Posts Tagged ‘electronic health records’

WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Interoperability

The Yosemite Project: An RDF Roadmap for Healthcare Information InteroperabilityDATE: Friday, October 17, 2014
TIME: 2 PM Eastern / 11 AM Pacific
PRICE: Free to all attendees

This webinar has passed. The recording (posted within two business days of the live event) can be found in the “Webinar” section of

About the Webinar

Register Now!Interoperability of electronic healthcare information remains an enormous challenge in spite of 100+ available healthcare information standards. This webinar explains the Yosemite Project, whose mission is to achieve semantic interoperability of all structured healthcare information through RDF as a common semantic foundation. It explains the rationale and technical strategy of the Yosemite Project, and describes how RDF and related standards address a two-pronged strategy for semantic interoperability: facilitating collaborative standards convergence whenever possible, and crowd-sourced data translations when necessary.

We hope you will join us on October 17, 2014 for this free webinar.

Register today to reserve your spot!


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A Closer Look At SemTechBiz Startup Competition Winner: KnowMED And Its Clinical Discovery Platform

KnowMED walked away the big winner of the Semantic Start-Up Competition. The Semantic Web Blog caught up with CTO Matthew Vagnoni, MS, and CEO Jerry D. Scott to further discuss the company’s winning entry, the Clinical Discovery Platform, for helping the health care sector semantically integrate data and ask natural language questions of that data, to support clinical research and complex decision-making.

The problem that the health care industry at large faces of not being able to easily and efficiently integrate and share data across organizations’ borders is equally a challenge right within the institutions themselves. “Large modern health care organizations are somewhat insular,” says Vagnoni.

At Medical City Children’s Hospital in Dallas, as an example, there are three separate electronic health record systems just for its neonatal division. The diverse formats and vocabularies made it difficult to try to ask questions of this data for research or efficiency purposes. But within two months of deploying KnowMED’s Clinical Discovery Platform, Vagnoni says, most of the data was integrated into a single view, “so clinicians could interact with it almost like using Google. …We combined the data from all the different sources so that clinicians could go in and ask questions [that reflect] how they think, not how [the information] is in the data schema.”

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Solving the NLP Challenge in Health Care

The health care industry is built on an awful lot of manual infrastructure, and the strain can grow even more with the adoption of standards such as the tenth revision of the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems (ICD). In the U.S., the adoption deadline of ICD-10, which codes for diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases, is set for October of 2014.

“The way the country is trying to address quality improvement in health care is requiring more information to be captured electronically in a system so it can be processed and used to improve care,” explains Dr. Daniel Riskin, MD, MBA, FACS, and CEO and co-founder of Health Fidelity. Earlier this year the company released the REVEAL cloud-based service for healthcare IT application companies and their healthcare organization customers. “The first step is for doctors to use electronic health records. The next is to drive increasing capture of useable information,” Riskin concludes.

Typing medical narratives is just text – it’s not useable information. Making it useable for standards such as ICD-10 – which is some five times as detailed as ICD-9 – can lead to situations where doctors and nurses have to do twice as much work tagging items within narratives, and where coding departments can grow to be twice as big. The aim to improve health care via such efforts is sound, but so too is relying more on technology and less on manual labor to get value out of the unstructured data.

The clinical NLP (natural language processing) technology in Health Fidelity’s REVEAL platform steps into the picture here, transforming huge volumes of unstructured clinical data (Big Data if ever there was any) into information that healthcare IT application vendors and their hospital customers can then make use of to improve care quality, safety and efficiency.

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