Operationalizing Machine Learning in Regulated Healthcare Systems: A Case Study of Provider Search Engine Deployment

Abstract

Healthcare organizations face unique challenges when putting machine learning into practice. This article walks through the creation of a provider search tool built with AI that helps patients find the right doctors across many healthcare websites. We built it using small, independent services that work together, with special language processing tailored for medical terms. The article covers the important parts: making sure everything follows healthcare laws, keeping patient information safe, rolling out updates without breaking things, and watching the system to catch problems early. By sharing what we learned from building this in the real world, we hope other healthcare groups can follow our example while still meeting strict requirements like HIPAA and HITECH. Our experience shows that well-built AI systems can make finding providers easier while keeping patient data protected, systems running smoothly, and medical information accurate, even in sensitive healthcare settings where mistakes aren't an option.