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The Inevitable Integration of AI into Medical Coding

Innovation leaders at Signature Performance have kept a close eye on AI integration trends in the healthcare industry. AI is a cutting edge tool that has the distinctive ability to significantly lower costs and administrative burdens. One area that has been stirring both excitement and uncertainty is its applications in the realm of medical coding.


Since its inception, coding has long been a crucial element in the healthcare revenue cycle process. It has typically required a trained medical coder to review medical records and essentially serve as translators between the documentation of health services provided and the universal coding systems that payers rely on to determine billing. As the healthcare industry continues to evolve with new best practices and procedures, so must the medical coding systems used to classify them for payment.


Medical coders utilize standardized systems such as the International Classification of Diseases (ICD), the Current Procedural Terminology (CPT) and Healthcare Common Procedure Coding (HCPCS). These coding systems are all updated annually to account for changes in best practices and service innovation. To maintain accuracy, medical coders must keep up to date with these changes or risk inaccurate billing; if this occurs, this increases administrative burden by negatively affecting provider reimbursement, increasing the incidence of denied claims, and ultimately jeopardizing the safety and continuity of care for patients.


As more business sectors venture towards the adoption of artificial intelligence, what are the implications in the world of medical coding and what does this mean for the future of medical coders?


What is Possible?


AI can be trained to read through electronic medical documentation and identify specific diagnoses, treatments, and procedures. From here, an appropriate preliminary code can be suggested, which is then reviewed by an experienced medical coder. As previously mentioned, the annual updates to standardized coding systems can cause delays or errors by coders due to natural human learning curves. AI systems are quick to learn and adopt these updates; they can be helpful in auditing medical records to locate coding errors, document discrepancies, and flag these for human review. This can help organizations better utilize the full scope of their talent and save the more complex encounters to be coded by the workforce.


AI Systems Learning Process

Designed to Supplement and Empower Humans, Not Replace Them


There is some concern in the medical coding community that new AI technologies will completely replace their positions. Some who are considering coding as their next career move are understandably uncertain about whether to make the time and educational investment of getting certified when the position may become obsolete in the near future.


However, some experts in the healthcare informatics community have expressed a different take on AI integration. Contempo Coding medical coding auditor and public speaker Victoria Moll recently held a webinar where she shares a great analogy about AI integrations, relating it to filing taxes:

  • If your tax filing is fairly simple (single income, no additional assets) you may feel comfortable doing your own taxes or using a simplified third-party tax software that uses AI functionalities to walk you through the process.

  • For those with more complex tax situations (business owners, multiple incomes, etc.), you may feel more inclined to have a tax professional manage your filing for you. Many tax professionals may still use a third-party AI software to help keep the filing organized and auto-fill paperwork, but their subject-matter expertise and personal knowledge of each taxpayer’s unique circumstances is still crucial to ensure an accurate filing.

This same principle applies to medical coding: incorporating AI for automatic code selection can help optimize efficiency by reducing some of the administrative burden involved in basic medical coding. The time coders historically spent looking up codes can now be spent on more complex tasks that require human clinical judgment and expertise. These activities include reviewing the AI-generated automatic coding for errors, coding more intricate encounters, and performing quality assurance functions.


Simply put, it is not a matter of the occupation going away, but rather a possible shift in the type of work medical coders perform.


Learn More


Signature Performance is constantly exploring new ways in which our clients can leverage innovative technology to help lower their administrative costs and improve the health of their business. If you are ready to discover more ways to reduce your organization’s administrative burden, visit our website today for more information.

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