Most patient services technology stacks weren’t intentionally designed. They evolved over time, shaped by different program needs, timelines, and operational pressures. But as hub models become more dependent on automation, interoperability, and AI, those architectural decisions are starting to create operational and scalability challenges.
In a recent guest post on Drug Channels, CareMetx Chief Product and Technology Officer George Moore explores how excessive customization can make hub environments harder to maintain, slower to evolve, and more difficult to modernize over time. He examines the operational impact of skipped platform upgrades, integration complexity, and growing maintenance burdens, particularly as organizations work to introduce more advanced AI capabilities into patient services workflows.
The piece also explores what AI readiness actually requires at the architectural level. Clean data structures, managed integrations, and clear separation between CRM, operational, and integration layers all play a critical role in whether new capabilities can be deployed efficiently or require significant rework behind the scenes.
Read the full article on Drug Channels.
For teams actively evaluating the future of their hub infrastructure, download Built to Scale: A Hub Technology Architecture Guide for Patient Services Leaders. It provides a practical way to assess whether current systems are enabling growth or quietly creating long-term operational friction. The guide includes diagnostic questions, architectural frameworks, and vendor evaluation considerations designed to help leaders make more informed technology decisions.