NLP is a form of artificial intelligence that enables computer programs to process and analyze unstructured data, such as free-text physician notes written in an EHR. Today, NLP technology is largely used as the basis for speech recognition in clinical documentation and automated coding in claims submissions.
In the report, Chilmark Research outlined 12 potential use cases for NLP in the healthcare industry, which it further divided into three maturity categories:
1. Mainstay NLP healthcare use cases, or those with a proven return on investment:
- Speech recognition
- Clinical documentation improvement
- Data mining research
- Computer-assisted coding
- Automated registry reporting
2. Emerging NLP healthcare use cases, or those that will likely have immediate impact:
- Clinical trial matching
- Prior authorization
- Clinical decision support
- Risk adjustment and hierarchical condition categories
3. Next-generation NLP healthcare use cases, or those that are on the horizon:
- Ambient virtual scribe
- Computational phenotyping and biomarker discovery
- Population surveillance
To access Chilmark Research’s report, click here.
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