Many years ago, the company I worked for was an early adopter of Computer Assisted Coding (CAC) technology. At that time the vendor was claiming up to 75% of coded reports could be sent direct-to-bill and for a billing company, that claim was very promising. Unfortunately 3 years after implementation we were still reviewing 100% of the CAC coding output and never sent any claims direct-to-bill because we did not have confidence in the accuracy of the coding engine.
Fast forward two decades later, while there have been many improvements with CAC technology it still has not achieved high direct-to-bill rates once promised. It has limited capabilities using natural language processing (NLP) and relying on rules based coding. From my observations working with many providers across the country, CAC rarely exceeds a 50% direct-to-bill rate and many providers are not even hitting that threshold. Unfortunately, CAC has fallen short on desired outcomes for a large number of providers. Thankfully with the evolution of technology, artificial intelligence now has the ability to deliver better coding outcomes with a solution such as Maverick Medical AI’s autonomous coding solution.
When I initially began working with Maverick, they boasted of an 85% direct-to-bill rate at go-live. The skeptic in me said ‘No way, that threshold just isn’t possible.’ Much to my surprise Maverick has been able to deliver on that claim and I am excited to see how their technology will revolutionize the medical coding industry.
One of the main reasons why Maverick’s autonomous coding solution can deliver better outcomes than CAC is because it is powered by AI deep learning technology, rather than rules based coding. As a human coder interacts with the coding platform and makes coding changes, the platform is learning based on those changes and over the course of time the engine gets better and better at predicting codes. The success of Maverick in achieving an 85% direct-to-bill rate is largely due to applying the deep learning technology to a provider’s historical data.
Switching to a new coding solution may seem overwhelming and time-consuming, but the implementation process with Maverick is simplified. During the implementation phase, large amounts of claims data along with reports are processed and analyzed and then validated for coding accuracy. Maverick’s validation phase ensures that any coding quality issues are identified and corrected prior to go-live, reducing any future risks associated with coding quality. Much of this work is performed by Maverick’s coding experts, keeping the amount of time and resources allocated by clients during the implementation phase to a minimum. Additionally, there is no need to spend countless hours starting from scratch building your coding rules all over again since Maverick’s coding solution learns from your historical coding data.
As evidenced by the frenzy of new AI technology flooding the market, autonomous coding is the future of medical coding and CAC as we know it will become a thing of the past. With autonomous coding solutions becoming more prevalent in the market there are 3 key areas providers can address now to ensure the best outcomes with the autonomous coding solution of their choice:
1. Documentation improvement. Clear and concise documentation is the first key in achieving success with an autonomous coding solution. Coding is only as good as the documentation regardless of how coding is being performed. Utilizing standardized templates which contain all pertinent information to assign CPT, ICD-10-CM and quality codes are best.
2. Coding quality. Since a large component of the coding output is tied to historical coding practices, a provider should have confidence in its current coding quality. Providers should conduct regular coding audits (both internal and external) to validate coding integrity and correct any issues noted prior to implementing an automated solution.
3. Workflow. An efficient workflow is key to any successful implementation. It is essential to evaluate existing workflows and identify and resolve any issues that may be a barrier to implementation and proactively solve them before introducing any new coding solution.
Stacie L. Buck, RHIA, CCS-P, RCC, RCCIR, CIRCC
President & Senior Consultant, RadRx