Showing posts with label NLP. Show all posts
Showing posts with label NLP. Show all posts

Friday, December 14, 2012

Clinical Language Understanding from Nuance

source: http://www.nuance.com/for-healthcare/resources/clinical-language-understanding/index.htm

Clinical Language Understanding

There is a growing demand to extract structured, "actionable" information from unstructured (dictated) medical documents.

Clinical Language Understanding leverages advancements in Natural Language Processing (NLP), medical Artificial Intelligence (AI) and speech recognition technology to create tailored solutions for healthcare informatics.
Clinical Language Understanding technology can be used to derive patient information from free text and to produce actionable data used to improve patient care and streamline workflow.

  • Addresses physicians’ concerns for efficiency
  • Preserves the patient’s unique clinical story
  • Enables physicians to document their clinical decision making processes
  • Integrates into physician and enterprise workflows, enhancing acceptance
  • Supports organizational needs for structured data
  • Streamlines Electronic Health Record (EHR) population from the narrative by automatically extracting clinical facts from dictation
  • Helps accelerate EHR adoption so providers can realize the value of their HIT investments
  • Supports compliance with EHR certification criteria
The use of Clinical Language Understanding offers physicians the best of both worlds. It supports the comprehensive documentation of care through narrative dictation, capturing the uniqueness of each patient encounter and documenting the clinical decision-making process without the limitations of rigid documentation "templates". However, unlike "blobs" of free-text, key patient data is identified and automatically saved as structured data in the EHR's database, where information can be analyzed, reported and used for better patient care.
Clinical Language Understanding technology allows a computer to read and understand electronic free text and extract data for use in countless applications across the healthcare spectrum. 360 | Clinical Understanding Services software analyzes free text dictation, tagging the most important clinical data elements such as problems, social history, medications, allergies, and procedures. The tagged elements can then be used to populate electronic medical records, enabling applications that range from retrospective analysis across large amounts of medical records to medical decision support at the point of care.
By integrating one of the most comprehensive medical ontologies and state-of-the-art language processing algorithms, Clinical Language Understanding technology can achieve the highest level of conceptual understanding of clinical narrative and bridge the gap with structured data entry to support advanced healthcare applications.
Nuance Healthcare is the right partner to help physicians and organizations transition to structured data creation, while enhancing the quality of clinical documentation, adoption and utilization of the EHR. Nuance Healthcare leverages its considerable speech and 360 | Clinical Understanding Services technology assets—the industry’s largest portfolio, extensive knowledge and experience, and integration of cutting-edge communication and mobile devices - to create the right solutions for each physician. Moreover, Nuance Healthcare’s partnerships with all the major EHR vendors ensures clinicians direct access to their choice of clinical documentation workflow while data flows seamlessly into the EHR.

Clinical Language Understanding from NLP News

source: http://nlp.hivefire.com/topic/profile/clinical-language-understanding/

Natural Language Processing (NLP) News



Clinical Language Understanding

1-13 of 13 

  1. Mentioned In 13 Articles

  2. Nuance Communications Inc. : Leaders in Healthcare Partner with Nuance for Enterprise-Wide Clinical Speech Recognition Solutions


    ...0,000 healthcare providers across more than 10,000 institutions, Nuance's healthcare portfolio of voice and clinical language understanding (CLU) solutions continues to be recognized as industry standard for the high-q...
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  3. 1-13 of 13 



Clinical Language Understanding: the Future of Electronic Medical Record Software

source: http://www.meaningfulusenetwork.com/clinical-language-understanding-the-future-of-electronic-medical-record-software/


Clinical Language Understanding: the Future of Electronic Medical Record Software

As EMR vendors aim to entice doctors with more functional electronic medical record features, voice recognition technology has gained tremendous importance. Though voice recognition programs generally identify human speech and transform it into free text, their shortfall in the EMR world has been their inability to translate free text to fit into many systems’ check box and drop down menu components.
With natural language processing (NLP), however, relevant information is extracted from narrative text and populated into corresponding fields. NLP, when applied to the medical domain, is referred to as clinical language understanding (CLU). The CLU engine, for example is able to identify that “cancer” is a “disease” and can relay this to the natural language processor.
Using these technologies, EMR vendors like Nuance are developing platforms to help doctors chart more accurately and efficiently. The Dragon medical 360/M.D. Assist software uses CLU to detect missing details and unclear associations between findings, and it can also prompt doctors to identify more specific diagnoses (i.e. chronic versus acute). The MModal tool, meanwhile, can alert clinicians, while dictating, if they are overlooking any vital information that’s already in the patient’s chart. This can include labs or other tests in the patient’s electronic medical record that may be relevant to what the clinician is currently charting. Similarly, ChartLogic uses dictation and NLP capabilities in a product it calls Stella (similar to Apple’s Siri), which is compatible with many leading EMR software.
Electronic medical records in general are headed in the direction of technologies, like CLU, that have the ability to help providers increase input speed and improve workflow. Over time, we are likely to see a growing trend in more advanced voice recognition functions being incorporated into EMR software, which will benefit both physicians and patients alike.

Nuance Tech: Voice Recognition and Clinical Language Understanding

source: http://www.medgadget.com/2012/12/nuance-tech-voice-recognition-and-clinical-language-understanding.html



Nuance Tech: Voice Recognition and Clinical Language Understanding

by  on  • 8:54 am


While at RSNA, we got a chance to check out the latest voice recognition technology from Nuance. These are the guys that make Dragon NaturallySpeaking software, and also power many of the automatic call centers that help direct people and provide information based on natural language processing.  Nuance offers voice recognition and clinical language understanding (CLU) technology that can be embedded into just about any computer software or smartphone/tablet app. The company has released a short video demonstrating the capabilities of its 360 | Development Platform that allows integration of its technology into 3rd party tools:


Thursday, December 6, 2012

Natural Language Processing Takes Center Stage In EHRs



Natural Language Processing Takes Center Stage In EHRs

NLP tied to speech recognition software can help physicians enter structured data into computers more easily.
12 EHR Vendors That Stand Out
12 EHR Vendors That Stand Out
(click image for larger view and for slideshow)
Physicians have always resisted using point-and-click templates to document patient visits in electronic health records. Instead, many prefer speech recognition programs to transcribe their dictation in EHRs. But, in order to show Meaningful Use, they must enter a certain amount of structured data. Some EHR vendors are trying to make it easier for them to do that by imbedding natural language processing (NLP) software into their products.
At least three leading vendors—Allscripts, eClinicalWorks, and Greenway—have taken the first steps in this direction. All of these companies are applying voice recognition coupled with NLP to their ambulatory-care EHRs, and Allscripts is doing the same with its Sunrise acute-care products, including Sunrise Mobile MD II.

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Allscripts is working withM*Modal, a Medquist subsidiary that has a cloud-based voice recognition application. (Allscripts also offers its customers Dragon, the speech recognition program of Nuance Communications.) The company has already integrated M*Modal's NLP software into its Sunrise EHR, and the two companies are developing the application on the ambulatory care side.
[Is it time to re-engineer your Clinical Decision Support system? See 10 Innovative Clinical Decision Support Programs.]
Vern Davenport, chairman and CEO of M*Modal, toldInformationWeek Healthcare that his company's product can convert voice to text and do "context enablement" to create discrete data elements that go into EHR templates. The application can put problems, procedures, and medications into the correct fields, he said.
Because M*Modal is cloud-based, its use is not limited to specific computer devices, and the application can learn from all of the physicians who use it, Davenport noted.
Bill Fera, MD, executive director of healthcare advisory services for Ernst & Young, believes that this characteristic will help M*Modal continue to improve its application. Overall, he said, applications that extract coded data from free text have gotten significantly better, compared with a few years ago.
EClinicalWorks (ECW) is coming out with a native iPad version of its EHR next summer; at the same time, it will release a new EHR feature called Scribe that uses natural language processing to help doctors codify their documentation. (Because of the limitations of iPad keyboards, NLP will be needed to aid this process.) ECW is using Nuance's Dragon product to extract the data from transcribed dictation.
In a demonstration of Scribe at the recent Health Information and Management Systems Society (HIMSS) conference, an ECW representative spoke into a microphone and had Dragon place the transcribed dictation into categories such as "chief complaint" and "family history." After finishing his dictation, he pressed an "extract data" button, and the codified version of the data popped up on the left side of the computer screen.
“Workflow is incredibly important in utilizing an EHR,” Girish Kumar Navani, CEO of eClinicalWorks, toldInformationWeek Healthcare. “eClinicalWorks is simplifying technology by taking dictation as well as free text and transforming it into structured data. This will further streamline the use of EHRs in physician practices.” Jim Ingram, MD, chief medical officer of Greenway, agrees. "I really see the use of natural language processing as an enabler," he said in an interview with InformationWeek Healthcare. "It's providing the physicians who are later adopters of EHR technology with an easier way to move into this world and get the benefits of using an EHR."
About a year ago, he said, Greenway integrated NLP into its EHR, using M*Modal's engine, and it has been introducing this PrimeSPEECH product to customers for six months. Up to now, the application has been used to extract coded data for billing purposes, enhancing decision support, and pulling information into medical histories. In the future, he said, Greenway will add functionality for quality reporting and order tracking, among other things.
Greenway is also using the application in reverse, extracting elements of a Continuity-of-Care Document (CCD), such as medications, problems, and allergies, and merging those with the coded portions of transcribed dictation in the narrative version of the note.
Ernst & Young's Fera believes that the addition of NLP will reinforce the argument for using voice recognition in EHRs. "The main point is we're moving beyond speech recognition to natural language processing or understanding. With earlier iterations of speech recognition, the dictation generated a 'blob file' with no coded elements. So one argument against using that software was that the dictation couldn't populate your EHR fields. But now, with the continued evolution of language processing, not only can you document easily but it's getting into a formatted text."
Healthcare providers must collect all sorts of performance data to meet emerging standards. The new Pay For Performance issue of InformationWeek Healthcare delves into the huge task ahead. Also in this issue: Why personal health records have flopped. (Free registration required.)



source :http://www.informationweek.com/healthcare/electronic-medical-records/natural-language-processing-takes-center/232601951#