HealthMay 12, 2020

Clinical NLP: The key to unlock your data

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.

Specifically, AI-powered technology such as, natural language processing (NLP) and machine learning (ML), are being applied to address one of healthcare’s most tedious processes – reviewing patient medical records.

Currently, payer and provider organizations dedicate highly skilled, and highly paid professionals to manually comb through patient medical records (often hundreds of pages) in order to identify key pieces of information that can be used in a variety of high-value use cases that directly influence patient care and reimbursement.

To improve this process, health leaders can leverage clinically trained NLP technology to optimize the manual medical record review process. Clinical Natural Language Processing (cNLP) automates the review process of unstructured data within the medical record, extracts the clinically relevant data, and codifies the extracted data to industry standard terminologies.

No matter the use case, the value cNLP brings is clear; automation of labor-intensive processes, optimization of existing workflows, increasing staff efficiency, reducing manual labor and costs associated with administrative review, and increasing the accuracy of data used to inform initiatives that impact reimbursement and influence patient care.

Over the next few months, subject matter experts from the Health Language Content Team will dig into four, distinct high-value use cases where cNLP can be leveraged to provide significant value within: 1) Risk Adjustment, 2) Quality Measure Reporting, 3) Medical Necessity Review, and 4) Predictive Analytics. Be sure to catch all four blogs to learn about each of these valuable cNLP applications.  In the meantime, speak to an expert to learn more about the Health Language cNLP Solution.

Ali Gilinger
Sr. Product Marketing Manager, Health Language
As a Senior Product Marketing Manager, Ali supports the company’s Health Language solutions by building go-to-market strategies and marketing launch and support plans for the entire solutions portfolio.
Solutions
Health Language Clinical Natural Language Processing
Automate the review of unstructured data, extract clinically relevant data, and codify extracted data to industry standards.