Three Ways Artificial Machine Learning Will Impact Medical Coding

Humans are a critical part of the coding process, especially as we build AI systems. Autonomous coding without having learned from human providers and coders during the augmentation phase will lack the efficacy we need from the technology. Over the next few years, as we learn from those closest to these systems, we will begin to see tools that codify charts without any user intervention or user input.

The ability, and technology, to augment the coding process is available – and starting to be implemented. These tools give clinical and billing teams “super powers” by providing code suggestions based on notes they have entered into the EHR, improving the accuracy of the process at the frontlines.

As we improve existing tools, we will begin to see the ROI and cost/benefit tip toward widespread accessibility across both provider and payor organizations.