Over the last four decades, various technologies have been created for the express purpose of focusing on the generation, presentation as well as the application of various forms of clinical information in the healthcare industry as a whole. These are more commonly referred to as ‘health informatics’ or just ‘Health solutions’. These solutions have been steadily experiencing substantial growth, especially over the past few years.
Health informatics essentially enable the clinical data to be easily accessible (to duly authorized personal, that is) through different computer networks for the express purpose of improving and by extension, leading to more positive health outcomes for patients in general.
Here, speech or voice recognition in particular, also presents a few highly interesting applications. Basically, voice recognition or VR systems are composed of a single or even series of microphones that are designed to convert sound waves (such as a person’s voice) into electrical signals.
Once that happens, sound cards then proceed to ‘digitalize’ these electrical signals so that they could easily be read by the relevant speech engine software. This software has the capability of converting this raw data into highly usable text.
If done correctly, if can easily eliminate the many layers that exist between the clinician and the actual print out of the report that ends up being a permanent record at the health care facility.
There are many benefits of speech recognition in healthcare. It can effectively increase the overall productivity of the entire department, since there will be no time lags between the speaker and the text. Once this has been done, the doctor can visually check for errors and rectify the same in real time, acquire a printout and sign it off so that it can become part of the medical facility’s overall patient record database.
However, as with all things there are certain issues that need to be ironed out before the technology goes into full production. For example, dealing with ambient noise issues is still a major problem with regard to speech recognition technology and its implementation in any health care facility.
Almost all hospitals and other ancillary facilities, by their very nature, are intrinsically very noisy, what with screaming children, PA systems and patients and doctors all talking simultaneously.
Under the circumstances, it is often not that easy for the speech recognition software to be able to pick up the specific voice that it is supposed to turn to text. When words not related to the task at hand get through into the system, they have to be manually corrected by the doctor himself. This leads to a possibility of human error that can have potentially serious consequences.
Apart from that, substantial time has to be spent in training not just the operators, but the software itself, to be able to differentiate in between the subtle nuances of human speech and accents lest it makes a mistake.
In the light of the above we can say that while there are very many advantages of using this technology, but nevertheless they also come bundled with their own intrinsic challenges as well.