Linguamatics, the market-leader in natural language processing (NLP)-based text mining and analytics, today announced that Huntsman Cancer Institute (HCI) at the University of Utah has deployed its NLP based I2E software platform to transform the immense stores of unstructured text in electronic health records (EHRs) into actionable information to drive improvements in cancer research, treatments and outcomes.
HCI is using Linguamatics I2E with its in-house clinical informatics infrastructure to extract discrete data from the unstructured text contained in surgical, pathology, radiology, and clinical notes related to hematology disease areas such as Leukemia and Lymphoma.
The resulting data is loaded into an integrated biobanking, clinical research, and genomic annotation platform. This enables HCI’s clinicians and principle investigators to harness the richest possible set of data for research into patient outcomes, comparative effectiveness, and genetic drivers of disease.
Analysis at this scale can find information that would often be missed when reading documents one at a time.
In addition HCI has a better range and quality of data to support clinical trial matching and increase numbers of patients on trials.
“Healthcare organizations face a major challenge to identify, capture and leverage valuable knowledge buried within vast stores of complex, unstructured patient data, and to do it in a reproducible and scalable way”, commented Phil Hastings, Senior Vice President, Sales and Marketing, at Linguamatics.
“When abstracting detailed patient data, a clinical research assistant may look at multiple documents and spend several hours per patient to get all their radiology, pathology and surgical data curated. To perform this work at a meaningful scale is both laborious and expensive.”
“I2E is a uniquely agile and scalable NLP platform, which empowers organizations to successfully address the data abstraction challenge”, continued Dr Hastings.
“We are pleased to be working with Huntsman Cancer Institute in their drive to streamline and extend their healthcare analytics efforts and positively impact research processes and patient outcomes.”