Computer - Assisted Coding
November 15, 2009
Computer –assisted coding (CAC) is a computerized tool that automates a set of medical or surgical codes, based on clinical documentation from a healthcare provider, which is used for review and validation. With the assistance of these new automation tools, coding or HIM professionals can easily translate clinical data input into useful clinical data output. Increased amounts of clinical coding is done by machines, which saves time and human participation for more complex coding cases and data analysis tasks. Factors, such as advances in natural language processing, EHR adoption, compliance issues and ...view middle of the document...
Secondly, the complexity is exacerbated by payer- specific modifications, which creates the need to code or process the same procedures differently, depending on the payer. Third, continuous coding education and re- training is necessary due to the constant coding and regulations changes over time. Finally, the generation of charges and claims follow ups are sometimes disconnected in time and space and many times, are performed by different people which adds to the costs of the claims processing cycle.
Currently, there are two formats of CAC technology; Natural Language Processing (NLP) and Structured Input. Much like language translation software that translates one language from another, NLP software can translate data from clinical language into the language of CPT/ ICD 9 CM codes. In NLP, artificial intelligence is used to extract pertinent data and clinical terms derived from text – based documents and they are then converted into a set of codes to be used or edited by a coding professional. This software is often referred to as the NLP “engine”. Coders, first, begin by reviewing suggested codes instead of coding from scratch. The NLP system allows the coder to review, edit, approve and finalize codes for each record. By using a recommended list of codes, coders will improve their productivity and elevate their role from researcher to quality data analyst.
Within NLP, there are two approaches to NLP software. The rules – based approach creates an understanding of clinical words and phrases and the medical codes that are used to report these words and phrases with a complex, extensive series of rules. This approach is also called the knowledge – based approach because CAC’s coding ability depends on the coder’s expertise to provide the complex rules to properly assign code numbers to words and phrases. The statistics – based approach creates an understanding of clinical words and phrases and the medical codes that are used to report these words and phrases with a large body (or corpus) of reports. This approach is also called the data driven approach because the coding ability of the software is based on a group of statistics. The software predicts the appropriate code that should be assigned to a given word or phrase based on the statistics that indicates the assigned code to these words/phrases in CAC’s corpus of data.
Currently, NLP is starting to become prevalent in specific clinical settings. It is most effective when transcription system interfaces is available and the system can be remotely accessed. NLP works best in outpatient settings. Outpatient’s clinical documentation is often electronic and there are limited medical terms listed. Also, NLP engines work well when electronic data and text files are received from an electronic template, diction, or speech recognition system. Although transcription is not necessary for CAC, it is suggested that transcription interfaces are to be implemented for optimal workflow.