Electronic software applications (CODING) - Essay Example

Study carried out by the 3M Health Information Systems revealed that NLP system is accurate and effective, particularly in assigning CPT and ICD codes (Wolnniewicz, 2011). Since that time, other studies have shown that tools utilizing NLP have become increasingly more effective. As a result, NLP have great benefits in the arena of healthcare, for example, in outpatient coding, which is the focus of this paper. One of the benefits of NLP is that it has the ability to provide instant feedback to health professionals or physicians about clinical data.

This in turn enables them to provide meaningful and complete notes, as well as answer other additional questions right before patient leaves the room (Warner, 2000). Another advantage of using NLP in outpatient coders is that it is accurate and does not miss a code. Therefore, it ensures that no code is left behind, and in addition, each code that it presents and highlights to the coder is consistent. Furthermore, it allows pleasant mapping back to document or source where the coder obtained the codes and this is highly essential in retrospective auditing.

Hence, NLP in outpatient coding ensures high accuracy, which in turn leads to productivity in the healthcare system. It is possible to say the NLP in clinical coding enables the best of both worlds because using the NLP with the natural speech documentation capture provides physicians with a way to tell a complete story about a patient with all its subtitles. In addition, it avails all clinical information and fact required for EMR’s optimum operation. NLP works beyond a query tool to assume the major component of the point-of-care process assisting doctors with real-time patient’s information in which a medical record is being documented (Tsunoda & Wong, 2000).

It also acts as a guide to physicians in order to incorporate most accurate and thorough information about patients while dictating their notes. NLP in outpatient coding allows doctors to be efficient when handling documentation, ensures that the medical records of a patient are not condensed, purely structured content, which is developed by point-and-click templates, thus, are comprehensive. Moreover, it also supports the healthcare system or facility in complying with government regulations such as the HITECH.

This in turn ensures optimization of care and maximization of reimbursement. The pros of NLP is that it is capable of coding both inpatient and outpatient charts among other elements, and it provides the fastest and most accurate in coding results. NLP is capable of highlighting key phrases and terms in order to generate recommended codes for CPT and ICD-9 CM coding automatically (Dunne, 2013). Another pro is that NLP can understand, analyze and generate languages used by humans naturally, thus, it can interface with computers in both spoken and written context using human languages rather than computer languages.

Other pros of NLP outpatient coding is security of the data or patient information, as well as flexibility for outpatient operations. This in turn enables physicians and other healthcare workers to serve patients efficiently, thus, enhancing productivity. Use of NLP for outpatient coding may also prevent establishment of a claim that insurance company will deny for insufficient specificity. It also reduces chances of coders coming back to physicians for more clarity, even weeks