Pondering DNA at The Eagle, Cambridge

I was recently privileged to have a pint of Guinness at the Eagle in Cambridge with some colleagues after work in our U.K. office. The Eagle is a historically significant pub in the area of DNA. Two things came to mind:  1) What is it with the number 51 and controversies? Area 51 and Photo 51 both bring up their own issues...and if we combine the two it would get really interesting...Alien DNA. Now that would be a good pub conversation! Especially here at the Eagle, where James Watson and Francis Crick theorized DNA’s helical structure.  And 2) I wish Rosalind Franklin could have lived to see how things are evolving in precision medicine.

Linguamatics is pleased to congratulate US healthcare system Mercy on their recent award win at the 12th Gateway to Innovation conference. Mercy won the Innovative IT Project of the Year Award for using Linguamatics I2E Natural Language Processing (NLP) solution to extract clinical analytics insights from their Electronic Health Records (EHR) notes for cardiac patients.

Mercy Technical Services provides contract research services for medical device and pharmaceutical clients to support use of real world evidence (RWE) in Food and Drug Administration submissions. This award recognizes a project that demonstrates value or impact to the organization by solving a business problem or by addressing a specific strategic objective for the company.

NLP used to Extract Real World Evidence from EHRs

As a large health system with a mature and consolidated Epic EHR system, Mercy has a significant data set of patient treatments and outcomes. There is a multitude of information documented in the EHR, such as lists of specific symptoms, diagnoses derived from echocardiogram reports, and certain benchmarking classifications. Since typically 80% of this information is unstructured text, many valuable clinical insights are unavailable in discrete fields, and therefore vital patient information can be trapped when making clinical decisions.

NLP text mining platforms like Linguamatics I2E extract information from unstructured text-based EHRs and transform it into actionable insights that can be placed into a dataset and analyzed.

The Philosophy of Yin and Yang

The idea itself is relatively simple- all things exist in a state of entanglement and contradiction to themselves. Like my favorite geeked out analogy - Star Wars with the light (Yin) and the dark side (Yang). If you recall- Luke (Yin) and Darth Vader (Yang) both always had one foot over the line that delineates the dark side from that of the light. Either character could have changed their sides but ultimately there must always be a balance in the Force.

Yin, Yang and Star Wars - What Does That Have to Do With Modern Healthcare?!

It’s about balance. Healthcare organizations are businesses. A business by its very nature needs to make a profit to continue its existence. Healthcare organizations just happen to be in the business of caring for people. It is a business that by all ethical principles should not be performing unnecessary procedures to stay out of the red and yet this is still done by some organizations.  

You may have heard that big data in healthcare is being used to cure diseases, improve quality of life, predict epidemics and so on. But how much of an impact is this having on society today?

The complexity of human health means that there is a lot of information that radiologists and disease specialists inherently best capture in the patient narrative and other clinical documentation. Up to 80% of patient information is made up of unstructured data. Naturally, many clinicians want to concentrate on their job: telling the story of the patient and how to treat them most effectively rather than spending 50% of their time entering structured information in check boxes and drop downs. Therefore, there's a desire to start using Natural Language Processing (NLP) systematically so that clinicians put more work into patient care and less into clinical documentation. Here at Linguamatics we help healthcare organizations look at how this mass of unstructured data can help identify high-risk patients and reduce the time spent on documentation.

An example of what healthcare providers are looking at the population level for individuals that we know have food insecurity or social isolation issues. These social determinants of health help identify if a patient isn’t eating properly or can't get to an appointment their likelihood of having a good outcome is severely reduced.

A valuable part of a clinician’s training includes the effective identification and careful documentation of all the elements impacting a patient's well-being. Thorough documentation is essential to ensure accurate and timely clinical care. Although electronic health records (EHRs) hold many great opportunities to capture essential details in electronic form, patients could be at risk if all elements of their medical records are not compiled and analyzed. With 990.8 million reported visits to physician offices in 2015 [1], odds are that precious information could slip off the radar of even the most dutiful clinical staff. 

The importance of Nature AND Nurture in healthcare

For this reason, providers must adopt a successful population management strategy that considers all elements of a patient’s record, including the estimated 70% of the record that exists as unstructured notes. Structured data is excellent for documenting patient information that ensures a hospital runs effectively but not as efficient for capturing imperative clinical concerns during a patient’s 20-minute encounter with a physician. 

Although the concept of nature vs. nurture has been well-documented for centuries, providers are just now realizing the critical importance of social determinants:

  • Does a patient live alone?
  • Do they utilize a walking cane?
  • Are they on a fixed-income? 

Identifying before protecting: Using I2E to help vulnerable populations

Undoubtedly, EHRs contain a wealth of information to identify patients requiring special attention, such as those with: