Correlates of Suicide Among Veterans Treated in Primary Care: Case–Control Study of a Nationally Representative Sample

Abstract

BACKGROUND: Veterans receiving Veterans Affairs (VA) healthcare have increased suicide risk compared to the general population. Many patients see primary care clinicians prior to suicide. Yet little is known about the correlates of suicide among patients who receive primary care treatment prior to death. OBJECTIVE: Our aim was to describe characteristics of veterans who received VA primary care in the 6 months prior to suicide; and to compare these to characteristics of control patients who also received VA primary care. DESIGN: This was a retrospective case-control study. SUBJECTS: The investigators partnered with VA operations leaders to obtain death certificate data from 11 states for veterans who died by suicide in 2009. Cases were matched 1:2 to controls based on age, sex, and clinician. MAIN MEASURES: Demographic, diagnosis, and utilization data were obtained from VA's Corporate Data Warehouse. Additional clinical and psychosocial context data were collected using manual medical record review. Multivariate conditional logistic regression was used to examine associations between potential predictor variables and suicide. KEY RESULTS: Two hundred and sixty-nine veteran cases were matched to 538 controls. Average subject age was 63 years; 97 % were male. Rates of mental health conditions, functional decline, sleep disturbance, suicidal ideation, and psychosocial stressors were all significantly greater in cases compared to controls. In the final model describing men in the sample, non-white race (OR=0.51; 95 % CI=0.27-0.98) and VA service-connected disability (OR=0.54; 95 % CI=0.36-0.80) were associated with decreased odds of suicide, while anxiety disorder (OR=3.52; 95 % CI=1.79-6.92), functional decline (OR=2.52; 95 % CI=1.55-4.10), depression (OR =1.82; 95 % CI=1.07-3.10), and endorsement of suicidal ideation (OR=2.27; 95 % CI=1.07-4.83) were associated with greater odds of suicide. CONCLUSIONS: Assessment for anxiety disorders and functional decline in addition to suicidal ideation and depression may be especially important for determining suicide risk in this population. Continued development of interventions that support identifying and addressing these conditions in primary care is indicated.KEY WORDS: mental health; veterans; primary care; health services research.

Courses of suicidal ideation among military veterans in residential treatment for posttraumatic stress disorder

“…Suicidal ideation (SI) and suicide attempts are also prevalent among active duty service members and can result in discharge from military service (Peterson et al, 2018). SI is often a precursor to suicide attempts and death by suicide (e.g., Dobscha et al, 2014; Miranda, Ortin, Scott, & Shaffer, 2014). Therefore, it is important to evaluate the effectiveness of existing treatments in addressing SI among veterans.…”

Suicidal ideation among young Afghanistan/Iraq War Veterans and civilians: Individual, social, and environmental risk factors and perception of unmet mental healthcare needs, United States, 2013

“…Men are at increased risk of fatal suicidal behavior (Luxton et al, 2012; Bush et al, 2013; Schoenbaum et al, 2014; Logan et al, 2015) and women are at increased risk of nonfatal behavior (Lemaire and Graham, 2011; Ursano et al, 2015). Risk factors for most suicide-related outcomes have included: non-Hispanic white race/ethnicity (Luxton et al, 2012; Bush et al, 2013; Schoenbaum et al, 2014; Logan et al, 2015); under 25 years old (among active duty) (Luxton et al, 2012; Bush et al, 2013; Schoenbaum et al, 2014; Logan et al, 2015); enlisted rank of E1–E5 (among active duty) (Bachynski et al, 2012; Hyman et al, 2012; Luxton et al, 2012; Bush et al, 2013; Schoenbaum et al, 2014; Logan et al, 2015); sexual minority status (Blosnich et al, 2013, 2014); pre-enlisted and/or current mental health conditions (Ilgen et al, 2010a; Guerra and Calhoun, 2011; Lemaire and Graham, 2011; Bachynski et al, 2012; Hyman et al, 2012; Skopp et al, 2012; Conner et al, 2013; Luxton et al, 2013; Nock et al, 2014; Ramsawh et al, 2014, 2015; Ramchand et al, 2015); a history of self-directed violence (Lemaire and Graham, 2011; Weiner et al, 2011; Bryan et al, 2015b); substance use problems (Mansfield et al, 2011; Bachynski et al, 2012; LeardMann et al, 2013; Alexander et al, 2014); poor physical health and functionality (e.g., bodily pain, traumatic brain injury) (Ilgen et al, 2010c; Brenner et al, 2011; Magruder et al, 2012; Dobscha et al, 2014); recent disciplinary action from a commanding officer (i.e., Article 15), a demotion, a dishonorable discharge, or recent denial for promotion (among active duty) (Hyman et al, 2012; Schoenbaum et al, 2014; Reger et al, 2015); and intimate partner problems (Hyman et al, 2012; Skopp et al, 2012; Alexander et al, 2014). Suicidal ideation is also associated with lack of social support (Pietrzak et al, 2010; Monteith et al, 2013; Monteith et al, 2015), sexual trauma (Lemaire and Graham, 2011; Lutwak and Dill, 2013), and sleep deprivation (Luxton et al, 2011; …”

Improving Prediction of Suicide and Accidental Death After Discharge From General Hospitals With Natural Language Processing

“…The challenge for any of these risk models is automation, namely, efficiently integrating data to facilitate identification of high-risk individuals. While potential interventions exist, [9][10][11][12] it may not be feasible to offer interventions to everyone. To facilitate such efforts, we sought to examine a large, generalizable group of individuals hospitalized over 9 years at 1 of 2 academic medical centers by coupling electronic health records (EHRs) with long-term death certificate data.…”