Predicting suicides after psychiatric hospitalization in US Army soldiers: the Army Study To Assess Risk and rEsilience in Servicemembers (Army STARRS).

IMPORTANCE 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. OBJECTIVE 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. DESIGN, SETTING, AND PARTICIPANTS 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. MAIN OUTCOMES AND MEASURES Suicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge. RESULTS 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). CONCLUSIONS AND RELEVANCE 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.

[1]  S. Berrouiguet,et al.  Post-acute crisis text messaging outreach for suicide prevention: A pilot study , 2014, Psychiatry Research.

[2]  I. Kohane,et al.  Finding the missing link for big biomedical data. , 2014, JAMA.

[3]  E. D. Klonsky,et al.  Correlates of suicide attempts among self-injurers: a meta-analysis. , 2014, Clinical psychology review.

[4]  M. Stein,et al.  The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) , 2014, Psychiatry.

[5]  R. Kessler,et al.  Predictors of suicide and accident death in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS): results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). , 2014, JAMA psychiatry.

[6]  M. Olfson,et al.  Focusing suicide prevention on periods of high risk. , 2014, JAMA.

[7]  M. Large,et al.  Debate: Clinical risk categorisation is valuable in the prevention of suicide and severe violence – No , 2014, Australasian psychiatry : bulletin of Royal Australian and New Zealand College of Psychiatrists.

[8]  Nancy Gebler,et al.  Design of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) , 2013, International journal of methods in psychiatric research.

[9]  Subin Park,et al.  Suicide mortality and risk factors in the 12 months after discharge from psychiatric inpatient care in Korea: 1989–2006 , 2013, Psychiatry Research.

[10]  L. Appleby,et al.  Suicide within two weeks of discharge from psychiatric inpatient care: a case-control study. , 2013, Psychiatric services.

[11]  D. Luxton,et al.  Suicide risk among US Service members after psychiatric hospitalization, 2001-2011. , 2013, Psychiatric services.

[12]  R. Kessler,et al.  Suicide Among Soldiers: A Review of Psychosocial Risk and Protective Factors , 2013, Psychiatry.

[13]  P. Kuhnert Recursive Partitioning and Applications.Second Edition. By H. Zhang and B.H. Singer. New York: Springer. 2010. 276 pages. UK£53.99 (hardback). ISBN 978-1-4419-6823-4. , 2013 .

[14]  M. King,et al.  The influence of sensitivity to reward and punishment, propensity for sensation seeking, depression, and anxiety on the risky behaviour of novice drivers: a path model. , 2012, British journal of psychology.

[15]  Gerald J. Hahn,et al.  Applied Regression Analysis (2nd Ed.) , 2012 .

[16]  L. Appleby,et al.  Implementation of mental health service recommendations in England and Wales and suicide rates, 1997–2006: a cross-sectional and before-and-after observational study , 2012, The Lancet.

[17]  Linda Cottrell,et al.  Suicide incidence and risk factors in an active duty US military population. , 2012, American journal of public health.

[18]  Bruce H Jones,et al.  Mental health risk factors for suicides in the US Army, 2007–8 , 2012, Injury Prevention.

[19]  M. Large,et al.  Risk Factors for Suicide Within a Year of Discharge from Psychiatric Hospital: A Systematic Meta-Analysis , 2011, The Australian and New Zealand journal of psychiatry.

[20]  E. Ritchie,et al.  Prevalence and Risk Factors Associated With Suicides of Army Soldiers 2001–2009 , 2011 .

[21]  M. J. Laan,et al.  Targeted Learning: Causal Inference for Observational and Experimental Data , 2011 .

[22]  M. Zamorski Suicide prevention in military organizations , 2011, International review of psychiatry.

[23]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[24]  Shalabh Statistical Learning from a Regression Perspective , 2009 .

[25]  P. Links,et al.  Review of predictors of suicide within 1 year of discharge from a psychiatric hospital , 2008, Current psychiatry reports.

[26]  H. Zou,et al.  Addendum: Regularization and variable selection via the elastic net , 2005 .

[27]  S. Pirkola,et al.  The characteristics of suicides within a week of discharge after psychiatric hospitalisation – a nationwide register study , 2005, BMC psychiatry.

[28]  H. Mcdonald,et al.  Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. , 2005, JAMA.

[29]  R. Berk Regression Analysis: A Constructive Critique , 2003 .

[30]  J. Kruse,et al.  Application of stratum-specific likelihood ratios in mental health screening , 2000, Social Psychiatry and Psychiatric Epidemiology.

[31]  Arthur E. Hoerl,et al.  Ridge Regression: Biased Estimation for Nonorthogonal Problems , 2000, Technometrics.

[32]  Heping Zhang,et al.  Recursive Partitioning and Applications , 1999 .

[33]  R. Stine Graphical Interpretation of Variance Inflation Factors , 1995 .

[34]  D. Rubin Multiple imputation for nonresponse in surveys , 1989 .

[35]  B. Efron Logistic Regression, Survival Analysis, and the Kaplan-Meier Curve , 1988 .

[36]  D H Gustafson,et al.  Suicide risk prediction by computer interview: a prospective study. , 1987, The Journal of clinical psychiatry.

[37]  D. Gustafson,et al.  A computer-based system for identifying suicide attemptors. , 1981, Computers and biomedical research, an international journal.

[38]  D H Gustafson,et al.  A probabilistic system for identifying suicide attemptors. , 1977, Computers and biomedical research, an international journal.

[39]  N. Draper,et al.  Applied Regression Analysis. , 1967 .

[40]  Lena Osterhagen,et al.  Multiple Imputation For Nonresponse In Surveys , 2016 .

[41]  Deaths by suicide while on active duty, active and reserve components, U.S. Armed Forces, 1998-2011. , 2012, MSMR.

[42]  V. Hasselblad,et al.  Effect of Clinical Decision-Support Systems A Systematic Review , 2012 .

[43]  Jörg Drechsler,et al.  Multiple Imputation for Nonresponse , 2011 .

[44]  Ilyssa E. Hollander,et al.  The American Association of Suicidology Prior Health Care Utilization Patterns and Suicide Among U . S . Army Soldiers , 2010 .

[45]  Daniel Eisenberg,et al.  Higher-risk periods for suicide among VA patients receiving depression treatment: prioritizing suicide prevention efforts. , 2009, Journal of affective disorders.

[46]  J. Maindonald Statistical Learning from a Regression Perspective , 2008 .

[47]  Blaz Zupan,et al.  Towards knowledge-based gene expression data mining , 2007, J. Biomed. Informatics.

[48]  Piper C. M. Williams,et al.  Uniformed Services University of the Health Sciences. , 2003, Academic medicine : journal of the Association of American Medical Colleges.

[49]  W. Grove,et al.  Clinical versus mechanical prediction: a meta-analysis. , 2000, Psychological assessment.

[50]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .