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


METHODS
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.


METHODS
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
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.
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Ronald C
RC
Kessler
Department of Behavioral Medicine, Blanchfield Army Community Hospital, Fort Campbell, Kentucky.
Christopher H
CH
Warner
US Army Office of the Surgeon General, Falls Church, Virginia.
Christopher
C
Ivany
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Maria V
MV
Petukhova
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Sherri
S
Rose
Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, New York.
Evelyn J
EJ
Bromet
US Army Office of the Surgeon General, Falls Church, Virginia.
Millard
M
Brown
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.
Tianxi
T
Cai
National Institute of Mental Health, Bethesda, Maryland.
Lisa J
LJ
Colpe
US Army Public Health Command, Aberdeen Proving Ground, Maryland.
Kenneth L
KL
Cox
Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, Maryland.
Carol S
CS
Fullerton
Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, Massachusetts10Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts.
Stephen E
SE
Gilman
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Michael J
MJ
Gruber
Institute for Social Research, University of Michigan, Ann Arbor.
Steven G
SG
Heeringa
Institute for Social Research, University of Michigan, Ann Arbor.
Lisa
L
Lewandowski-Romps
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.
Junlong
J
Li
US Army Public Health Command, Aberdeen Proving Ground, Maryland.
Amy M
AM
Millikan-Bell
Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, Maryland.
James A
JA
Naifeh
Department of Psychology, Harvard University, Cambridge, Massachusetts.
Matthew K
MK
Nock
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Anthony J
AJ
Rosellini
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Nancy A
NA
Sampson
National Institute of Mental Health, Bethesda, Maryland.
Michael
M
Schoenbaum
Department of Psychiatry, University of California, San Diego, La Jolla14Deapartment of Family and Preventive Medicine, University of California, San Diego, La Jolla15Veterans Affairs San Diego Healthcare System, San Diego, California.
Murray B
MB
Stein
King's Centre for Military Health Research, King's College London, London, United Kingdom.
Simon
S
Wessely
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Alan M
AM
Zaslavsky
Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, Maryland.
Robert J
RJ
Ursano
D000328:Adult; D000359:Aftercare / Q000523:psychology; D000465:Algorithms; D003710:Demography; D005260:Female; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000150:complications / Q000453:epidemiology / Q000523:psychology / Q000628:therapy; D008889:Military Personnel; D020380:Needs Assessment; D010351:Patient Discharge / Q000592:standards; D011599:Psychopathology / Q000379:methods*; D012372:ROC Curve; D055500:Resilience, Psychological; D012306:Risk; D018570:Risk Assessment / Q000379:methods*; D012737:Sex Factors; D012959:Socioeconomic Factors; D013405:Suicide / Q000523:psychology / Q000706:statistics & numerical data; D014481:United States / Q000453:epidemiology; D000092864:Suicide Prevention