Healthcare Language Processing, Language Interpretation, Digital Transcription, and Language Processing Solution Resources Healthcare Language Processing, Language Interpretation, Digital Transcription, and Language Processing Solution Resources


  • A Road Map To Accelerating Health IT Value And Innovation

    Health IT is in a state of constant evolution, and it often seems that, for every problem solved, another is created. That’s why it’s vital we stop to assess where the industry stands from time to time, as well as look to the future to determine the best course to take to achieve our collective goals.

  • $4.3 Billion Invested In Digital HIT In 2015

    While the number of venture capital-funded deals dropped, the average amount rose. By Christine Kern, contributing writer

  • Top 10 Health IT Trends For 2016

    For the past five years, EHR/MU was selected as the top health IT initiative for the coming year. This year, there’s a new top initiative, and what it is should come as no surprise.


  • Samsung Cloud Displays Unlock Efficiencies For Physicians And Accelerate EHR Adoption

    Regulatory requirements and government incentives to improve healthcare quality and efficiency through information technology have prompted healthcare providers to focus on achieving faster EHR adoption by implementing a virtual environment. However, for programs to be successful, the virtual solutions need to help make the work of physicians easier and more productive, while maintaining the reliability and security of patient data.

  • Getting Right With The Joint Commission: Improve Patient Safety By Ramping Up Emergency Communications

    This white paper from Amcom Software provides information about the Join Commission standards in regard to communications technology. It provides a case for improved communications, strategies for crisis communications plans, an emergency preparedness checklist, and technology solutions for automated event notification and response.

  • Leveraging Big Data And Analytics In Healthcare

    With the cost of mapping an individual human genome poised to break the $1,000 barrier – bringing personalized medicine closer to reality – the healthcare and life sciences industries are now grappling with managing the explosive growth of data.

  • Swedish Reduces Transcription Costs, Achieves 100% Adoption Of EMR

    This case study from Nuance takes a look at Swedish, the largest nonprofit healthcare provider in the greater Seattle Area. Swedish operates five hospital campuses, two ambulatory care centers with ERs, and a network of more than 100 specialty-care and primary care clinics.


  • The Problem With Consumerism In Healthcare

    Many industry leaders championed a free market approach to healthcare during the 12th Annual World Health Care Congress last week. Here are a few key reasons why I don’t think this model is “the fix” our industry so desperately needs.


Natural Language Processing (NLP) in healthcare is the processing of text with computer applications. NLP promises to reduce costs and improve quality for healthcare providers. With NLP, medical coding, records transcription, and clinical documentation processes can be significantly improved by limiting the number of employees required to perform these tasks and reducing the time it would normally require to input data manually.

NLP is designed to turn unstructured free text into structured values. NLP will ideally be able to assist physicians at the point of care, by offering them answers to questions based on the current set of records and information the system has available. IBM's Watson was one of the first largely-public displays of NLP when it appeared on Jeopardy, showing the world the potential of natural language processing by computers.

The advanced ICD-10 coding system has helped make a stronger case for NLP. The system's complexity in terms of the large range of codes available for each digit is something that could be completed programmatically. With NLP, computers will interpret notes and diagnoses from physicians and provide the proper codes. Similarly, another application of NLP is in EHR systems, where doctor's free-text notes can be taken, processed, and filled into the structured forms required by EHR systems.