With almost 20 years of practical experience deploying speech recognition technology in the healthcare arena, I believe the current reality is that cloud-based healthcare speech recognition is here and viable …

If you use an Apple or Android device, you’ve probably noticed the increased accuracy of these platforms’ dictation capabilities. A few of my friends have migrated almost entirely to dictating their text messages. This makes me wonder “why not just make a phone call?” However, my analysis of the cultural aspects of texting will have to wait — this post is about enterprise dictation.

With the advent of the EMR, providers are doing more and more with regard to patient data input. From a provider perspective, additional time spent in front of a computer means less time working with patients.

Real-time (or “front-end”) speech recognition at the point of care has made some providers more efficient, but it’s not a universal solution. Whether it’s the time required to learn the system, specialized workflow needs or their unique speech patterns, many providers are just not a good fit for front-end speech recognition. When they don’t have another option, frustration ensues.

It is well known in the electronic medical record (EMR) journey that there is a tangible difference between EMR implementation and EMR adoption. The implementation phase, a well-defined, subsidized, singular event, has been compared to a wedding: while significant, it’s not necessarily predictive of the long-term outcome. The adoption phase, in contrast, is rarely defined, difficult to measure and requires a level of engagement and commitment that is often overlooked.

To our fellow HIMSS attendees:
The nVoq Healthcare team will be onsite next week at HIMSS and welcomes the opportunity to talk toyou about SayIt – the true cloud-based platform that’s affordable, accessible and a great alternative tomore expensive speech recognition solutions.