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Home Case Studies Healthcare Software Solutions Provider Teams up with Pylogix for Distributed Development
Healthcare Software Solutions Provider Teams up with Pylogix for Distributed Development

Customer Profile: Home Health/Hospice Provider with Multiple Locations

  • Industry: Healthcare
  • Geographic Presence: United States and International

Key Differentiators:

  • Mixed teams located in the USA
  • Offshore development without access to PHI
  • Scrum methodology and project management

Solution Overview:

  • Three development teams, each consisting of three developers and two automation engineers
  • Quality assurance provided by two delivery managers and an architect.

Required Skills:

  • .NET Core
  • Angular 7
  • AWS (including Aurora DB)
  • Azure SQL
  • CircleCI
  • Jenkins
  • Kafka
  • New Relic
  • Postgres
  • SQL Server
  • Sumo Logic

The Challenge: Re-Writing Financials to Meet CMS Regulations for Home Health

Our client needed to re-write their financial system in order to comply with the Patient-Driven Groupings Model (PDGM), which is part of the CMS 2019 Home Health Final Rule. The project had a tight timeline and required gathering requirements just in time, which made designing for the final outcome particularly challenging. With new requirements continually impacting the original solution, constant adjustments had to be made to ensure the project’s success.

Pylogix’s Solution

Pylogix developed a quality-driven solution using .NET and Angular, which was deployed to AWS. The solution was developed using agile and scrum methodologies, with a focus on minimizing bugs and regressions.

Our teams architected, designed, and developed an event-driven solution to capture financial events from the client’s legacy system over Kafka and consume them into a journal. We also developed reporting, hard close, and general ledger services, including a new UI, to present the event information for use in the client’s financials.

We leveraged enterprise patterns and practices to implement multiple microservices running under AWS, using Kubernetes container management. The solution allowed our customers to scale both vertically and horizontally based on message volumes and user-load.