Data Infrastructure to Streamline Regulatory Healthcare Reporting

Faced with fragmented data sources, regulatory reporting challenges, and resource bottlenecks, the health plan sought to create a unified, scalable data infrastructure to streamline their tedious regulatory reporting processes.

However, the bottlenecks, data extract discrepancies, and tedious manual reporting were all surface-level symptoms of a much deeper issue. They lacked a data focus as an organization.

The solution required a multiple-step approach to surface those core issues for the health plan and build the data foundation on which they could establish efficient, repeatable processes.

The health plan needed infrastructure that could handle massive data volumes from various sources and be able to trust the numbers on the reporting side. The client trusted OmniData’s expertise in healthcare to root out these core issues, establish their data focus, and migrate all their source systems from on-Prem to a cloud-based Microsoft Azure data warehouse.

Their challenges were spread across multiple aspects of the business, impacting technology, people and processes.

The OmniData team, under the direction of Jessie Quinn, a Principal Solution Architect with more than 18 years prior experience in the healthcare system, acted as the health plan’s in-house data team.

The team worked closely with the health plan to identify necessary work or source systems, conduct analysis, build backlogs, develop tests, and deploy solutions into production to set them on the right trajectory to become a truly data-driven organization.

Fragmented Data Infrastructure

The first apparent issue was the lack of proper testing or validation processes for their data. Their legacy on-premises data warehouse was fragmented across production, development, and staging environments. Things were happening for production in dev, things happening for production in stage, and mini data warehouses were scattered across the organization.

This fragmented infrastructure meant the health plan’s key department leaders were showing up to internal meetings with different numbers, each person fully convinced their numbers were right.

Instilling Data Confidence & Credibility

We started by mapping their data sources, ingesting their data, reporting on it, and conducting User Acceptance Testing (UAT) with them to build confidence and credibility. During this process, we uncovered many things that weren't reported correctly.

We worked through several domains, starting with membership, then moving on to labs.

Through this process we found a cyclical pattern of data quality control issues, particularly with the lab claims. Many original claims went unbalanced, while some had triplicate entries.

Each month, we'd start with a sprint, breaking it down into planning in the first week. Then we'd move onto development, UAT testing, and finally putting it all into production and demonstrate what was done for the client so they had a complete understanding of the work and its impact.

We worked side-by-side with the health plan and repeated this cycle every month to meticulously unravel the past and build their foundation to become a data-driven organization.

Building Trust Through Transparency

The health plan also needed a consistent framework to implement agile methodologies and best practices for using Microsoft Azure tools effectively for specific tasks.

As the project progressed, we helped the health plan establish new patterns, repeatable processes, and uplevel data discipline across key departments. For example, we provided a trail guide of external training to upskill their employees. We created wikis on everything that we built for them and trained them to become self-sufficient.

By the end, they knew who their point people, SMEs and resources were for each job to carry the work forward.

This level of transparency avoided the “black box solutions” that are so prevalent in the industry. They understood how everything was built and regained confidence in their own data.

Through this project, the health plan established a future proof framework and processes that they now utilize for their other cloud-based projects.