Updated on: June 22, 2012

Attack the RAC with CAC

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Original story posted on: October 21, 2010

dlang100Applying the right kind of computer-assisted coding (CAC) software can help organizations proactively mitigate the impact of RACs. But before we explore how, let's first define what specific type of CAC we mean.

 

In the industry today, CAC has taken on many different meanings. Some refer to encoders as a form of CAC, while others refer to text highlighting as another form. The more "sophisticated" CAC will have NLP (natural language processing) and speech-interpretation technology driving the automated code assignment.

The type of CAC software that will help you proactively defend against RAC activity is the kind that incorporates automation for coding workflow and process.  CAC that gives you the ability to set up coding work pools specific to RAC-targeted cases, coupled with an automated pre-bill quality assurance routing process, is a tremendous benefit.

 

CAC on the Attack

 

Let's suppose you want an auditor or reviewer to look at certain targeted RAC cases after the record has been coded but before the codes are sent to billing in order to make sure the necessary documentation is present and the code assignments are correct. You need to get these completed cases to this auditor or reviewer quickly, because you don't want to create a negative impact on your DNFB (discharge not final-billed).

 

Here's how it works with the "right kind" of CAC software.

 

A manager can create a work pool in the system called "RAC Review." The reviewer's profile lets the system know who is eligible to review the cases. The system includes a workflow feature called "automated workload assignment," creating a setup that means when an eligible reviewer logs into the system, the targeted cases (if there are any) automatically are routed to the reviewer's work queue. Work pool prioritization means these records will get routed before any others so DNFB isn't negatively affected.

 

CAC and Excisional Debridement

 

How does the system know a record is "eligible" for targeted review? An additional feature of the "right kind" of CAC software is the ability to set up unlimited pre-bill QA rules. These rules can be based on a number of variables. From a RAC attack perspective, a rule can be established for each targeted case.

 

Let's look at an excisional debridement case as an example - if this isn't one of your RAC targets, it should be. The manager would create a rule that basically sets the system to funnel all charts that have an excisional debridement procedure code (86.22) to a certain reviewer when the coder has completed the record. Any reviewer assigned to the "RAC Review for Excisional Debridement" work pool receives this case in their work queue upon logging into the system. The case identification and routing is handled by the system.

 

Take it to the next level. Add to the automated workflow management the coding automation offered by the "right kind" of CAC software.

 

CAC software that not only provides text highlighting, but also natural language processing with speech-interpretation technology, is of great value when trying to manage RAC impact proactively. We know that in the case of NLP assigned codes, the software system should highlight the associated text.  In addition, the coder may highlight additional text to support further coding, particularly any code assignment that is entered manually (because the documentation may be handwritten and scanned, for example). These computer- and human-generated text highlights are stored and retained to streamline justification, or showing the RAC why a case was coded a certain way.

 

Suppose we can deploy the automated workflow and NLP-enabled coding concurrently. How would that proactively manage RAC impact?

 

Think about RAC targets for which you know specificity in documentation is paramount. If you could identify these cases immediately and get them incorporated into your concurrent coding/CDI reviews, you would have the opportunity to ensure that documentation reflects the level of care that is given, meaning that appropriate codes are assigned and paybacks to the RACs can be avoided.

 

Let's assume that mechanical ventilation is a target, because in order to code for it, specific documentation is needed, and RACs know that this level of documentation often is missing.

 

CAC in the ER

 

Now, a patient comes to the ER and is admitted with a preliminary diagnosis of respiratory failure. The ER record is coded by the NLP technology in the CAC application, and respiratory failure is assigned as an admitting diagnosis. There is a clinical documentation improvement/concurrent coding work pool for "respiratory failure admits" set up already in the system.

 

Your policy is that a clinical documentation improvement specialist (CDIS) or coder reviews every respiratory failure case within 24 hours of admission through the ER, and every two days thereafter while the patient is in the hospital, to ensure that the documentation supports the level of care being provided and the codes are reflective of the documentation.

 



 

To facilitate this concurrent clinical documentation improvement process, the "right kind" of CAC software must have an integrated physician query feature.  The CDIS/coder can query the physician concurrently to point out documentation improvement opportunities. Utilizing the same automated workload assignment feature we mentioned earlier, the case will appear in the CDIS/coder work queue for an updated review every two days while the patient is in the hospital.

 

These are just a few examples, but there is no end to the possibilities of proactively attacking RAC impact when using the "right kind" of CAC software.

 

About the Author

 

Dee Lang is the Vice President of Coding Technology for Precyse Solutions and is based in Greensburg, PA. She provides oversight and direction for the automated coding technology solution offered by Precyse.  Dee has a background that combines experience from acute care hospital information management, to corporate level positions in business development, marketing, and product management, to owning her own consulting business. Prior to joining the vendor space, she served as the HIM Director at Mercy Hospital in Pittsburgh, PA.

 

Contact the Author

 

dlang@precysesolutions.com

 

 

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