By Sharon Easterling, MHA, RHIA, CCS, CDIP, CRC, FAHIMA

Flash Points

  • From labeling data to validating algorithms, a coder’s precision and insight ensure AI systems in healthcare learn accurately and perform reliably.

  • Coding professionals safeguard patient privacy and guide the responsible use of AI. Ethics and compliance create trust while advancing innovation.

  • As AI documentation analysts and clinical AI trainers, coders are leading the integration of intelligent tools into everyday healthcare workflows.

Coding professionals are already actively contributing to AI projects in healthcare, often without needing to become data scientists or programmers. Their domain expertise makes them indispensable in roles that bridge the gap between clinical data and artificial intelligence. These professionals are not just users of AI; they are architects of its intelligence, ensuring it functions effectively, ethically, and in alignment with real-world healthcare needs.

Let’s explore the key steps in AI implementation and the roles coders and other Health Information professionals will take to ensure a smooth transition. 

Early AI Integration:  Data Annotator

Coders are among the first to label medical images and text with precise codes, creating the foundational datasets for AI training. Their accuracy is paramount for AI’s initial learning phase.

AI Development and Testing: AI Model Validator/Auditor

Coding professionals review AI-generated diagnostic suggestions or procedure codes, identifying discrepancies and providing critical feedback to refine algorithms and reduce errors.

Ethical AI and Compliance: AI Ethics and Compliance Specialist

Leveraging their deep understanding of healthcare regulations, coders help develop ethical guidelines for AI use, ensuring patient privacy and data security are maintained.

Clinical Decision Support: Clinical AI Trainer

Coders work alongside clinicians to train AI systems on nuanced clinical scenarios, helping the AI understand complex patient presentations and improve its diagnostic or treatment recommendations.

Future Roles: AI Documentation Analyst

Specializing in optimizing AI-assisted clinical documentation, ensuring that AI tools enhance, rather than complicate, the process of capturing accurate patient information.

My word of advice:  Embrace AI as the opportunity it is.  Your energy and skills are needed as workflows and processes change.  Your organization is counting on you to be there for the evolving challenges faced.

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Written by Sharon Easterling, MHA, RHIA, CCS, CDIP, CRC, FAHIMA, a nationally recognized leader in HIM, CDI, revenue cycle, and applied AI in healthcare.
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About the Author:
Sharon Easterling, MHA, RHIA, CCS, CDIP, CRC, FAHIMA
Sharon Easterling is a nationally recognized leader in health information, revenue cycle, and AI-driven workforce transformation. With over 20 years of executive experience, she specializes in clinical documentation integrity, coding, compliance, and operational strategy.