Use of Natural Language Processing Tools to Identify and Classify Periprosthetic Femur Fractures.

ABSTRACT:

Background

Manual chart review is labor-intensive and requires specialized knowledge possessed by highly trained medical professionals. The cost and infrastructure challenges required to implement this is prohibitive for most hospitals. Natural language processing (NLP) tools are distinctive in their ability to extract critical information from unstructured text in the electronic health records. As a simple proof-of-concept for the potential application of NLP technology in total hip arthroplasty (THA), we examined its ability to identify periprosthetic femur fractures (PPFFx) followed by more complex Vancouver classification.

Methods

PPFFx were identified among all THAs performed at a single academic institution between 1998 and 2016. A randomly selected training cohort (15

SUBMITTER: Tibbo ME 

PROVIDER: S-EPMC6760992 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature