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ICD-10 Intelligence

ICD-10 Accuracy: Beyond the DRG

Anecdotal data seems to suggest ICD-10 coding accuracy is strong with minimal payer denials.

Q: Our ICD-10 coding audits seem to suggest a high level of DRG accuracy, but we're wondering whether our coded data could be more specific. Are other organizations curious about this as well? Have accuracy standards and expectations begun to emerge, or are best practices still largely unknown?

Kudos to your organization for peeling back the layers of its coding audits to take a closer look at the findings. Accurate DRGs definitely do not imply coding accuracy. It isn't pleasant to uncover coding problems, but it's a necessary part of ensuring compliance.

Following are several other reasons why it's important to monitor coding accuracy:
  • Ensure accurate outcomes data that drives value-based reimbursement
  • Avoid auditor denials and recoupments
  • Enable detailed data analytics and research
With that said, anecdotal data seems to suggest that coding accuracy post-ICD-10 implementation has remained largely unchanged. In addition, many organizations have reported minimal payer denials. This logically leads us to the conclusion that the transition had minimal impact. This would also corroborate your organization's own findings.

Most recently, AHIMA published a study that also seems to suggest that accuracy rates remain high. Approximately 27% of the 156 coding professionals participating in a recent survey conducted by the AHIMA Foundation reported that their accuracy decreased by only 0.65% during the first three weeks of May. Interestingly, nearly 12% reported an increase in accuracy. Nearly 62% saw no change in accuracy.

"Health information management (HIM) professionals are already coding with the same degree of accuracy as in ICD-9," said AHIMA CEO Lynne Thomas Gordon, MBA, RHIA, CAE, FACHE, FAHIMA in a press release about the survey.

"We anticipated seeing a dip, but were glad to hear from folks that while they did have an initial large dip it is now settling back to pre-ICD-10 levels, though slowly," said Kate Jackson, RHIA, the Foundation's research manager, in the press release.

On the surface, it seems as though coding accuracy has remained intact. However, can we truly rely on this feedback and assume that all is fine?

Simply put, the answer is no. We need to continue to pursue further analysis. The AHIMA Foundation survey is a start, but it's important to recognize that the survey is based on self-reported data regarding the perceived effects of the transition. Hard data collected in real time may paint an entirely different picture. This is certainly something to keep in mind as various associations, vendors, and others publish coding accuracy benchmarks and standards. We must be mindful of the sample size, diversity of participants, and specific methods for data collection.

In addition, remember that DRG accuracy doesn't necessarily equate to coding accuracy. At HRS, we've seen many instances in which cases map to the correct DRG even despite the fact that coders default to unspecified codes. Technically speaking, this is not accurate coding. And this is the type of coding that could eventually put organizations in a financial bind when auditors recoup money and/or deny claims.

Coding Accuracy Audits: 5 Tips

Monitoring coding accuracy is paramount. However, we must shift our priorities. New challenges have emerged in ICD-10 that require our attention. Consider the following tips to get the most out of your coding audits:

1. Set realistic expectations. What was the accuracy level pre-ICD-10? If coders had a 92% accuracy rate in ICD-9, you certainly can't expect a 98% accuracy rate in ICD-10-at least not during the first year post-go-live.

2. Dive more deeply into audit findings. Is the problem with accuracy something that was also a problem in ICD-9, or is it specific to ICD-10? This helps pinpoint educational opportunities and identify areas of vulnerability. It also helps put accuracy statistics into perspective. If 98% of coding errors occur due to ICD-10 guidelines that were the same in ICD-9, then the transition likely had minimal impact on accuracy rates. These problems would have existed regardless of the shift to the new coding system.

3. Monitor unspecified codes. In how many instances is a more specific code available and documented? Hyperlipidemia is an example we see often. Coders don't code the specified type even when documentation is available. Our auditors also frequently see unspecified codes related to the following diagnoses:
  • Fractures
  • Pneumonia
  • Respiratory failure
  • Atrial fibrillation
It may be easier-and faster-to default to an unspecified code, but these codes could cost the organization in the long-run as payers continue to refine their policies and edits.

4. Validate 4th and 5th characters. How often are these characters correct? Do coders frequently default to either the left or the right when reporting laterality, for example?

5. Consider the effects of computer-assisted coding (CAC). According to the AHIMA Foundation survey, those who coded using CAC experienced a 0.2% increase in accuracy. Interestingly, those using CAC also reported a 17% decrease in overall productivity. The productivity decrease could be due to the fact that some CAC tools require coders  to essentially train the CAC before it is fully effective. CAC can help guide coders to the right category of codes, but depending on factors such as the documentation location and format, the coder  are still responsible  for further assigning that code to the highest degree of specificity. Over time, the accuracy rate should continue to increase.

Let Accuracy Trump Productivity

It's possible to pass an audit with flying colors and still have 'sloppy coding.' Ensure that coders follow use these strategies to boost compliance:

1. Review the entire record. Don't simply peruse the few first progress notes or the history and physical and discharge summary. Radiology reports and other documentation could provide critical information to move an unspecified code to a more specific diagnosis.

2. Think quality over quantity. Accuracy should always take priority over productivity.  

3. Take the time to guide CAC toward more specific codes. By finding the more specific documentation, coders can teach the CAC to automatically search for that language. This will eventually pay dividends in terms of productivity.

At the end of the day, the goal is to capitalize on the added specificity inherent in ICD-10. This was one of the main reasons the industry transitioned to this new and more complex coding system. Ensure that your codes reflect the highest degree of specificity possible. Not only is it the right thing to do, it will help the organization to move forward both financially and operationally.

Jonathan LaFleur is auditor, and Julie Boomershine, is manager of coding operations, both at HRS.

Boomershine has more than 20 years of experience in HIM. She holds an associate's degree in health information management from Davenport University in Kalamazoo, Mich. and a bachelor's degree in health information management from the University of Cincinnati.

LaFleur has more than 16 years of healthcare experience, both at the bedside and in HIM/CDI. He is a registered nurse in the state of Michigan and prior to joining HRS worked in two emergency departments and as a charge nurse in the medical ICU at a level I teaching hospital.

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