Structured Data Leads to Better Analysis, Outcomes
There's also a role for this kind of service in research. Many inclusion and exclusion criteria important to clinical trials are buried in physicians' notes. NLP could be used to identify these patients for use in study cohorts, Moore notes.
One other note: Although you might hear IBM describing NLP as an element of Watson, it is but one element of Watson. While Watson does employ NLP, it also contains a machine-learning element that helps Watson understand the entire ontology of a particular medical practice.
Over time, Watson "learns" more than it used to about a given practice, such as oncology. The NLP technology in use at UNCHC must be specifically programmed to seek and extract unstructured data into structured data, and as such, falls far short of Watson's ability to understand medicine.
Still, NLP is probably our best tool for mining unstructured data, and arrives none too soon given the explosion of electronically-stored medical data. And as Macko notes, "in the end, physicians are going to do what physicians do. They like to write things down, right?"
Scott Mace is senior technology editor at HealthLeaders Media.
- Transforming Decision Support and Reporting
- In Lakeport, CA, a Population Health Laboratory is Born
- Nurse Ethics Comes to a Head at Guantanamo Bay
- Providers Prep for New Payment Models as Population Health Grows
- CMS Mulls Income-Adjusting MA Stars
- Providers' Push to Consolidate Roils Payers
- Slideshow: Healthcare Executives Eye Efficiency
- As Retail Clinics Surge, Quality Metrics MIA
- 3 Ways to Rev Employee Development Programs
- Upfront costs of going digital overwhelm some doctors