How AI Closes Gaps in Healthcare Before It's Too Late | Clinical Decision Support with MongoDB Atlas
🔗 Explore the architecture and technical details - https://mdb.link/WK7E0Dc52Aw-healthcare Subscribe to the MongoDB for Developers YouTube Channel: https://www.youtube.com/@MongoDBDevelopers?sub_confirmation=1 Sign-up for a free cluster → https://www.mongodb.com/cloud/atlas/register Every day, patients miss critical evaluations — not because their doctors don't care, but because the data arrives too slowly for anyone to act on it in time. In this video, we walk through a Clinical Decision Support platform that detects HEDIS care gaps automatically, monitors patient vitals in real time, and gives care coordinators the clarity they need to intervene before it's too late. We break down why FHIR data stores hit their limits under live clinical workloads, and how MongoDB Atlas serves as the operational layer that makes real-time decisioning possible — without replacing existing infrastructure. Whether you're in healthcare IT, clinical operations, or building data infrastructure for value-based care, this is what it looks like when existing data finally does its job. #MongoDB #HealthcareAI #ClinicalDecisionSupport #FHIR #HealthTech #CareGaps #HEDIS #MongoDBAtlas #DigitalHealth 00:00 - Introduction: What are Care Gaps? 00:45 - Measuring Quality Care with HEDIS 01:40 - The FHIR Interoperability & Query Bottleneck 02:20 - Extending FHIR with MongoDB Atlas 03:20 - Generating the Patient 360 View 03:52 - Streaming Wearable Vitals & Real-Time Alerts 04:28 - Inside the Alert and Quality Engines 05:51 - Demo: Care Coordinator Dashboard Walkthrough 07:41 - Technical Insights & System Architecture Visit Mongodb.com → https://mdb.link/MongoDB Read the MongoDB Blog → https://mdb.link/Blog Read the Developer Blog → https://mdb.link/developerblog MongoDB for Developers YouTube Channel → https://www.youtube.com/@MongoDBDevelopers