Faced with the challenges of Accountable Care, the triple aim and Meaningful Use, NLP will help CMIOs to improve insights into patient and population health.

CAMBRIDGE, UK and BOSTON, USA - November 10th, 2015 – Chief Medical Informatics Officers (CMIOs) at US healthcare providers see that Accountable Care, the triple aim and Meaningful Use are all creating an unprecedented demand for more insights from patient data. Since much of the key information is locked away in unstructured data, the overwhelming majority of CMIOs believe that rapidly increasing the use of Natural Language Processing (NLP) will be a critical step in accessing this data and thus improving the delivery of patient care. These are the key findings of a recent study prepared by Linguamatics, with support from the American Medical Informatics Association (AMIA).

Linguamatics commissioned their “Assessing the Role of Clinical NLP in the Delivery of Patient Care” report, with the aim of discovering how CMIOs envisage using NLP in new applications that both enhance patient care and improve hospital efficiency. The report succeeded in uncovering four key areas where CMIOs foresee key developments:

• The CMIOs surveyed considered the potential improvement in the quality of care and patient safety, and the resulting reduction in costs that could be generated with predictive models, to be the most important application involving NLP. For example, CMIOs expressed interest in applications such as predicting hospital readmissions or outmigration/patient leakage.


I’m thrilled to see that Linguamatics I2E 4.3 is named as a KMWorld 2015 Trend-Setting Product.  Linguamatics I2E has a proven track record in delivering best of breed text mining capabilities across a broad range of application areas. Its agile nature allows tuning of query strategies to deliver the precision and recall needed for specific tasks, but at an enterprise scale.

According to customers, I2E gets to actionable results at least 10 times faster than a traditional keyword search. In many cases, I2E will produce successful results for projects that would otherwise be impossible or intractable.

Actionable information extracted using I2E can be presented in a variety of ways depending on your needs. NLP-based text mining provides the capability to look through unstructured text (typically in large sets of documents, from scientific reports, patents, or electronic healthcare records, pathology and radiology reports); and use sophisticated queries to automatically identify and extract out structured data (concepts and associations) to enable the system to interpret the meaning of the text. 

 


Linguamatics I2E natural language processing technology to automatically extract clinical attributes from pathology reports across eight hospital groups in Stratified Medicine Programme.

LONDON and CAMBRIDGE, UK, September 1st, 2015 – Cancer Research UK and Linguamatics announced today they will work on a joint project to apply Linguamatics’ natural language processing (NLP) text analytics platform, I2E, to automatically extract clinical attributes from cancer pathology reports and improve annotation of clinical samples relating to Cancer Research UK’s Stratified Medicine Programme (SMP). This project will allow the analysis of detailed patient characteristics alongside large volumes of genetic data, enabling more effective research into the causes and personalised treatment of cancer.

Dr Ian Walker, Director of Clinical Research and Strategic Partnerships at Cancer Research UK, said: “Pathology reports tell us a range of important information about a patient’s cancer, but the way this data is recorded can vary widely, which makes it harder to spot trends or other significant information that could have a bearing on treatment decisions or prognosis. This collaboration should help translate these reports into more meaningful data, which should help our researchers better understand the disease and accelerate advances in personalised medicine.”


On July 16, delegates across the life sciences, biotech, healthcare and other knowledge-driven industries gathered in Princeton for Linguamatics’ one-day seminar: “From bench to bedside, unlocking key insights in your data”.  

We heard from Regeneron Pharmaceuticals, Johnson & Johnson, Copyright Clearance Center (CCC) and Linguamatics on how NLP technology is moving into new application areas to improve patient outcomes and unlock key insights across the drug discovery, development and delivery continuum. Delegates were very engaged and many stayed long after the talks had finished, to continue the day’s discussions.  

Jim Dixon, Senior Application Specialist, gave us an introduction to I2E NLP text mining and the new features in the latest I2E release and industry’s first federated text mining platform. Whatever the content, I2E can mine and extract with precision and at scale. You can use Linguamatics I2E to provide valuable intelligence from text, getting you to the answers faster so you can make smarter and better informed decisions.

Dr. Peng Zhang’s presentation showed us a real-life use case of I2E’s potential at Regeneron. Eliminating or modifying a single gene in the mouse genome can provide insight into the role that gene plays in normal physiology and disease pathogenesis, but keeping up-to-date with novel information is time-consuming. Dr. Zhang uses I2E to systematically mine the scientific literature for any reported gene knockout in mice, and associated autoimmune phenotype.


Life sciences and healthcare professionals gathered at the UCSF Mission Bay campus for the West Coast Natural Language Processing (NLP) & Big Data Symposium on June 18th. The symposium, co-hosted by UCSF, featured presenters from UCSF, Merck, City of Hope, Copyright Clearance Center and Linguamatics and delegates from a diverse range of organizations.

The central theme of this year’s symposium was “From bench-to-bedside, unlocking key insights from your data”. Healthcare delegates were keen to find new ways to address meaningful use and accountable care leveraging NLP text mining of electronic health records. Life sciences delegates were keen to increase the efficiency and effectiveness of their business operations by mining real world data. There was also a strong interest in forging partnership opportunities between pharma/biotech and hospitals/cancer centers.

Sorena Nadaf, the CIO and Director of Translational Informatics at UCSF Helen Diller Family Comprehensive Cancer Center delivered the welcome address and highlighted the foundation of clinical NLP and its common uses for extracting and transforming narrative information in EMR’s to support and accelerate clinical research.

NLP & Big Data Symposium
Sorena Nadaf at the NLP & Big Data Symposium in San Francisco.