Evidence map›Paper›PMID 41051932›Full record

ArticlePopulation health management2025

Evaluation of the Electronic Health Record-Support Social Support Score in Breast Cancer: Comparison of Count and Item Response Theory Scores.

Salene M W Jones, Rhonda-Lee F Aoki, Stacey E Alexeeff, David Carrell, David Cronkite, Lawrence H Kushi, David Mosen, Shaila Strayhorn, Leah Tuzzio, Jessica Mogk and 2 more

Abstract readComparative Study
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Salene M W JonesFred Hutchinson Cancer Center, Seattle, Washington, USA.ORCID 0000-0003-2140-5798
Rhonda-Lee F AokiKaiser Permanente Northern California, Pleasanton, California, USA.
Stacey E AlexeeffKaiser Permanente Northern California, Pleasanton, California, USA.
David CarrellKaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.
David CronkiteKaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.
Lawrence H KushiKaiser Permanente Northern California, Pleasanton, California, USA.
David MosenKaiser Permanente Northwest, Portland, Oregon, USA.
Shaila StrayhornUniversity of North Carolina Wilmington, Wilmington, North Carolina, USA.
Leah TuzzioKaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.
Jessica MogkKaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.
Lauren MamminiKaiser Permanente Northern California, Pleasanton, California, USA.
Candyce H KroenkeKaiser Permanente Northern California, Pleasanton, California, USA.

Funding

An Electronic Health Record-Based Tool to Identify Newly Diagnosed Breast Cancer Patients at Risk of Low Social SupportR01CA253028 · NCI · KAISER FOUNDATION RESEARCH INSTITUTE · PI KROENKE, CANDYCE H · 2020 to 2025
$2.6M
NCI NIH HHS R01 CA253028
6 · The paper itself

Abstract

In breast cancer, clinicians add data on social support to patient electronic health records (EHRs) often in free text notes, but those data may be challenging to use for population health initiatives or research purposes. We evaluated the EHR-Support score designed to summarize need for social support using data from the EHR. This study included 996 women from the Pathways study, a Kaiser Permanente Northern California cohort of women diagnosed in 2005-2013 with breast cancer. This unique data resource included both EHR data and questionnaire data on patient-reported social support. Using unstructured EHR data and natural language processing, we developed 11 concept groups (items) characterizing social support. We also used structured data to create two additional concept groups. EHR-Support scores reflecting the lack of social support were generated three ways: counting the number of negative concept groups (count score), using item response theory (IRT), and converting counts to the IRT metric (converted count scores). The count scores were only associated with two of six patient-reported measures (r's: -0.004 to -0.073). The IRT score (r's: -0.038 to -0.179) and converted count score (r's: -0.032 to -0.195) were associated with five of six patient-reported measures, indicating more need for support was associated with less patient-reported social support. The EHR-Support score is a valid and feasible measure of social support that can be used for health services research and managing population health. The converted count score may provide the best balance of validity, precision from IRT and feasibility.

Indexed as

Breast NeoplasmsElectronic Health RecordsSocial SupportAdultAgedCaliforniaFemaleHumansMiddle AgedSurveys and Questionnairescancerneoplasmsocial support

Identifiers

PMID41051932
PMCPMC12721345

What OpenQuestion holds

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Registered trials

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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.