Dataset Information

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

ABSTRACT: The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100?000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded.

SUBMITTER: Kessler RC

PROVIDER: S-EPMC5247428 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

Kessler R C RC Stein M B MB Petukhova M V MV Bliese P P Bossarte R M RM Bromet E J EJ Fullerton C S CS Gilman S E SE Ivany C C Lewandowski-Romps L L Millikan Bell A A Naifeh J A JA Nock M K MK Reis B Y BY Rosellini A J AJ Sampson N A NA Zaslavsky A M AM Ursano R J RJ

Molecular psychiatry 20160719 4

The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict ...[more]

PMID: 27431294

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Project description:The US Army experienced a sharp increase in soldier suicides beginning in 2004. Administrative data reveal that among those at highest risk are soldiers in the 12 months after inpatient treatment of a psychiatric disorder.To develop an actuarial risk algorithm predicting suicide in the 12 months after US Army soldier inpatient treatment of a psychiatric disorder to target expanded posthospitalization care.There were 53,769 hospitalizations of active duty soldiers from January 1, 2004, through December 31, 2009, with International Classification of Diseases, Ninth Revision, Clinical Modification psychiatric admission diagnoses. Administrative data available before hospital discharge abstracted from a wide range of data systems (sociodemographic, US Army career, criminal justice, and medical or pharmacy) were used to predict suicides in the subsequent 12 months using machine learning methods (regression trees and penalized regressions) designed to evaluate cross-validated linear, nonlinear, and interactive predictive associations.Suicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge.Sixty-eight soldiers died by suicide within 12 months of hospital discharge (12.0% of all US Army suicides), equivalent to 263.9 suicides per 100,000 person-years compared with 18.5 suicides per 100,000 person-years in the total US Army. The strongest predictors included sociodemographics (male sex [odds ratio (OR), 7.9; 95% CI, 1.9-32.6] and late age of enlistment [OR, 1.9; 95% CI, 1.0-3.5]), criminal offenses (verbal violence [OR, 2.2; 95% CI, 1.2-4.0] and weapons possession [OR, 5.6; 95% CI, 1.7-18.3]), prior suicidality [OR, 2.9; 95% CI, 1.7-4.9], aspects of prior psychiatric inpatient and outpatient treatment (eg, number of antidepressant prescriptions filled in the past 12 months [OR, 1.3; 95% CI, 1.1-1.7]), and disorders diagnosed during the focal hospitalizations (eg, nonaffective psychosis [OR, 2.9; 95% CI, 1.2-7.0]). A total of 52.9% of posthospitalization suicides occurred after the 5% of hospitalizations with highest predicted suicide risk (3824.1 suicides per 100,000 person-years). These highest-risk hospitalizations also accounted for significantly elevated proportions of several other adverse posthospitalization outcomes (unintentional injury deaths, suicide attempts, and subsequent hospitalizations).The high concentration of risk of suicide and other adverse outcomes might justify targeting expanded posthospitalization interventions to soldiers classified as having highest posthospitalization suicide risk, although final determination requires careful consideration of intervention costs, comparative effectiveness, and possible adverse effects.

Project description:OBJECTIVE:Understanding suicide risk is a priority for the US military. We aimed to estimate associations of childhood maltreatment with pre-enlistment suicidal behaviors in new Army soldiers. METHODS:Cross-sectional survey data from 38,237 soldiers reporting for basic training from April 2011 through November 2012 were analyzed. Scales assessing retrospectively reported childhood abuse and neglect were derived and subjected to latent class analysis, which yielded 5 profiles: No Maltreatment, Episodic Emotional Maltreatment, Frequent Emotional/Physical Maltreatment, Episodic Emotional/Sexual Abuse, and Frequent Emotional/Physical/Sexual Maltreatment. Discrete-time survival analysis was used to estimate associations of maltreatment profiles with suicidal behaviors (assessed with a modified Columbia-Suicide Severity Rating Scale), adjusting for sociodemographics and mental disorders. RESULTS:Nearly 1 in 5 new soldiers was classified as experiencing childhood maltreatment. Relative to No Maltreatment, all multivariate maltreatment profiles were associated (P values < .001) with elevated odds of lifetime suicidal ideation (adjusted odds ratios [AORs] = 3.10-4.93), plan (AORs = 3.75-10.77), attempt (AORs = 3.60-15.95), and onset of plan among those with ideation (AORs = 1.40-3.10). Several profiles also predicted attempts among those with plans (AORs = 2.01-2.47), and Frequent Emotional/Physical/Sexual Maltreatment predicted unplanned attempts among ideators (AOR = 5.32). Adjustment for mental disorders attenuated but did not eliminate these associations. CONCLUSIONS:Childhood maltreatment is strongly associated with suicidal behavior among new soldiers, even after adjusting for intervening mental disorders. Among soldiers with lifetime ideation, certain maltreatment profiles are associated with elevated odds of subsequently planning and/or attempting suicide. Focus on childhood maltreatment might reveal avenues for risk reduction among new soldiers.

Dataset Information

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

Publications

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

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