The future of coding is AI-driven
In today’s complex healthcare environment, the accuracy of clinical documentation is more than a compliance requirement — it is a strategic imperative. Accurate and complete member health profiles are the foundation for effective risk adjustment and member care, and precise health profiles begin with reliable coding. Traditionally, chart coding for risk adjustment has been a complicated and labor-intensive process, with relevant health data residing in medical charts rather than claims. But the burdensome process of coding is changing, with new coding strategies driven by artificial intelligence (AI) and overseen by human coding experts.
The key to this new approach to coding is to embed AI throughout the process to automate and augment the coding workflow, thereby enabling coders to focus their attention on the clinical elements that require human judgment. AI analyzes both claims and chart data, guiding coders to the most relevant content and orchestrating the workflow for maximum efficiency.
Not only does AI drive a more efficient coding process, but it also improves coding quality. Where traditional coding is subject to the expertise of each individual, AI operates as a unified system, continually learning and developing common patterns. This centralized intelligence promotes consistent outcomes and limits variations from person-to-person interpretation. This combination of AI and human expertise delivers both efficiency and accuracy for smarter and more impactful risk adjustment coding.