Detecting goals of care conversations in clinical notes with active learning.

ABSTRACT:

Objective

Goals of care (GOC) discussions are an increasingly used quality metric in serious illness care and research. Wide variation in documentation practices within the Electronic Health Record (EHR) presents challenges for reliable measurement of GOC discussions. Novel natural language processing approaches are needed to capture GOC discussions documented in real-world samples of seriously ill hospitalized patients' EHR notes, a corpus with a very low event prevalence.

Methods

To automatically detect sentences documenting GOC discussions outside of dedicated GOC note types, we proposed an ensemble of classifiers aggregating the predictions of rule-based, feature-based, and three transformers-based classifiers. We trained our classifier on 600 manually annotated EHR note

SUBMITTER: Weissenbacher D 

PROVIDER: S-EPMC11177878 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature