Health Language Blog

Clinical NLP Part 4: Taking Predictive Analytics Strategies to the Next Level

Posted on 07/15/20 | Comments

Clinical Natural Language Processing for Predictive Analytics 

We hope you’ve found this cNLP blog series enlightening, so far, and have learned new areas where this advanced technology can improve the quality of data to better inform forward-thinking strategies. If you missed any of our previous segments, we hope you will take time to read how cNLP can improve risk adjustment, quality measures reporting and medical necessity review. In this fourth and final installment, we will explore the value proposition of cNLP within the framework of predictive analytics.

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Topics: Analytics, data quality, NLP, unstructured text, value-based care, cnlp, predictive analytics

Clinical NLP Part 3: Streamlining, Optimizing Medical Necessity Review

Posted on 06/17/20 | Comments

Clinical Natural Language Processing for Medical Necessity Review 

In our first installment of this four-part blog series, we explored how Clinical Natural Language Processing (cNLP) can impact risk adjustment.  In the second installment, we discussed how cNLP improves the outlook on quality measures reporting—and specifically how it can impact the bottom line. This third blog segment will uncover the challenges of medical necessity reviews and why the ability to extract data from free text is critical to improve the process.

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Topics: clinical documentation, Analytics, data quality, NLP, unstructured text, quality measure reporting, cnlp, medical necessity

Clinical NLP Part 2: A Better Equation for Calculating Quality Measures

Posted on 06/03/20 | Comments

Clinical Natural Language Processing

Aligned with the complex language of healthcare, Clinical Natural Language Processing (cNLP) enables healthcare organizations to unlock the value of their data. An important goal of cNLP is to provide structure to highly unstructured data sources. In this second installment of our four-part series on cNLP, we uncover the opportunities and challenges providers and payers face when extracting data from free text for quality measures reporting. If you missed our first blog related to risk adjustment, we invite you to read it here.

Whether a provider, payer, or patient, all benefit from clinical records that are thorough, accurate, understandable, and interoperable. Having quality data available is foundational for providing quality care to patients and ultimately improving outcomes.  However, the vast amount of data paired with the varied types of data available in electronic health records creates challenges when attempting to review information meaningfully, extract it from the records, and share it effectively.  

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Topics: clinical documentation, Analytics, quality reporting, CMS, data quality, NLP, unstructured text, quality measure reporting, cnlp, HEDIS, COVID-19

Clinical NLP Part 1: Spotlight on Risk Adjustment

Posted on 05/20/20 | Comments

Part 1:  Spotlight on Risk Adjustment 

Welcome to the first installment of a four-part blog series that explores the broad and growing value of using clinical natural language processing (cNLP) to deliver results for both payer and provider organizations.

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Topics: HCCs, NLP, unstructured text, chart review, cnlp, risk adjustment, predictive analytics

Clinical NLP: The Key to Unlock Your Data

Posted on 05/12/20 | Comments

We're kicking off a Clinical Natural Language Processing (cNLP) blog series! 

In these uncertain times, healthcare leaders are under pressure to do more with less. Whether faced with budget cuts or staff reductions, they are still on the line to provide superior patient care and improve health outcomes.  

To do this, stakeholders are looking to advanced technology to help augment existing workflows, optimize staff labor, and eliminate unnecessary manual efforts.

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Topics: NLP, unstructured text, quality measure reporting, cnlp, risk adjustment, predictive analytics, medical necessity review

Webinar Recap: Applying AI in Healthcare: Practical Applications of Clinical NLP to Drive Value in Your Organization

Posted on 03/11/20 | Comments

AI in Healthcare:  Practical Applications of Clinical NLP

While there’s been a lot of buzz about the promise of artificial intelligence (AI) in healthcare, health leaders are recognizing that AI holds the potential to diagnose and treat disease, improve processes, and better manage underlying operational, financial, and patient health data through which they can innovate and maximize value.

Specifically, within healthcare, Natural Language Processing (NLP), a specific branch of AI, has quickly proven value by enabling healthcare organizations the ability to efficiently leverage unstructured data, which represents nearly 80% of all healthcare data.

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Topics: NLP, Natural Language Processing, unstructured text, quality measure reporting, clinical natural language processing, cnlp, sepsis detection, risk adjustment

From Data to Intelligence: The Path to Improving Plans’ Performance

Posted on 01/08/20 | Comments

The Value of AI in Healthcare 

There’s been a lot of buzz about the promise of artificial intelligence (AI) in healthcare. We’re moving rapidly from hype to real-world use cases in which health leaders recognize that AI holds the potential to diagnose and treat disease, improve processes, and better manage underlying operational, financial, and patient health data through which they can innovate and maximize value. 

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Topics: Health Plans, NLP, unstructured text, quality measure reporting, clinical natural language processing, patient risk, cnlp, Medicare Advantage, HEDIS, Star Ratings, member health

NLP: Unlocking the potential of unstructured text in healthcare

Posted on 05/30/17 | Comments

Hospitals and health systems are sitting on a wealth of patient information that has potential to transform care delivery. Yet analytics infrastructures designed to fuel performance improvement have traditionally overlooked much of that data because it resides in health IT systems as unstructured free text.

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Topics: NLP, Natural Language Processing, unstructured text