The Sheep, the Wolves and NLP. A Cautionary Tale.

At the Great ACE Tweet-up (woohoo!) in Austin, TX, we’re going to kick off our series discussing innovation for modern transcription.

We’re going to talk about the reality of keeping transcription relevant into the future – emphasis on reality.

I’m always a bit surprised at how easily our industry finds something that it thinks will be its salvation – its silver bullet. And we’re so ready to believe in a one-size-fits-all solution to all our problems.

But we’re not always so good at making that silver bullet a reality. We go through a lot of hard knocks before we get it right. Look how long it is taking many of us to adopt speech recognition effectively. Seriously – for many of us by now, speech rec should be standard operating procedure. Enough people have done it that the lessons are already learned.  So why do we have to learn the same hard lessons over and over?

That’s why I have concerns about the industry’s new focus on NLP as the means of staying viable into the future.

Just like speech recognition, NLP is not going to be the silver bullet that kills all our werewolves. It’s not a one-size-fits-all, plug it in and let it rip, solution. It will take thought. It will take planning. It will take effort.

Now don’t get me wrong – I’m not saying NLP is a bad thing! I’m saying we have to learn more about it – and more importantly– we can’t expect it to compensate for all of our inefficiencies the way we did with speech rec.

Part of what we will be doing in our sessions is – just like we’ve done with speech rec over the years – stripping away the hype and getting down to the basics of what all this change really means for the clinical documentation industry.

But here is the difference. With speech recognition, we had time. But we don’t have 10 – 15 years to figure out how to make the next saving grace a reality.

There are a lot of gaps that need to be filled before any solution, be it NLP or anything else, becomes a reality for us. There are a lot of claims being made that, I’m sorry, shame on us if we believe without question. I’m hearing some pretty fantastic claims about NLP “accuracy” that I hope we’re ready to give a good hard look at.…just like speech rec! Does anyone remember claims about speech rec in the 90s? Does anyone remember the buzz about how it was going to eliminate transcription?

Let’s ask ourselves some questions…

  • What IS the problem we are trying to solve? How will NLP solve it for us? What do we actually need NLP to do?
  • NLP is not as accurate and as easy to “plug in” as it would seem. In fact, there are MANY different NLPs out there. How do we know which to use for what purpose, and how?
  • If NLP does work for us, do we have the knowledge and skill to make use of it?
  • Do we have the workflow required to accommodate its use?
  • Let’s say NLP “codes” the document accurately and MTs validate it – then what? Is it getting to the EMR by ESP? Osmosis? Telekinesis?
  • Do we know what knowledge will be required for us to use NLP as the tool to take us from transcription to Meaningful Use and the EMR?
  • Do our MTs have that knowledge and skill? Do we?
  • And while we’re busy slashing MT line rates so that the highly skilled ones leave the industry – who will be left with the requisite knowledge to do all this validation and reconciliation?

In a nutshell – who is thinking about the reality versus the hype? Who is thinking about what we need to know to make this real? Are we relying on yet another technology to save us without focusing on what we are at the core?

That’s what is even scarier  – we’re so ready to give away the value of our expertise to the technology companies. Hey folks, technology doesn’t mean squat without the people who make it work!! Part of the reason for low adoption of the EMR is that technology vendors tried to tell doctors what doctors needed instead of listening to what the doctors really need. The people should be driving this boat – not the technology vendors!

Let’s not be sheep this time around ready to follow the first person to say they have a solution for us.

This time let’s ask the hard questions FIRST.

The moral of this story is… This time – Let’s be wolves.


2 Responses

  1. Hi Lynn. I really like your approach to things going on in the industry right now. I am almost a graduate in MT, so a lot of the things you are talking about like speech recognition and NLP, what is that by the way, are foreign to me but I am doing my best to stay informed of the changes and how I can come into this field and adapt myself.

    • Thank you and good luck with your studies!

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