Through the application of natural language processing or NLP, electronic health records are being improved in terms of physician use.  Point and click templates have always been resisted by physicians to document visits by patients within EHRs.

As an alternative, physicians prefer speech recognition software programs that actually transcribe the dictation into the EHRs. In order to show use that is both meaningful and effective, physicians are required to enter a particular amount of structured data.  In an effort to make this process easier for users, electronic health records vendors are trying to improve input that imbeds natural processing language software directly into the products.

Let’s look at a brief overview of what natural language processing is and how it works.  NLP describes a process of technology where communication is naturally presented to humans via spoken language or text.   New studies reveal that NLP, a branch of computer science that employs both linguistics and regular speech, may increase the effectiveness of record keeping and improving care for patients.  This is why physicians are taking notice of NLP and asking that their EHRs include this processing.

Researchers show that natural language processing actually improves accuracy in records and is much more effective than other automated systems.  Why is this?  Harvard Medical School offers some insight into the question, stating that clinical data can finally be used to measure patient safety more systematically and methodically.  The practice ensures accuracy, which is something that has never been seen in the medical community.  Great benefits are being brought to manage care, which niche is extremely needful for these kinds of approaches.

The Need for NLP

Seen throughout the medical community of managed care is the need for electronic health records to provide computerized tracking of both patients and associated networks of institutions.  This is needed to detect whether or not a patient is at risk for complications.  This may be one specific complication or an array of several complications.

This also shows whether or a not a specific department or hospital is performing at a lower credential than others.  The tracking is needed in order to allow administration and other key players to help with quality assurance and improvement throughout the network.  This is something greatly needed in managed care.

The growing need for this sort of application is on the rise.  It is becoming more and more difficult to detail these components without an automated tracking system, such as the NLP.  When the information cannot be accessed or is non-existent, it is impossible for the facility to take notice or improve.

Tackling these critical issues is a must and through the natural language processing algorithms in place, is now a possibility across the medical community.  The algorithms set forth incorporate particular rules of speech and language directly into the analysis.  This is exciting news for medicine and particularly, for doctors.  Improvement is needed and without the use of this kind of technology, healthcare is taking a terrible turn for the worse.