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Understanding ICD-10: Computer Assisted Coding

By Jennifer Bresnick

- Providers struggling with the ICD-10 transition – and there are many, many organizations who are – may be looking to technology to help them conquer the obstacles that lie ahead of October 1, 2014.  One of the biggest challenges will be keeping productivity at its previous level, to ensure a steady flow of revenue from claims, and many providers are turning to computer assisted coding (CAC) to supplement their coding work.  But CAC isn’t a magic bullet, and providers need to understand its benefits and limitations before leaning too heavily on automated coding tools.

What is computer assisted coding?

CAC is any software that attempts to draw information from clinical documentation and assign an ICD-9 or ICD-10 code to that data.  The program uses natural language processing (NLP) to analyze the plain-text documentation and determine whether a particular medical reference requires an ICD code or not.

For example, a notation of “heart disease” in a patient’s chart may need an ICD-10 code if the provider is making a diagnosis or providing services based on that condition.  But “family history of heart disease” does not.  The software can determine which is which, then select a code, or a group of codes, that may be applicable to the situation.

While most of these programs still require a degree of human intervention, NLP is reaching the point of being sensitive, capable, and increasingly reliable.  As a result, human coders are spending less time scanning complex documents and more time getting claims out the door.

How can it help with ICD-10?

ICD-10 introduces a new coding structure and an enormous amount of clinical detail that is less familiar to ICD-9 experts.  CAC can reduce the amount of time a coder needs to search for and identify the proper code by guiding the coder to the right area automatically.

On routine procedures or large batches of documentation, CAC can cut the amount of human effort significantly.  This is a major benefit to workers concerned about predictions of a major drop in the number of charts per hour an individual will be able to handle as they get used to ICD-10.

What are its limitations?

While major vendors such as Nuance, M*Modal, and 3M tout the benefits of their CAC systems to streamline workflows, reduce productivity burdens, and smooth the way for a painless ICD-10 transition, CAC does not replace the need for improved charts and coder education.

Without detailed, specific documentation, a CAC system will have nothing to work with.  Many ICD-10 codes require an ontology that simply doesn’t exist in ICD-9.  Physicians must learn to provide the level of detail necessary to get to the most specific ICD-10 code or even the most powerful CAC software will be useless.  Coders must still be aware of when an ICD-10 code properly matches a diagnosis and when it doesn’t, so they can provide an accurate safety net if the computer gets it wrong.

CAC does not replace training and education.  It does not replace competent coders and solid documentation.  Providers integrating CAC into their ICD-10 workflows can’t rely completely on software, especially during the early transition days when payers, clearinghouses, and vendors are still getting on the same page.  CAC may be an excellent way to supplement the process, but human intelligence is still irreplaceable.

How can I use CAC effectively?

Use CAC as a supplement for your coders and physicians as they learn to navigate the new pathways of ICD-10.  CAC can provide a framework and methodology for tackling the new requirements for improved documentation, but people still need to do the work.

Customized EHR templates that ensure information is collected in a structured and computer-readable manner is one important element of harnessing the power of a CAC system.  Testing and identifying the strengths and weaknesses of a chosen CAC system before go-live will also help human coders fill in the gaps where necessary when financial reimbursement is on the line

CAC is just one weapon in the arsenal when it comes to ICD-10.  While automation can help reduce the burden, it can’t do all the work.  CAC is an extremely useful tool to help coders parse through patient data, but detailed, complete documentation and a solid understanding of the requirements of ICD-10 will be equally as vital in the run-up to October of 2014.




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