AMIM Annual Symposium in Washington DC

How can NLP transform patient care?

November 26 2014

Natural Language Processing (NLP) is a hot topic in healthcare.

At this year's AMIA Annual Symposium, in Washington DC,  we brought the discussion on clinical NLP to a roundtable held on Monday lunchtime and were also invited to the AMIA NLP workgroup to present some real-life use cases in clinical NLP.

However, as much as we like sharing what we're doing, we were keen to know what other people think when it comes to how NLP can transform patient care, today and in the future.

So that’s what we did – we asked peers at the AMIA conference that question (How can NLP transform patient care?) as part of a contest with an incentive of an iPad Mini and $50 Starbucks voucher for 1st and 2nd place respectively.

More than a third of entries identified mining the unstructured, free text narrative of a medical record to be crucial to the transformation of patient care. Unsurprising really, if you consider that around 80% of data in an electronic health record is unstructured and the only real way to get this information into a useable format is using NLP.

But what was interesting was the difference in how to use this data. Ideas included; for better patient information, for using the extracted coded concepts in clinical decision support and to retrieve full patient cohorts.

It was a tough contest to judge but the winning entry came from Edgar Chou at Drexel University College of Medicine. He had a few ideas but the one we thought was most interesting, with the potential to have the greatest impact on patient care was to around the payer care mix.

"Use NLP to extract textual data to supplement existing structured data for more accurate reporting to payers, increasing dollars assigned to all patients due to more accurate capture of diagnoses."

 After all, better diagnoses and more money are decisive factors in the ability to provide better patient care.

The funniest and, probably, most creative entry (though not quite so "on topic") was the NLP list poem:

Nobody Likes Problems
New Learning Possible
Natural Language Processing
Now Let’s Purchase
New Linguamatics Product
No Lost Physicians
Normally Living Patients
Written by: NL-P (Netherlands Person)

But unless we count purchasing "new Linguamatics product" as transforming patient care (we can't be biased now!), then it doesn't quite fulfil the criteria.

Our runner up entry from Tyler Tippetts, University of Utah, was creative and puts patients at the heart of their own care. The idea of using NLP on patient-generated data: imagine if patients linked their Facebook and Twitter accounts, for example, to their EHR or PHR and let it be processed to detect symptoms - letting patients potentially help themselves.

A significant challenge for Meaningful Use 2 is patient engagement, integrating EHR with social media could be a key way for NLP to impact patient engagement,  providing issues of Protected Health Information are properly addressed.

Certainly, the mining and mapping of tweets for disease control and understanding has been used in the past and maybe this is a future use of social media. It could be particularly useful in understanding mental health and state of mind.

The competition is now closed but if you have any comments or other ideas you’d like to share on how NLP can transform patient care please do let us know via this blog, on Twitter @Linguamatics, Facebook, LinkedIn or Google+.

We thank everyone who took part in the competition and look forward to running another one again soon.