Evidence map›Paper›PMID 41779393›Full record

ArticleJAMA network open2026

Clinical Note-Extracted Psychosocial Factors for Predicting Suicide Attempt Among ED Patients With Suicidal Ideation.

Hyunjoon Lee, Ketan Jadhav, Michael Ripperger, Peyton L Coleman, Theodore J Morley, Samuel A Palmer, Lide Han, Qingxia Chen, Cosmin A Bejan, Douglas M Ruderfer and 1 more

Abstract read
In one paragraph

Article in JAMA network open, 2026. 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

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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

11 authors.

Hyunjoon LeeDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Ketan JadhavDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Michael RippergerDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Peyton L ColemanCenter for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Theodore J MorleyCenter for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Samuel A PalmerCenter for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Lide HanCenter for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Qingxia ChenDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Cosmin A BejanDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Douglas M RuderferDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Colin G WalshDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The Joint Commission recommends universal suicide screening in emergency departments (EDs), which emphasizes the need to identify at-risk individuals. Existing suicide risk prediction models rely primarily on clinical data and demonstrate limited performance. The potential of incorporating psychosocial information to enhance predictive performance remains understudied. Objective: To evaluate whether augmenting clinical data-based risk scores with psychosocial factors improves the prediction of suicide attempt (SA). Design, Setting, and Participants: This retrospective prognostic study based on electronic health record data included 4661 ED patients discharged after presentation for suicidal ideation (SI) from middle Tennessee hospitals between June 1, 2018, and February 27, 2024. Main Outcomes and Measures: The primary outcome was SA within 90 days of ED admission and time-to-event in days. Clinical data-based Vanderbilt Suicide Attempt and Ideation Likelihood (VSAIL) score and 6 psychosocial factors (homelessness, financial insecurity, chronic stress, social isolation, loneliness, and adverse childhood experiences) derived from clinical notes were integrated using a Cox proportional hazards regression model. Performance metrics included area under the receiver operating curve (AUROC), area under the precision-recall curve (AUPRC), positive predictive value (PPV), negative predictive value, sensitivity, and specificity. Performance was evaluated for models trained on (1) VSAIL, (2) psychosocial factors, and (3) VSAIL plus psychosocial factors. Results: This study included 3382 Vanderbilt University Hospital (VUH) (mean [SD] age, 26.1 [15.6] years; 1751 males [51.8%]) and 1279 Regional Health Systems (RHS) (mean [SD] age, 34.5 [18.0] years; 715 males [55.9%]) ED visits for SI. Within 90 days, SAs were reported in 160 (4.7%) VUH and 34 (2.7%) RHS ED visits for SI. Compared with VSAIL alone, VSAIL plus psychosocial factors was associated with significantly increased median AUROC (VUH: 0.645 [IQR, 0.645-0.645] vs 0.734 [IQR, 0.719-0.747]; P < .001; RHS: 0.547 [IQR, 0.547-0.547] vs 0.680 [IQR, 0.672-0.687]; P < .001), AUPRC (VUH: 0.083 [IQR, 0.083-0.083] vs 0.122 [IQR, 0.111-0.137]; P < .001; RHS: 0.029 [IQR, 0.029-0.029] vs 0.054 [IQR, 0.052-0.058]; P < .001), and PPV (VUH: 0.093 [IQR, 0.082-0.094] vs 0.143 [IQR, 0.123-0.161]; P < .001; RHS: 0.042 [IQR, 0.040-0.043] vs 0.112 [IQR, 0.096-0.129]; P < .001) while maintaining specificities above 0.90. Chronic stress emerged as the strongest predictor of SA (β = 0.643 [95% CI, 0.427-0.859]; P < .001). Conclusions and Relevance: In this prognostic study of patients discharged from the ED after presentation for SI, augmenting a clinical data-based suicide risk prediction model with clinical note-extracted psychosocial factors was associated with significantly higher predictive performance. These findings suggest that psychosocial factors can enhance risk stratification and support targeted interventions, such as therapies addressing chronic stress.

Indexed as

Emergency Service, HospitalSuicidal IdeationSuicide, AttemptedAdultEmergency Room VisitsFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentRisk FactorsTennessee

Identifiers

PMID41779393
PMCPMC12961534

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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.