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


Journal

BMJ health & care informatics
ISSN: 2632-1009
Titre abrégé: BMJ Health Care Inform
Pays: England
ID NLM: 101745500

Informations de publication

Date de publication:
Oct 2021
Historique:
received: 05 08 2021
accepted: 08 10 2021
entrez: 29 10 2021
pubmed: 30 10 2021
medline: 9 11 2021
Statut: ppublish

Résumé

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). Retrospective cross-sectional study of real-world clinical data. Secondary care, urban and suburban teaching hospitals. All inpatients in 12-month period from 1 October 2018 to 30 September 2019. 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. Word embeddings with most similarity to 'Ceiling of Treatment' clustered around phrases describing end-of-life care, ceiling of care and LST discussions. The phrases have differing prognostic profile with the highest 7-day mortality in the phrases most explicitly referring to end of life-'Withdrawal of care' (56.7%), 'terminal care/end of life care' (57.5%) and 'un-survivable' (57.6%). Vocabulary used at end-of-life discussions are diverse and has a range of associations to 7-day mortality. This highlights the importance of correct application of terminology during LST and end-of-life discussions.

Identifiants

pubmed: 34711578
pii: bmjhci-2021-100464
doi: 10.1136/bmjhci-2021-100464
pmc: PMC8557276
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Alzheimer's Society
ID : 171
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_17214
Pays : United Kingdom

Informations de copyright

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: The authors have received research funding support from the Cicely Saunders Institute on Palliative Care, NIHR Applied Research Centre South London and the NIHR Maudsley Biomedical Research Centre.

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Auteurs

Ivan Shun Lau (IS)

Kings College Hospital, King's College Hospital NHS Foundation Trust, London, UK.

Zeljko Kraljevic (Z)

Department of Biostatistics and Health Informatics, King's College London, London, UK.

Mohammad Al-Agil (M)

Kings College Hospital, King's College Hospital NHS Foundation Trust, London, UK.

Shelley Charing (S)

Patients, (Private Individuals), London, UK.

Alan Quarterman (A)

Patients, (Private Individuals), London, UK.

Harold Parkes (H)

Patients, (Private Individuals), London, UK.

Victoria Metaxa (V)

Kings College Hospital, King's College Hospital NHS Foundation Trust, London, UK.
School of Medical Education, King's College London, London, UK.

Katherine Sleeman (K)

Department of Palliative Care, Policy and Rehabilitation, King's College London, London, UK.

Wei Gao (W)

Department of Palliative Care, Policy and Rehabilitation, King's College London, London, UK.

Richard J B Dobson (RJB)

Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

James T Teo (JT)

Kings College Hospital, King's College Hospital NHS Foundation Trust, London, UK jamesteo@nhs.net.
Institute of Psychiatry Psychology and Neuroscience, King's College London, London, UK.

Phil Hopkins (P)

Intensive Care Medicine, Anaesthesia and Trauma, King's College Hospital NHS Foundation Trust, London, UK.

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Classifications MeSH