Machine Learning

We’ve talked a lot about how technology is transforming healthcare. From ambient listening devices to voice-based assistants, we’re seeing a data explosion. This shift (what many call a “data revolution”) is especially visible in the rise of AI scribes: tools that automatically generate clinical notes from doctor-patient conversations.The promise is big: faster diagnoses, more personalized care, and a lighter admin load for clinicians. But there’s a catch: most of this data never gets used.

We discussed how new technology is transforming healthcare: As the volume of electronic data continues to increase, many sectors refer to this phenomenon as a data revolution. And though this revolution promises faster diagnoses and personalized care, it comes with a catch: most of that data is never even used.Welcome to healthcare’s quiet crisis: the abandonment of unstructured data.

The way healthcare organizations collect and use critical data is changing, and changing fast. From smartwatches to AI-powered documentation, new technologies are transforming how patient information flows, creating new opportunities for continuous health monitoring, early intervention, and improved clinical outcomes. But with so many tools entering the space, it can be hard to keep up.

Clinical notes. Imaging reports. Lab results. Transcripts from patient conversations. It’s all full of critical insights, but none of it fits neatly into rows and columns – it’s all unstructured data.