Evidence map›Paper›PMID 37290826›Full record

ArticleJournal of the American Board of Family Medicine : JABFM2023

Supporting the Capture of Social Needs Through Natural Language Processing.

Lewis J Frey, Chanita Hughes Halbert, Christopher D Blasy

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Board of Family Medicine : JABFM, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Lewis J FreyFrom the Ralph H. Johnson Veterans Affairs Medical Center (VAMC), Charleston, SC (LJF, CDB); University of Southern California, Los Angeles, CA (CHH) lewis.frey@va.gov.
Chanita Hughes HalbertFrom the Ralph H. Johnson Veterans Affairs Medical Center (VAMC), Charleston, SC (LJF, CDB); University of Southern California, Los Angeles, CA (CHH).
Christopher D BlasyFrom the Ralph H. Johnson Veterans Affairs Medical Center (VAMC), Charleston, SC (LJF, CDB); University of Southern California, Los Angeles, CA (CHH).

Funding

Data-Driven Methods to Identify Social Determinants of HealthI01HX003379 · VA · RALPH H JOHNSON VA MEDICAL CENTER · PI FREY, LEWIS JAMES, GEBREGZIABHER, MULUGETA GEBRESELASSIE · 2021 to 2025
–
HSRD VA I01 HX003379
6 · The paper itself

Abstract

Social factors impact morbidity and mortality among patients. Documenting social needs in the clinical notes is currently widely done by family physicians. The unstructured format of information on social factors in electronic health records limits the ability of providers to address these issues. A proposed solution is using natural language processing to identify social needs from the electronic health record. This could support physicians in capturing structured social needs information that is consistent and reproducible without increasing documentation burden.

Indexed as

Electronic Health RecordsNatural Language ProcessingDocumentationHumansPhysicians, FamilyNatural Language ProcessingSocial Determinants of Health

Identifiers

PMID37290826
PMCPMC10484332

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.