Enhance workflow and improve patient diagnosis with the Cozeva NLP

Natural Language Processing or NLP is the ability of computers to decipher human speech terms and texts. Health organizations have increasingly used NLP to enhance the efficiency of provider workflows and improve patient diagnosis.

In healthcare, NLP is pivotal for improving,

  • Interactions with providers

It deciphers complex medical terms, solves EHR challenges for nurses, and is used as an alternative to handwritten notes.

  • Health knowledge and awareness

It comprehends and displays complex medical information in a way that patients can understand to make informed health decisions.

  • Care quality

NLP tools offer efficient evaluation metrics to improve care quality.  Algorithms assist healthcare organizations in identifying errors in care delivery and mitigating them.

  • Critical care needs

NLP algorithms identify and extract vital information from large databases and provide doctors and medical staff with the right tools to treat patients having complex health problems.

Now let’s look at Cozeva’s NLP technology and try to understand what makes it so unique. 

What makes the Cozeva NLP unique?

Cozeva uses NLP technology that extracts clinical information from the Subjective, Objective, Assessment, and Plan (SOAP) notes and feeds the extracted information along with administrative data, supplemental data, and assessments into the platform’s Predictive Analytics tool.

 

Patients associated with an evidence-based care plan who are diagnosed with, or suspected of, combinations of chronic conditions are listed on each care opportunity report. These care plans indicate when patients are due for specific assessments, diagnoses, or treatments. When there is any indication, the metrics engine generates an alert for the team of healthcare professionals to address the needs of their patients.

 

It provides predictive analytics and dynamic population health management to provide “real-time” patient information that facilitates timely diagnosis. It implements more than 300 measure sets for diverse conditions.


The technology has a significant ability to decipher contextual information and unambiguous vocabulary. It helps reduce your administrative burden and coder intervention by increasing efficiency by 5x, saving time, and minimizing iteration.

 

It collects charts and allows Natural Language Processing (NLP) to do the hard work by-

 

  • Extracting from Free Text in C-CDAs– Apply Natural Language Processing (NLP) to
    any free text in C-CDA (Consolidated Clinical Document Architecture) documents to help close HCC gaps. Improve your accuracy over time by profiling the source of the C-CDAs.
  • Extracting from Scanned Charts– Apply deep learning techniques to extract text from scanned documents and highlight documents to quickly convert to structured data.
  • Increasing ROI– Reduce chart chases by retrieving charts automatically via Cozeva’s secure gateway and increase quality coding by listing specific codes and reducing the need for clinical chart review.

 

You can get detailed insight into abstraction results. Cozeva’s NLP reviews submission results override initial NLP findings, and lets you stay in control of accepting or rejecting your records.

 

The NLP not only looks for clinical documentation entered by the provider but also looks into open care gaps the member might have. It assesses single charts as well as a percentage of charts for quality measures and risk adjustments.

What are some other features of the NLP?

Cozeva’s NLP technology,

  • boasts over 98% accuracy in risk and 99% in quality
  • improves performance in both quality and risk registries
  • helps you launch new measures in weeks
  • enables seamless switching between NLP for quality and NLP for risk 
  • allows you to print out charts with highlights
  • is competitively priced.

Our NLP uses ICD 10-CM guidelines to promote accurate coding for causal conditions. It also shows providers “missed opportunities” where documentation is lacking to promote higher specificity and more complete documentation.

Additionally, NLP results can be used to build reports (of trending errors) for provider training to help correct documenting habits at the point of care.

 

The NLP technology is a daily solution and not a project-based solution. Cozeva is presently enhancing its NLP in EHR integration where NLP results can be obtained after signing an encounter note. NLP extracts free text in C-CDAs and from scanned charts. It powers your transformation into a value-based healthcare ecosystem which in turn increases your ROI.

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