Paula Akialis, MBA, RHIA, CCS, CPC, CPC-I

For years, health information professionals have heard careers described as either traditional or nontraditional. But does that distinction still make sense?

In today’s revenue cycle, coding accuracy alone no longer guarantees payment. And Sepsis is the primary battleground.

ICD-11 introduces a fundamentally different model but ICD-11 won’t automatically improve data quality. If we don’t change how coding happens, we’ll simply have more codes—and the same specificity problem.

You cannot look far without seeing that healthcare is a changing industry with new challenges seeming to arise daily. What if you could improve your skills to address just one thing, one challenge you are facing?

With AI handling much of the coding, organizations face a new challenge: ensuring the accuracy and compliance of codes generated by systems that often operate as ‘black boxes.’ The question then becomes: Whom would you rather entrust with the challenge of ensuring your organization’s coding meets your standards?

Artificial intelligence (AI) is rapidly becoming part of the medical coding workflow. When organizations ask, “How long does it take to transform a coder into an AI-analyst?” the most honest answer may be: How much time do you have?

The New Coder Problem is not about intelligence, motivation, or credentials. It’s about readiness—and the disconnect between education, employer expectations, and today’s coding environment.