Why Medical Coding and Billing Software Desperately Needs AI

September 7th, 2022 - Find-A-Code
Categories:   Coding  

Why Medical Coding and Billing Software Desperately Needs AI

It has been said that the healthcare industry is notoriously slow in terms of technology adoption. Whether or not this is true across the board, it is at least a viable argument in the business side of medicine. One need only look at how convoluted medical coding and billing are to know that it needs a technology injection. Specifically, medical coding and billing software desperately needs artificial intelligence (AI).

Software developers are working on the AI issue even now. One of the more recent offerings is a software tool from a California company known as Aesop Technology. It is a software tool that helps both clinicians and medical coders spot diagnostic errors without having to spend an inordinate amount of time on research. Errors can be corrected with just a few clicks.

The company says their clients who have already used the software are reporting increased per-patient revenues of up to 10%. That is impressive all on its own, but the benefits go beyond increased revenues. Because clinicians and coders do not have to spend so much time looking up diagnostic codes, they can get more done in the same amount of time.

Hundreds of Thousands

If there was ever an industry that needed AI, it would be medical coding. Coding specialists look up diagnostic codes from no fewer than six systems. The most common system is ICD-10. That system alone offers more than 160,000 different codes. That says nothing of the CPT, NPI, and other systems.

With so many codes and different ways to utilize them, coding is almost guaranteed to generate errors at the clinical level. Doctors, advanced practice nurses, registered nurses, and office staff have enough on their plates just getting patients in and out. Clinicians want to focus more on diagnosis and treatment. Expecting them to be experts at coding is simply unrealistic.

It is understandable that clinicians would be frustrated by the coding process. They are equally frustrated by complicated electronic health record (EHR) systems that were supposed to make their lives easier. So, in terms of correct coding, they have a lot working against them.

What Artificial Intelligence Does

It goes without saying that nearly all the mistakes that occur in medical coding are the result of human error. But we accept that those errors are inevitable because of how convoluted the medical billing system is. Without changes to the system, errors cannot be eliminated. That is why the system needs AI.

In a generic sense, AI replaces human effort in tasks for which that effort is either unnecessary or proves inefficient. AI systems are able to crunch incredible amounts of data in a very short time, allowing them to artificially make decisions based on comparing data points.

Imagine a system that runs in the background of a medical practice's EHR. Whenever the doctor writes notes or assigns codes, the system compares that data to historical data from that particular office. Additional data from other sources is brought in as well. By comparing the data, the system can predict that the doctor is about to make a coding mistake. It can suggest an alternative which the doctor can 
accept or reject.

This sort of system does not have to be limited to EHR. It can be built into coding and billing software as well. That way, AI is looking for potential problems at all three levels of the billing and payment system.

There is much more that AI can do to improve medical coding and billing. Its time has come. Medical coding and billing software desperately needs what AI offers, and it needs it now.


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