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ICD-10-CM/PCS and Computer Assisted Coding (CAC)

February 11, 2014

ICD CACThe ICD-10 October 2015 compliance deadline will soon be here. Managing the transition from ICD-9 to ICD-10 is especially critical for small practices—a successful transition is vital to their success and often their continuing survival. If they weather the change, they’ll be well positioned to realize improved reimbursement models, lowering their costs while improving the quality of their patients’ patient care. Yet the transition is costly, especially for smaller practices, which typically have limited access to sophisticated conversion technologies, experienced conversion specialists and in depth training programs. The use of computer assisted coding is critical to the success of ICD-10 conversion.

What a Computer Assisted Coding System (CAC) Does

  • Scans EHR documents
  • Identifies key terms using NLP (Natural Language Processing) and other technologies
  • Suggests progress (CPT) and diagnostic codes (ICD-9 and ICD-10) that match the terms

What It Doesn’t Do

  • Eliminate the needed for skilled coders

What a Computer-Assisted Coding System Should Produce

  • Increased medical coder efficiency
  • Better medical coding accuracy
  • Quicker medical billing
  • Increased revenue from better itemized bills
  • Identification of clinical documentation gaps

Does CAC Work?

There are many CAC systems vendors offering their services to practices as the ICD-10 deadline looms. But data regarding CAC’s ICD-10 conversion effectiveness is scant. To aid in understanding the usefulness of CAC technology in ICD-10 implementation, the AHIMA Foundation and Cleveland Clinic jointly conducted a research project to examine the impact of CAC technology on data quality, timeliness of processing and the role and impact of coders on the process. Underwritten by CAC vendor 3M Corporation, this pilot program sought to answer two basic questions:

  • Is there a measurable difference between traditional coding and the use of CAC in terms of coding timeliness and accuracy?
  • Will the use of credentialed coders in conjunction with the use of CAC result in improved timeliness and accuracy?

The Findings

1. CAC, with Coder Support, Reduced Coding Time

There was a 22 percent reduction in time per record for CAC supported coding vs. manual coding. The 25 records used were significantly complex, with an average patient stay length of 16 days.

2. CAC, with coder Support, Did Not Reduce Accuracy

Time to code was decreased without lessening quality, as measured by recall and precision for both procedures and diagnoses.

3. CAC Tuning Improves Precision Over Time

Sophisticated CAC systems utilize “tuning” through natural language processing (NLP) to “learn” over time. Six months after the study was implemented, the CAC’s unaided recall rate “improved for coding both diagnoses and procedures.”

The Cleveland study used a NLP CAC system from 3M that’s marketed to hospitals. The envisioned use of coders in such systems is ultimately as editors who oversee the EHR conversion process, rather than perform it. The cost of NLP-based systems is higher than cross-walk option systems, in which ICD-9 codes map to ICD-10 data through a conversion process implemented in an office’s current claims billing system. The crosswalk systems are a short term solution at best: all systems must be ICD-10 compliant by 2015. ICD-10 crosswalk-provided data often fails to provide needed information to medical management pricing and contract applications, are labor intensive and prone to error.

ICD-9 to ICD-10 Transition Outcomes

ICD-10 transition workflow and best practices planning should focus on achieving basic, well-defined outcomes:

  • Clinical equivalency: Use of either the ICD-9 code or its equivalent ICD-10 code defines the same attributes of patient care, medical necessity and treatment outcomes.
  • Benefit neutrality: Use of either the ICD-9 code or its equivalent ICD-10 code produces the same member coverage, without increasing member premium or out-of-pocket expense.
  • Financial integrity: Either set of codes results in the payment of appropriate benefits by the insurer and the appropriate financial contribution by the recipient.
  • Operational stability: Accuracy metrics such as auto-adjudication frequency and claims payments are at equivalent acceptable levels under either the old or new codes.


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