Artificial Intelligence (AI) and Medical Coding Part 1 – Will AI Replace Medical Coders?

The introduction of artificial intelligence (AI) technology into daily work routines is quickly becoming commonplace. Health information is no exception, with several forms of autonomous coding systems already in development or available for implementation. Other AI and machine learning tools are also being created to enhance the industry. With technological advances on the horizon, it is natural for medical coders to wonder if artificial intelligence will eliminate or reduce the need for their specialized skills.

A widely used and commonly accepted form of generative artificial intelligence used to answer questions is ChatGPT. To get insight into the estimated impact of AI on the need for medical coders, ChatGPT was interrogated to see what it had to say when asked whether artificial intelligence will replace the need for medical coders. The response generated by ChatGPT is revealing and reassuring.

ChatGPT

Question
Will the introduction of autonomous coding systems or other artificial intelligence or machine learning tools eliminate the need for human medical coders?

Response
The introduction of autonomous coding systems and other artificial intelligence (AI) or machine learning (ML) technologies is transforming the field of medical coding, but it is unlikely to completely eliminate the need for human medical coders in the foreseeable future. Instead, AI and ML are expected to augment and assist human coders in their work, leading to increased efficiency, reduced errors, and better productivity.

Here are several key reasons why human medical coders will still be needed:

1. Complexity of Medical Data

Medical coding is a nuanced task that involves interpreting a wide range of medical records, procedures, diagnoses, and billing information. While AI can handle routine tasks and some straightforward coding assignments, it still struggles with more complex cases that require human judgment, expertise, and contextual understanding. For example, medical coders often need to review intricate patient histories, collaborate with clinicians for clarification, and understand the subtleties of a patient’s condition, which can be challenging for AI to interpret accurately.

2. Regulatory Compliance and Billing Nuances

The healthcare industry is subject to strict regulations and standards, including those related to insurance billing, compliance with ICD-10, CPT, and HCPCS codes, as well as payer-specific rules. Human coders possess the expertise to navigate these regulations and adapt to changes, ensuring compliance with local, national, and payer-specific requirements. AI tools can assist with this, but human oversight remains essential to ensure that coding aligns with the latest regulatory standards.

3. Ethical and Legal Responsibility

Medical coding has significant ethical and legal implications, particularly when it comes to billing and reimbursement. Incorrect coding can lead to audits, denials of claims, or even legal consequences for healthcare providers. Human coders are trained to avoid such pitfalls, take responsibility for their work, and make judgments when faced with unclear or ambiguous coding situations. AI systems, while powerful, can still make mistakes or misinterpret complex cases, requiring human intervention.

4. Training and Adaptation to New Scenarios

While AI models can be trained on large datasets, they may still struggle with novel situations, particularly if they haven't been exposed to specific cases during training. Human coders can adapt to new and evolving medical practices, emerging technologies, and rare medical conditions, something that AI might not be able to handle as well without retraining on new data. Human expertise is also needed to update and refine coding practices as medical practices and terminologies evolve.

5. Quality Control and Human Oversight

While AI can perform many tasks faster than humans, there is still a critical need for quality control. Human coders can review AI-generated codes to ensure accuracy, identify any potential errors or inconsistencies, and intervene when the AI makes mistakes. This is particularly important in complex cases or when AI systems have not been thoroughly trained on a specific medical issue.

6. Evolving Role of Medical Coders

As AI takes over some routine aspects of coding, the role of human coders may shift towards more strategic and supervisory functions. Coders may spend less time on manual coding and more time on analyzing coding trends, improving data accuracy, assisting with coding audits, and working closely with healthcare providers and AI systems to ensure the highest quality of documentation and billing.

Conclusion:

In summary, while AI and machine learning technologies can significantly enhance the efficiency and accuracy of medical coding, they are unlikely to fully replace human coders. Rather, they will help coders focus on more complex, nuanced tasks while improving overall productivity. Human medical coders will continue to play a vital role in ensuring the accuracy, compliance, and ethical standards of healthcare billing and coding.

Real World Employment Outlook

The Bureau of Labor Statistics’ estimate for growth in the field of Medical Records Specialists is 9% or 16,700 jobs between 2023-2033. This is more than double the 4% estimated rate of growth for most occupations. Medical Records Specialists : Occupational Outlook Handbook: : U.S. Bureau of Labor Statistics

Take Aways

Although artificial intelligence and machine learning tools are likely to be implemented in the field of health information over the next decade, they’re main purpose, when it comes to coding, according to ChatGPT, will be to assist and augment coders in the work they do, rather than replacing them. Given this perception, in combination with the data from the Bureau of Labor Statistics it seems the employment outlook for coders will continue to be strong over the next decade.

Do you want to learn more about how AI will impact the world of medical coding? Then stay tuned for the next installment of this blog, Artificial Intelligence and Medical Coding Part 2 - How Using AI Will Affect the Work of Coders; to find out how the kind of work coders do is likely to shift with the implementation of artificial intelligence tools.

References

https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm

Since 1992, HIA has been the leading provider of compliance audits, coding support services and clinical documentation audit services for hospitals, ambulatory surgery centers, physician groups and other healthcare entities. HIA offers PRN support as well as total outsource support.

The information contained in this coding advice is valid at the time of posting. Viewers are encouraged to research subsequent official guidance in the areas associated with the topic as they can change rapidly.