Leading Healthcare Software Solutions Provider Selects QAT Global for Financial System Re-Write

Distributed Development With an Experienced Team of Resources from the US, Brazil, and Costa Rica

Customer Snapshot

  • Healthcare – Home Health/Hospice Provider
  • Multiple US and International Locations

Key Differentiators

  • Mixed teams across the US, Brazil, and Costa Rica
  • Offshore development without access to PHI
  • Scrum Methodology and Project Management

Solution Snapshot

  • Three development teams of three developers and two automation engineers each
  • Project quality ensured by two delivery managers and an architect.

Skills Needed:

  • .NET Core
  • Angular7
  • AWS
  • AWS Aurora DB
  • Azure SQL
  • CircleCi
  • Jenkins
  • Kafka
  • New Relic
  • Postgres
  • SQLServer
  • Sumo Logic

The Challenge

The client wanted to re-write their Financials on a new platform in support of the Patient-Driven Groupings Model (PDGM), a part of the CMS 2019 Home Health Final Rule.

The project needed to be completed in a short timeline. This involved gathering requirements just in time, which made designing for the final outcome particularly challenging as new requirements would continually impact the original solution, and as a result, constant adjustments had to be made

Healthcare Software Solutions Provider Case Study

QAT Global’s Solution

QAT Global delivered a quality-driven solution that was written in .NET and Angular and deployed to AWS. The solution was developed in fast-paced sprints using agile and scrum methodologies with minimal bugs and regressions.

The QAT Global teams architected, designed, and developed an Event-driven solution to capture financial events sent from their legacy system over Kafka and consume them into a journal. Reporting, Hard Close, and General Ledger services were then developed, including a new UI, to pull the event information for use in the client’s financials.

QAT Global leveraged enterprise patterns and practices in order to implement multiple microservices that ran under AWS leveraging Kubernetes container management. The solution allowed our customers to scale both vertically and horizontally based on message volumes and user-load.