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Healthcare Data Analytics

NLP On Demand

Need quality data fast? Do away with the manual.

View our webinar exploring how NLP-based AI addresses data challenges in healthcare

Learn how NLP On Demand can solve your complex data extraction and research needs

Request a free trial to see if NLP On Demand works for you – 100% risk free!

NLP-based AI for automated mining of clinical documents and reports

Manually extracting clinical data from unstructured text is inefficient.  And yet, clinical staff often dedicate up to 30% of their working day repeating just this kind of exercise, and report low levels of satisfaction accordingly.  

9 in 10

health data analysts report more manual than automated extraction

A Quarter

of health institutions are starting to utilize NLP to automate their processes

Inspirata’s NLP On Demand surfaces key information difficult to extract at scale within healthcare documentation in mere minutes. The results can be immediately applied to improve patient outcomes, optimize costs, and deliver a better quality of care.

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Introducing NLP On Demand

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NLP On Demand provides a comprehensive, fast, and automated approach to solving key issues with data in medical reports:

  • De-identification
  • Greater Consistency
    • 99% Accuracy in Cancer Case Finding
    • 100% Reproducibility & Consistency
  • Better Workflow Efficiency
    • No tedious, manual labor associated with extracting clinical data
  • Improved Medical Insight
    • Data-driven insights for research, quality improvement, and clinical decision support

Offered as Software-as-a-Service (SaaS), NLP On Demand can be deployed to address the following use cases:

  • Document profiling and classification
  • Tumor or disease profiling and characterization
  • Automation of diseases registry reporting
  • Completeness and accuracy of clinical documentation
  • Clinical concept extraction and mining
  • Computer-assisted medical record coding
  • Population health studies/disease statistics
  • Problem list extraction and risk stratification
  • Computing service quality

The Current State of Automated Data Extraction

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Benefits of NLP On Demand

Healthcare Data Analytics NLP On Demand

Healthcare Data Teams

  • Execute faster and with greater confidence with more timely, accurate, and complete datasets
  • Leverage difficult to surface or entirely untapped data sources to enhance your clinical research or business intelligence
  • Scale your clinical research and business analytics teams
  • Leverage our database of thousands of clinical concepts such as genomic biomarkers, symptoms, side effects, and medications
  • Identify disease characteristics, medications, or risk factors from clinical documents to stratify patients and improve the quality of care
  • Protect the identity of data subjects while maintaining data utility through document de-identification
  • Improve your understanding of data quality to spotlight areas of required improvement

NLP On Demand in Action

COVID-19 Open Research Dataset


Scholarly Articles


Full-Text Documents


Our team, in conjunction with HDR UK, applied Inspirata’s NLP engine to the COVID-19 Open Research Dataset (CORD-19) to help researchers around the globe find answers to important questions about the virus.

Webinar: Improving Health Data Quality

Inspirata and Health Data Research UK draw on their recent collaboration evaluating the quality of datasets published on the HDR UK Innovation Gateway. The presenters debate methods for overcoming the numerous challenges associated with assessing the quality of health data. 

Why Inspirata?

  • Industry-proven, scalable AI and NLP Engine in use at 100+ institutions globally.
  • Recognizes thousands of clinical concepts, including medication, anatomic parts, symptoms, side effects, and genomic biomarkers
  • Accessible as a cloud-based service or embedded within custom applications and analytic pipelines via API
  • Partnered with hospitals and healthcare collaborative networks worldwide to assess, improve, and extract value from clinical data

Request a Demo