Having worked in the healthcare industry for over 30 years, I’ve witnessed many significant advances in technology, and while many have instantly been well received, the mention of any type of coding automation often strikes fear into the hearts of many medical coders.  

 

There are many myths surrounding the use of AI in medical coding, but perhaps one that causes the most anxiety is the belief the adoption of AI in medical coding will lead to massive layoffs of medical coders. This myth is rooted in the assumption that AI systems will fully automate the coding process, eliminating the need for human coders. Let’s delve into why this fear is more fiction than fact, and explore the actual impact of AI on the medical coding profession.

 

Staffing Challenges

Twenty years ago, medical coders were fearful computer assisted coding (CAC) applications would replace them, reducing the number of medical coding jobs, but in fact the opposite occurred. The demand for medical coders has only grown in subsequent years, and currently there is a reported 30% shortage of medical coding professionals the healthcare industry.  Additionally, nearly 25% of medical coders in hospital settings currently pose a significant retirement risk.

 

FACT: Many organizations are dealing with staffing challenges ranging from keeping up with increases in volume, employees unexpectedly on extended medical leave creating backlogs resulting in need for outsourcing, as well as seeking solutions to handle attrition (retirement,  resignation or death) given the difficulty in recruiting and retaining qualified staff. 

 

Offshoring & Cost Savings

The most substantial negative impact to medical coding jobs in the US over the past two decades was not due to the introduction of CAC technology, but rather overseas outsourcing which still occurs on a regular basis. Too often, on LinkedIn I see a post from one of my thousands of connections sharing they were just given notice their position was eliminated due to offshoring. Unfortunately overseas outsourcing has become a necessity as the cost of delivering healthcare continues to rise while reimbursements have remained stagnant or in some cases have even declined. Offshoring is one of the easiest ways to reduce administrative costs.  

 

FACT: Due to the cost savings realized through the many benefits of an autonomous medical coding solution the implementation of autonomous medical coding has the potential to significantly reduce offshoring and even eliminate it altogether for some organizations, keeping more medical coding jobs in the US. 

 

The Perfect Duo: Humans & Machines

Autonomous coding solutions shouldn’t be viewed as a threat to medical coders, but rather viewed as the next generation of coding tools in a coder’s toolbox. The use of AI can boost coder productivity by significantly reducing the number of repetitive coding tasks and it can also boost accuracy by alerting the coder to potential issues that may otherwise go undetected. AI can supplement a coder’s expertise assisting them in making more informed and accurate coding decisions.  Additionally, while many AI solutions demonstrate excellent accuracy rates for coding that is redundant with little variation, it can be challenged with coding more complex cases that require a degree of human reasoning and intuition which is an integral part of medical coding. 

 

FACT: Realizing the maximum benefit from autonomous medical coding can only be achieved through a collaborative synergy by combining the efficiency of technology with the irreplaceable human touch.  

 

Elevated Professional Status

While the role of medical coders will evolve over the next several years, it will certainly not be diminished. While traditional job roles are being reinvented, new job roles are also being created. 

 

As autonomous coding technology gains more widespread adoption, a typical production coder can expect to transition into the role of an auditor, validating the output of an autonomous coding platform.  Additionally, coders may be re-deployed to assist with other tasks or promoted to other revenue cycle roles including revenue integrity analyst or clinical documentation improvement specialists, where coding knowledge is invaluable.    

 

Furthermore, companies who have developed autonomous medical coding platforms are currently seeking coding professionals with subject matter expertise to assist in product development and coding quality validation. Human subject matter expertise is vital to machine learning ensuring the coding model is initially trained correctly and properly maintained with coding updates. 

 

FACT: The medical coding field stands poised to gain heightened professional recognition amid this transition. The critical role of human oversight in maintaining quality assurance highlights the pivotal position of medical coders as guardians of medical coding integrity. Medical coders have the opportunity to enhance their professional status by taking on more complex and advisory responsibilities. 

 

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Preparation Meets Opportunity

For medical coders, the path forward involves embracing change through continuous learning and skill set expansion as well as exploring non-traditional roles that benefit from coding knowledge and expertise, as well as managerial and executive roles.  

 

Most importantly, medical coders should develop a career map outlining goals and the steps needed to achieve them, helping to navigate different stages in their career. While there are many aspects that should be considered when developing a career map, two of the most important are a skill gap analysis and a professional development plan.  A skill gap analysis involves comparing your current skills with the skills required for the roles you aim to achieve in the future. Identifying gaps will then help you assemble a professional development plan outlining the steps you need to take to develop the necessary skills and qualifications to meet your career goals. These steps may include formal education, online courses, workshops, conferences, on-the-job training, networking, or mentorship opportunities. 

 

FACT: For now, the immediate landscape for medical coders will remain relatively unchanged as AI technology is still evolving and has not yet been widely implemented and the shift to automation will occur gradually over time. In the healthcare industry, the adoption of new technology tends to be slow, often due to competing priorities and budgetary constraints. Additionally, while larger providers are typically the most likely to implement new technologies, mid-size and smaller providers tend to lag behind.

 

In the short term, medical coders should learn all they can about artificial intelligence – how it all works and how AI will impact the healthcare industry.  Additionally, medical coders may want to consider learning more complex specialties and earning additional specialty certifications to boost their resume.

 

Learn more about Maverick’s Autonomous Medical Coding platform.