Automated detection of sudden unexpected death in epilepsy risk factors in electronic medical records using natural language processing.

ABSTRACT:

Objective

Sudden unexpected death in epilepsy (SUDEP) is an important cause of mortality in epilepsy. However, there is a gap in how often providers counsel patients about SUDEP. One potential solution is to electronically prompt clinicians to provide counseling via automated detection of risk factors in electronic medical records (EMRs). We evaluated (1) the feasibility and generalizability of using regular expressions to identify risk factors in EMRs and (2) barriers to generalizability.

Methods

Data included physician notes for 3000 patients from one medical center (home) and 1000 from five additional centers (away). Through chart review, we identified three SUDEP risk factors: (1) generalized tonic-clonic seizures, (2) refractory epilepsy, and (3) epilepsy surgery candid

SUBMITTER: Barbour K 

PROVIDER: S-EPMC11771062 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature