Make sense of the workflow. Then automate it.

When payer-specific behavior spreads throughout an automation, every new customer can create another variation to maintain. Requirements are also easy to misunderstand when engineers and healthcare stakeholders use different language for the same workflow.

I separated data extraction and validation from browser automation. The pipeline prepares normalized, validated data first; thin payer adapters then handle portal-specific interactions. This allowed the core prior-authorization logic to stay shared.

An eligibility pipeline was waiting on data fetched sequentially at different points. I traced those dependencies and consolidated independent requests into one parallel boundary. The improvement came from understanding the flow of work before changing the implementation.

I used Domain-Driven Design and shared terminology to connect customer requirements, implementation, and user acceptance testing. I also introduced a centralized environment policy and logging boundaries that excluded patient data.