Natural language word embeddings as a glimpse into healthcare language and associated mortality surrounding end of life.

ABSTRACT:

Objectives

To clarify real-world linguistic nuances around dying in hospital as well as inaccuracy in individual-level prognostication to support advance care planning and personalised discussions on limitation of life sustaining treatment (LST).

Design

Retrospective cross-sectional study of real-world clinical data.

Setting

Secondary care, urban and suburban teaching hospitals.

Participants

All inpatients in 12-month period from 1 October 2018 to 30 September 2019.

Methods

Using unsupervised natural language processing, word embedding in latent space was used to generate phrase clusters with most similar semantic embeddings to 'Ceiling of Treatment' and their prognostication value.

Results

Word embeddings with most similarity to 'Ceiling of Treat

SUBMITTER: Lau IS 

PROVIDER: S-EPMC8557276 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature