White Paper: Advanced Coding Technology Can Advance The Revenue Cycle

By Mark Morsch, OPTUMInsight

Coding is changing. ICD-10 is looming larger on the horizon, and financial leaders are right to be fearful of its potential effects. Natural language processing (NLP) and computer-assisted coding (CAC) are advanced coding technologies that can alleviate some of the challenges faced in healthcare organizations today.

In the 1970s, coding was strictly a recordkeeping exercise. Today, it is an essential conduit for provider revenue. It's no wonder that finance leaders are paying more attention to it. As coding has become more important, tools have also progressed to help organizations code better, faster, and with greater compliance. Coding tools that saved time and money in the 1990s and 2000s, such as encoders and online coding references, are starting to become less important as more advanced technologies have matured. Those technologies include computer-assisted coding (CAC) and natural language processing (NLP).

CAC and NLP are interconnected in their importance to revenue integrity. The financial benefits of CAC software depend on the effectiveness of its NLP, while the operational impact of NLP directly relates to the usability of its attending CAC interface. In this paper, we will discuss how NLP is the most critical component for CAC to keep its promise of decreasing time to revenue and improving reimbursement accuracy.

New Technology Will Improve Coding Speed And Accuracy
Using a tool such as CAC that reads and interprets an entire electronic documentation set in seconds; coders will spend less time coming up with accurate codes. Moreover, CAC can help coders come up with a more complete set of codes, capturing important complications and comorbidities that are often missed in a large, complex record. That leads to more accurate reimbursement. Greater accuracy could also lead to a higher CMI (case mix index), as well as reduced denials and rework. Additionally, improved accuracy improves coding consistency, limits compliance risk, and improves the bottom line.

Finance leaders are wise to be wary of promises of improved coding speed, accuracy, and reimbursement. The fact is, CAC vendors can deliver these promised improvements only at varying degrees. The variable that determines how well they can keep those promises is the technology that makes CAC possible — NLP.

Natural language processing technology scans and interprets narrative text. With NLP, information included in dozens of documents can be transformed into discrete, meaningful pieces of data within seconds. The term "NLP" identifies a set of technologies and approaches, each of which differ in effectiveness. In general, NLP technologies available today fall into one of five methods which are outlined in this white paper. To understand how these methods differ, we will also define the standard measurements of NLP accuracy.

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