What is the true value of computer-assisted coding (CAC) in the conversion to ICD-10? The consensus answer seems to be the productivity gains associated with the use of this technology.
Understandably, disrupted cash flow resulting from discharged patients whose bills have not been finalized is a valid concern as organizations prepare for the transition to the unknowns of ICD-10.
Specifics about productivity gains gleaned from CAC still have not been completely vetted, due to various factors. I don’t necessarily see CAC as a productivity enhancer, as its benefits are offset to some degree by the fact that the volume of codes in ICD-10 is too immense, meaning it is impossible anyone to truly know much for sure at this point.
Claims of productivity gains ranging from 10 to 50 percent seem too-far reaching for my tastes, and I remain reluctant to form any definitive conclusions about such projections. The increased number of codes, clinical documentation specificity requirements and the introduction of a new technology tool all will impact the coding process and time necessary to produce an accurate and complete claim.
Another major variable is the electronic medical record (EMR) content, specifically regarding what constitutes codeable content and non-codeable content within the EMR. While many organizations have an EMR, many use hybrids containing documents that cannot be processed by CAC technology. Therefore, additional time is required for coders to review this information for complete and appropriate code assignment.
But what about the gains in the fields of coding quality and data collection through the use of CAC? Shouldn’t the focus of computer-assisted coding be on the potential for improved quality of coded data? Since “big data” is transforming how business is done in so many industries, many of the experts are in agreement that big data is going to become even bigger with ICD-10 coding.
ICD-10 specificity will enable deeper data mining, allowing providers to make smarter predictions and conduct better analyses to improve everything from fraud detection to patient outcomes. As we continue to navigate the changing healthcare landscape with Accountable Care Organizations (ACOs), population health management, and value-based purchasing, providers will rely on harnessing such “big data” to create actionable insights, improve care and reduce costs.
I understand the focus on productivity offered by CAC, considering the anticipated coder shortage, productivity losses due to ICD-10 specificity, impacts on cash flow, etc. However, with the emphasis on the importance of data analytics, wouldn’t improved coding quality and data collection eclipse any productivity gains associated with CAC?
To me, the value of such technology lies in the organization of electronic information in a manageable way, so that an individual can make the final critical decisions on what codes should be assigned to a medical record. The single most important attributes of a coder is his or her critical thinking skills and the ability to analyze information presented to them in the medical record and apply the appropriate guidelines. I see CAC as a navigational tool intended to assist in validating the documentation within the EMR. Recognizing this adds an auditing step into the traditional coding process that is not being accounted for at the current time.
So I think it is time for us to ask ourselves: Is the true value in CAC technology reflected in productivity or improved data outcomes? Present the following question to your staff, and to yourself: Does improved data quality, data collection, compliance and accurate reimbursement eclipse any productivity gains from CAC technology? Ask your CFO, CCO, and/or CMIO for their perspectives on the value of this technology.
I think you will get quality answers.
About the Author
John Pitsikoulis, RHIA, is the ICD-10 practice leader and an AHIMA ICD-10-Approved Trainer for Nuance Communications. John has more than 28 years of revenue cycle, health information management, coding, and compliance consulting experience. John has developed and led several corporate and client strategic engagements for managing the conversion to ICD-10, including ICD-10 assessments, implementation planning, integrated testing, education plan management and revenue preservation strategies.
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