Journal Article

Social Determinants and Military Veterans’ Suicide Ideation and Attempt: a Cross-sectional Analysis of Electronic Health Record Data

Dichter, Melissa E, Bossarte, Robert M, Taylor, Laura, Blosnich, John R, Dio, Kavalieratos, Montgomery, Ann Elizabeth, Gordon, Adam J, Ketterer, Bryan

2020

Overview

BackgroundHealth care systems struggle to identify risk factors for suicide. Adverse social determinants of health (SDH) are strong predictors of suicide risk, but most electronic health records (EHR) do not include SDH data.ObjectiveTo determine the prevalence of SDH documentation in the EHR and how SDH are associated with suicide ideation and attempt.DesignThis cross-sectional analysis included EHR data spanning October 1, 2015–September 30, 2016, from the Veterans Integrated Service Network Region 4.ParticipantsThe study included all patients with at least one inpatient or outpatient visit (n = 293,872).Main MeasurementsAdverse SDH, operationalized using Veterans Health Administration (VHA) coding for services and International Statistical Classification of Diseases and Related Health Problems (ICD)-10 codes, encompassed seven types (violence, housing instability, financial/employment problems, legal problems, familial/social problems, lack of access to care/transportation, and nonspecific psychosocial needs). We defined suicide morbidity by ICD-10 codes and data from the VHA’s Suicide Prevention Applications Network. Logistic regression assessed associations of SDH with suicide morbidity, adjusting for socio-demographics and mental health diagnoses (e.g., major depression). Statistical significance was assessed with p < .01.Key ResultsOverall, 16.4% of patients had at least one adverse SDH indicator. Adverse SDH exhibited dose-response-like associations with suicidal ideation and suicide attempt: each additional adverse SDH increased odds of suicidal ideation by 67% (AOR = 1.67, 99%CI = 1.60–1.75; p < .01) and suicide attempt by 49% (AOR = 1.49, 99%CI = 1.33–1.68; p < .01). Independently, each adverse SDH had strong effect sizes, ranging from 1.86 (99%CI = 1.58–2.19; p < .01) for legal issues to 3.10 (99%CI = 2.74–3.50; p < .01) for non-specific psychosocial needs in models assessing suicidal ideation and from 1.58 (99%CI = 1.10–2.27; p < .01) for employment/financial problems to 2.90 (99%CI = 2.30–4.16; p < .01) for violence in models assessing suicide attempt.ConclusionsSDH were strongly associated with suicidal ideation and suicide attempt even after adjusting for mental health diagnoses. Integration of SDH data in EHR could improve suicide prevention.

• Publisher: Springer Nature B.V
• Subject: Aggression / Cross-sectional studies / Demography / Electronic health records / Electronic medical records / Health problems / Health risks / Housing / Internal medicine / Legal issues / Mental health / Military personnel / Military psychology / Morbidity / Regression analysis / Risk analysis / Risk factors / Social conditions / Social problems / Statistical analysis / Statistics / Suicidal ideation / Suicide / Suicide prevention / Suicides & suicide attempts / Violence