Evidence map›Paper›PMID 40383724›Full record

ArticleScientific reports2025

Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer.

Hao Yuan Yang, Karthik Raghunathan, Eric Widera, Steven Z Pantilat, Teva Brender, Timothy A Heintz, Edie Espejo, John Boscardin, Hunter Mills, Albert Lee and 2 more

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Hao Yuan YangDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
Karthik RaghunathanDepartment of Anesthesia and Perioperative Care, Duke University, Durham, NC, USA.
Eric WideraDivision of Geriatrics, San Francisco VA Health Care System, San Francisco, CA, USA.
Steven Z PantilatDivision of Palliative Medicine, University of California San Francisco, San Francisco, CA, USA.
Teva BrenderDepartment of Internal Medicine, University of California San Francisco, San Francisco, CA, USA.
Timothy A HeintzDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Edie EspejoGeriatrics, Palliative, and Extended Care, Veterans Affairs Medical Center, San Francisco, CA, USA.
John BoscardinDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
Hunter MillsBakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA.
Albert LeeBakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA.
Jacob BerchuckDivision of Oncology, Winship Cancer Institute, Emory University, Atlanta, GA, USA.
Julien CobertAnesthesia Service, San Francisco VA Health Care System, 4150 Clement St Building 6, Office 206, San Francisco, CA, USA. Julien.cobert@ucsf.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Palliative care is known to improve quality of life in advanced cancer. Natural language processing offers insights to how documentation around palliative care in relation to metastatic cancer has changed. We analyzed inpatient clinical notes using unsupervised language models that learn how words related to metastatic cancer (e.g. "mets", "metastases") and palliative care (e.g. "palliative care", "pal care") appear relationally and change over time. We included any note from adults hospitalized at the University of California, San Francisco system. The primary outcome was how similarly terms related to metastatic cancer and palliative care appeared in notes using a mathematical approach (cosine similarity). We used word2vec to model language numerically as vectors. Relational data between vectors was captured using cosine similarity. We performed linear regression to identify changes in these relationships of terms over time. As a sensitivity analysis, we performed the same analysis per year restricted only to patients with an ICD-9/10 diagnosis code for metastatic cancer. Metastatic cancer and palliative care terms appeared in similar contexts in clinical notes each year, suggesting a close relationship in documentation. However, over time, this relationship weakened, with these terms becoming less commonly used together as measured by cosine similarities. We found similar trends when we retrained models just on patients with a diagnosis code for metastatic cancer. Text in clinical notes offers unique insights into how medical providers document palliative care in patients with advanced malignancies and how these documentation practices evolve over time.

Indexed as

DocumentationNatural Language ProcessingNeoplasmsPalliative CareElectronic Health RecordsFemaleHumansMaleNeoplasm MetastasisLinguisticsMachine learningNatural language processingPalliative care

Identifiers

PMID40383724
PMCPMC12086223

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