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Army Suicide Surveillance: A Prerequisite to Suicide Prevention

Chapter 24

ARMY SUICIDE SURVEILLANCE: 

A PREREQUISITE TO SUICIDE 

PREVENTION

GREGORY A. GAHM, PhD,* and MARK A. REGER, PhD†

INTRODUCTION

SUICIDE PREDICTION DEFINED

SUICIDAL BEHAVIOR PREDICTABILITY

IMPORTANCE OF SUICIDE PREDICTION

EPIDEMIOLOGICAL SURVEILLANCE STUDIES

Models for Suicide Research

An Army Suicide Surveillance System

THE SUICIDE RISK MANAGEMENT AND SURVEILLANCE OFFICE

History of the Office

Army Suicide Event Report Data Collection Process

SUMMARY

*Colonel, Medical Service Corps, US Army; Chief, Department of Psychology, Madigan Army Medical Center, 9933C West Hays Street, Fort Lewis, 

Washington 98431-1100

†

Research Psychologist, Department of Psychology, Madigan Army Medical Center, 9933C West Hays Street, Fort Lewis, Washington 98431-1100; 

Affiliate Assistant Professor, Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, 1925 NE Pacific Street, 

Seattle, Washington 98195-6340 
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Combat and Operational Behavioral Health

INTRODUCTION

“Mental health specialists are now able to predict 

and prevent many suicides.” At first glance, this 

statement (and those similar to it) appears to be a 

reasonable expectation of behavioral health providers. 

Suicidal ideation is a common presenting problem in 

outpatient settings,1,2 and when suicides do occur, they 

inflict a tremendous emotional toll on family, friends, 

coworkers, and the broader community. Caring for the 

psychological needs of individuals requires providers 

to make suicide risk assessment and prevention a high 

priority. A general awareness of the significant amount 

of research that has been conducted to inform clinical 

decisions about suicidal patients may also suggest that 

clinicians can predict and prevent many suicides. Hundreds of studies have added to the body of knowledge 

about suicide, and there are a number of well-respected 

peer-reviewed journals dedicated solely to suicide research. Furthermore, there is a general recognition that 

behavioral health providers have specialized training 

in suicide intervention. Behavioral health providers 

are often viewed as experts in suicide assessment and 

prevention, and psychologists are regularly consulted 

about acute suicide potential in specific individuals, 

both within the military and in the civilian sector. 

However, a closer analysis of the literature supporting the quoted statement suggests that more caution may be indicated. What does it mean to predict 

suicide? What does current research demonstrate 

about clinicians’ abilities to predict suicide? How does 

prediction relate to prevention, and what does it mean 

to prevent suicide? This chapter will review some of 

the current literature on suicide prediction, suggesting that population surveillance studies provide an 

important tool to improve knowledge about suicidal 

behaviors in the military. It will describe an ongoing 

epidemiological surveillance project in the US Army, 

and propose future directions that will maximize the 

benefits of the program. 

SUICIDE PREDICTION DEFINED

What does it mean to predict suicide? Prediction 

requires an individual to “foretell on the basis of 

observation, experience, or scientific reason.”3

 Thus, 

suicide prediction implies an ability to anticipate future behavior. Obviously, truly knowing the future is 

not possible, but case law suggests that defendants in 

legal cases should have intervened when results were 

“reasonably foreseeable.”4 Certainly, clinical providers 

are tasked with predicting “reasonably foreseeable” 

suicide behaviors. Patients often present to providers 

with questions about their own safety. In addition, US 

Army commanders frequently consult psychologists 

for assistance in determining whether suicide is a “reasonably foreseeable” outcome for one of their soldiers. 

Providers are not only asked to assess if a patient will 

attempt or complete suicide, but when. A patient with 

a high risk of an imminent suicidal behavior requires a 

different intervention than an individual with chronic 

risk factors but no imminent risk of self-harm. 

A key question, therefore, relates to the definition of 

“reasonably foreseeable.” What research is available to 

help clinicians predict suicidal behaviors? How well 

can trained mental health experts currently foresee 

suicidal behaviors? The next section reviews some of 

the current research on suicide prediction in an attempt 

to inform future research priorities.

Research on the predictability of suicidAL behaviors

Can providers currently predict suicidal behavior? 

Extensive research has been conducted to identify 

factors that might help in suicide prediction. Many 

variables have been studied, including demographic 

factors, specific risk factors, periods of elevated risk, 

psychopathology, psychiatric comorbidity, medical 

disorders, substance use, personality disorders, and 

personality traits. This body of work has produced 

some helpful information. For example, individuals 

who complete suicide are more likely to be white male 

adolescents or older adults.5–7 Chronic or recurrent depression,8

 especially with comorbid alcoholism,9 also 

increases the risk of suicide. In addition, hopelessness, 

relationship problems, living alone, chronic medical 

problems, and a family history of suicidal behaviors 

appear related to suicide completion.10,11 Most individuals who complete suicide were seen in primary 

care within a month of their death,12 but were less likely 

to be under the care of a behavioral health provider.13

Individuals who complete suicide use methods more 

likely to be fatal, and therefore often die on their first 

attempt.14 At the same time, there is strong evidence 

that a prior suicidal behavior increases the risk of a 

future suicide attempt15 or completion.16

A variety of other risk and protective factors have 

varying degrees of support.10,11 Unfortunately, many of 

these are based on a single study, or on contradictory 

evidence.17 Although a significant body of research 

exists on the topic of suicide, few well-designed studies are available to answer some of the most basic 
395

Army Suicide Surveillance: A Prerequisite to Suicide Prevention

questions in the field. Suicide research is extremely 

complex because of the low base rate of completions; 

ethical problems associated with studying high-risk 

individuals; biases in retrospective data; the cost of 

conducting well-designed studies; and differences in 

suicide rates by gender, age, and ethnicity.

The literature supporting the risk factors reviewed 

above suggests that even when all the known risk factors are considered together, they may only account 

for a small proportion of the variance in suicidal behaviors. That is, the known risk factors do not provide 

clinicians with sufficient information to predict suicide. 

This assertion is strongly supported by studies that 

have attempted to predict future suicides using many 

of the known risk factors described above. In one study 

at a psychiatric hospital, 1,906 inpatients with affective 

disorders were linked to their manner of death during 

a 2- to 14-year follow-up period. Using suicide risk factors judged to have the most robust evidence, researchers attempted to predict which patients would later 

complete suicide. In the follow-up period, 46 patients 

completed suicide. None were correctly predicted by 

the researchers. 

In a similar study, 4,800 psychiatric inpatients were 

prospectively followed for 4 to 6 years.18 Using a variety of risk factors, the researchers explored several approaches to predicting future suicides. Like the study 

described above, they characterized their own results 

as wholly “unsuccessful,” even when alternative statistical approaches were employed in later studies.19

Other studies20,21 have reported similar results. 

Unfortunately, failure to prospectively identify appropriate numbers of suicide completions is only one 

of the problems related to suicide prediction. A second 

problem relates to the high false-positive rate of current suicide prediction models. That is, the probability 

that a person will complete suicide when known risk 

factors are positive is low.17 The implications of this 

problem are magnified exponentially by the fact that 

suicide is a very rare behavior. This problem is not 

simply a matter of statistical trivia, but has significant 

implications for the use of provider time and costs of 

treatment. 

To illustrate the point, the following is an adaptation of an example provided by Gaynes et al.22 Assume 

that a provider could predict suicidal behaviors with 

80% sensitivity and 70% specificity (rates similar to 

depression screening). A provider who saw 10,000 

patients over a number of years, 10 of whom truly 

attempt suicide, would correctly predict 8 suicide attempts while committing 2,997 false-positive errors. 

Thus, even if clinicians could predict suicide with this 

level of sensitivity and specificity, they would still miss 

20% of the suicides, and the low base rate of suicide 

behaviors would result in significant costs related to 

false-positive errors. 

In summary, behavioral health providers do not 

currently have the information they need to predict 

suicidal behaviors with any significant degree of accuracy. This conclusion is shared by many in the field. 

At the end of one of the prediction studies reviewed 

above, Pokorny stated, “Identification of particular 

persons who will (complete) suicide is not currently 

feasible.”18(p249) After reviewing the literature on suicide 

prediction, Paris stated that “it is not possible to predict suicide with any degree of accuracy.”23(p235) Bryan 

and Rudd stated that there is an “inability to predict 

suicidal behavior reliably.”24(p186)

Although many of the studies reviewed above 

were based on actuarial prediction models, conclusions about the accuracy of clinical judgment do not 

differ from those summarized for statistical prediction models. Gaynes et al stated, “Despite the public 

health import of suicide and the Surgeon General’s 

call to action, evidence to guide the primary care clinician’s assessment and management of suicide risk is 

extremely limited.”22(p831) Goldstein et al made the sobering statement that beyond identifying individuals 

with multiple risk factors, “it appears unrealistic for the 

general public or the legal system to expect that health 

professionals be able to predict suicide in specific patients based on our present knowledge.”25(p422) Many 

clinicians and researchers prefer to define the clinician’s role in terms of a “risk assessment process,”24

suggesting a general recognition that providers are 

not capable of predicting suicide. 

IMPORTANCE OF SUICIDE PREDICTION

Is suicide prediction important? Because current 

research to support suicide prediction is immature, and 

well-designed suicide research is extremely difficult 

and costly to conduct, it may be worth considering 

whether prediction is actually an important goal. Unfortunately, an analysis of the question results in the 

inescapable conclusion that without a reasonable ability to predict suicide, prevention efforts are extremely 

ineffective and costly.

Prediction is in many ways a prerequisite of prevention. In order to prevent a condition, prevention 

programs must generally be able to predict, with 

some degree of accuracy, who will benefit from a 

preventive effort. Without any predictive information, preventive actions can still be conducted, but 

high-risk individuals cannot be targeted, the effective 

components cannot be evaluated, and the costs are 

significant. Options for population-targeted preven-
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Combat and Operational Behavioral Health

tion programs include conducting preventive activities with no one, with random individuals (or those 

with the most financial resources), or with groups 

who are believed to be at greater risk. These options 

are usually unacceptable. Clearly, when there is 

reason to believe that effective preventive efforts are 

available, failure to conduct any such activities is far 

from ideal. Performing preventive efforts among only 

those with sufficient economic resources devalues 

human life. However, applying preventive efforts 

to an entire population requires significant financial 

resources and exposes everyone in the group to any 

risks that are associated with the prevention efforts. 

Predictive information is essential for helping clinicians and patients balance the costs and benefits of 

specific preventive efforts. 

An example from the field of dementia illustrates 

the latter point. Results from a number of studies 

suggest that high-dose treatment with the antioxidant 

vitamin E may slow disease progression and reduce 

the incidence of dementia.26–29 Recently, however, 

new safety concerns related to high-dose vitamin E 

treatments have emerged.30,31 Although prophylactic 

vitamin E supplementation may not be indicated for 

all older adults, some patients with known risk factors 

for Alzheimer’s disease (eg, genetic vulnerabilities) 

may determine, after weighing the risks and potential 

benefits with their provider, that the risk–benefit ratio 

supports their use of vitamin E treatment. Advances in 

predicting dementia inform decisions related to preventive practices that may be associated with risks.

Similarly, suicide prevention efforts are not without 

risk. Although biological risks of suicide prevention 

may not apply, specific interventions to prevent suicide 

in a high-risk individual may violate confidentiality, 

harm the therapeutic relationship, increase stigma 

associated with treatment, decrease the probability 

of forthright conversations about suicidal ideation in 

the future, and increase the probability of treatment 

drop-out. In addition, population-based prevention 

efforts targeted at those for whom they are not appropriate may, at a minimum, reduce the effectiveness of 

the program, because messages can be “washed out” 

for everyone receiving nonspecific prevention efforts 

and training. 

Based on the low base rate of suicide behaviors 

and the current accuracy of suicide prediction, wellintentioned interventions are surely targeting many for 

whom the intervention is not needed. It may be argued 

that as long as the negative impact on nonsuicidal individuals is low and the intervention is palatable to the 

community, the effort is justified. However, when individuals are targeted for intervention efforts, clinicians 

are committing numerous false-positive errors. Many 

individuals who are not “truly suicidal” may be targeted with intrusive interventions and suffer adverse 

effects because of the inability to predict suicide.

This discussion is not arguing that efforts aimed at 

prevention should be ended; rather, it is emphasizing the importance of efforts to improve the ability 

to predict suicide behaviors. In fact, efforts aimed at 

prediction can contribute significantly to prevention efforts, because progress in prediction often illuminates 

keys for prevention programs. The following is another 

example from the literature on Alzheimer’s disease. 

Genetic research has now shown that mutations in 

three genes cause many of the early onset (before age 

65) Alzheimer’s disease cases and that these genetic 

mutations result in a build-up of a toxic protein fragment called amyloid beta, which may eventually lead 

to the death of nerve cells. This information has been 

helpful, not only for genetic counseling and predicting which family members will develop the disease, 

but also for defining new treatment approaches. The 

genetic data has informed exciting new approaches 

to treatment and prevention that attempt to “normalize” amyloid beta levels. Significant discoveries about 

suicide prediction would likely suggest information 

about the etiology of suicide that could potentially be 

leveraged by prevention programs. Although the road 

from prediction to prevention may be less direct for 

suicide, findings of significant predictive value would, 

at a minimum, suggest a narrower population in which 

to focus prevention efforts.

Epidemiological Surveillance Studies

Although research has demonstrated that clinicians 

are currently unable to predict which individuals will 

complete suicide with any degree of accuracy, suicide 

reduction is an extremely important health goal, and 

suicide prediction is in many ways a prerequisite to 

suicide prevention. This section reviews the use of 

epidemiological surveillance studies as an important 

tool for improving suicide prediction.

Suicide is not alone in the prediction challenges it 

presents due to its low incidence. A key challenge in 

many areas of medical and psychiatric research is the 

rarity of the disease or condition of interest. Improving the medical community’s ability to predict these 

rare events requires research methods that are effective for studying low base-rate behaviors or diseases. 

Epidemiological surveillance studies offer just such a 

methodology. 

Epidemiological methodologies are not composed 

of a single research design or statistical analysis. Rather, they comprise the body of methods that examine 
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Army Suicide Surveillance: A Prerequisite to Suicide Prevention

the occurrence of health-related conditions or events in 

defined populations.32 Included among these are randomized controlled trials (RCTs), cohort studies, and 

case-control designs. In RCTs, subjects are randomly 

assigned to one of several exposures and prospectively 

followed to determine the effect on outcomes. Cohort 

studies are observational, in the sense that the researcher does not control which subjects are exposed to 

specific variables. A group of participants (a “cohort”) 

is instead identified and then classified based on its 

natural exposure to the variables of interest, and followed over time to measure outcomes. This approach 

allows for the study of some topics that cannot be studied through RCTs, but cohort studies are inefficient for 

rare outcomes because a huge sample size is required 

to identify a sufficient number of infrequent positive 

outcomes on which to base conclusions. In contrast, 

a case-control study identifies individuals who are 

positive for a specific outcome and compares them to 

controls who are negative for the outcome. 

Models for Suicide Research

Consideration of these basic methodologies indicates that RCTs obviously cannot be conducted to 

determine the effect of numerous exposure variables 

(eg, child abuse, combat exposure) on suicide. Large 

cohort studies have clear advantages, but they are 

extremely costly and inefficient for rare events with 

delayed outcomes such as suicide. Case-control studies 

offer an efficient, ethical approach to improving suicide 

prediction. A case-control surveillance system can efficiently identify individuals with suicidal behaviors 

and compare them to control subjects. 

An Army Suicide Surveillance System 

Although a number of suicide surveillance studies 

have been conducted in the United States and Europe 

(eg, the National Center for Injury Prevention, the 

World Health Organization Regional Office for Europe 

[WHO-EURO] Multicentre Study on Parasuicide), 

their results may not generalize to the US Army population. Soldiers represent a demographically distinct 

population that faces unique work-related stressors. 

The Army cohort is a younger, more ethnically diverse, 

and disproportionately male group compared to the 

broader US population.33 Many soldiers are exposed 

to unique experiences and stressors, and as the Army 

mission changes over time, these work-related stressors can shift. Therefore, civilian suicide surveillance 

efforts may be of limited relevance. 

An Army surveillance program offers a number 

of specific advantages. First, such efforts allow the 

Army to track trends over time as the military mission changes. Second, unique Army risk factors, such 

as deployments, combat exposure, training assignments, repeated geographic relocation, and others can 

be studied. Third, recommendations for refining the 

Army’s suicide prevention efforts can be generated. 

Finally, a suicide surveillance program may provide 

opportunities to evaluate the effectiveness of suicide 

prevention programs and policies.

Additional research on suicide in both the military 

and civilian sectors is clearly needed. Epidemiological 

surveillance studies represent one of the more efficient 

approaches to improving suicide prediction. The Army 

has recently established a long-term suicide surveillance 

program to supplement its other risk-tracking efforts. 

The Suicide Risk Management and Surveillance Office

History of the Office

To effectively execute the suicide surveillance mission, the US Army established the Suicide Risk Management and Surveillance Office (SRMSO), a Medical 

Command office based at Fort Lewis, Washington. In 

2002 and 2003, questions for an epidemiological data 

collection tool called the Army Suicide Event Report 

(ASER) were fielded, and content was clarified and 

revised. The ASER evolved from a scannable, paperbased data capture and processing approach, to an 

electronic Microsoft Word form, to a Web form submitted on a secure site. On February 4, 2004, Army Suicide Event Reporting Implementation Guidance was 

signed by Major General Kenneth Farmer, Jr, Deputy 

Surgeon General. This was followed by a widely circulated memorandum signed by Major General Joseph 

Webb, Jr, Deputy Surgeon General, stating that “the 

behavioral health leadership at each medical treatment 

facility will complete the ASER in accordance with the 

Implementation Guidance.” The ASER requirement is 

also specifically addressed in the revised Army Regulation 600-63, Army Health Promotion.

34 

Army Suicide Event Report Data Collection Process

The ASER is a data collection form intended to 

standardize the data collected on all suicidal behaviors among Army soldiers. Submission of an ASER is 

required for all suicide-related behaviors that result 

in death, hospitalization, or evacuation from theater. 

To support this requirement, SRMSO has worked 

with each medical treatment facility (MTF) to identify 

both a command and an ASER point of contact (POC). 

The command POC is generally the MTF commander 
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Combat and Operational Behavioral Health

who is responsible for ensuring regional compliance 

with ASER requirements. The command POC also 

appoints a provider to serve as the ASER POC, who is 

responsible for either personally completing the MTF’s 

ASERs, or ensuring that a qualified provider completes 

the requirements. 

For suicide completions, the data collection process 

generally begins when SRMSO receives notification 

from the Armed Forces Medical Examiner’s Office at 

the Armed Forces Institute of Pathology that a soldier’s 

death has been confirmed as a suicide (Figure 24-1). 

Upon such notification, the ASER and command POC 

for the MTF are notified and requested to complete an 

ASER within 60 days. Alternatively, ASERs are commonly submitted after a suicide completion is identified locally; SRMSO then confirms this determination 

with the medical examiner’s office.

For suicidal behaviors resulting in hospitalization or 

evacuation, the data-collection process requires ASER 

POCs to submit monthly reports for each MTF. This 

reporting generally involves coordination with inpatient psychiatric personnel and outpatient behavioral 

health clinic personnel. Because no central system formally tracks nonfatal suicide behaviors, these reports 

are currently used to determine how many ASERs are 

required for each MTF. ASER POCs are notified when 

expected ASERs are past due (30 days). 

Army Suicide Event Report Questions

Development of the current ASER content evolved 

from a structured review of the past versions and data, 

and a systematic review of the literature. The results of 

the review were assessed for evidence-based predictors of suicide risk, and additional identified questions 

were combined into the update of the ASER. 

For theoretically meaningful presentation of relevant risk factors for suicide and suicidal behavior, risk 

variables were organized into four categories using a 

prototype successfully implemented in the violence 

Figure 24-1. Army Suicide Event Report data collection.

AFME: Armed Forces Medical Examiner’s Office

ASER: Army Suicide Event Report

HOSP: hospital

MTF: medical treatment facility

POC: point of contact

SRMSO: Suicide Risk Management and Surveillance Office

COMPLETED 

SUICIDE

NOT

COMPLETED 

SUICIDE

SUICIDE EVENT

SRMSO AFME LIST 

CONFIRMS

POC SUBMITS 

MTF HOSP 

NUMBERS

POC 

COMPLETES 

ASER

NOTICE OR REMINDERS 

TO POC TO COMPLETE 

ASER 

POC 

COMPLETES 

ASER

 

 

  






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Army Suicide Surveillance: A Prerequisite to Suicide Prevention

risk assessment literature35: (1) dispositional or personal factors (eg, demographics); (2) historical or developmental factors (eg, family history, prior suicidal 

behaviors, life events); (3) contextual or situational 

factors (eg, access to firearms, place of residence); and 

(4) clinical or symptom factors (eg, posttraumatic stress 

disorder, other psychiatric disorders or symptoms). 

This categorical banding of risks is intended to help 

organize the complex and multifaceted factors that 

contribute to suicidal behaviors. These factors were 

combined with a comprehensive set of questions 

related to the event (eg, method, location, injuries) to 

form the current ASER. 

Required Source Information

Completion of an ASER requires a review of all 

relevant and available records. In addition, interviews 

may be needed in some cases, especially when suicidal 

behaviors resulted in hospitalization or evacuation. 

These data sources are described in Table 24-1. 

Suicide Risk Management and Surveillance Office 

Reports

SRMSO drafts regular reports of suicide findings 

and also responds to requests from senior leaders for 

specific analyses. SRMSO generates quarterly and annual reports that are provided to the behavioral health 

consultants to the Surgeon General, the Army Suicide 

Prevention Program (G-1), and all ASER POCs and 

command POCs. 

Future Directions

Current SRMSO efforts are focused on improving 

data quality and accessibility for senior leaders. First, 

SRMSO is pursuing approaches to populating the 

ASER database from existing Army and Department 

of Defense data sources. As described above, the 

ASER POC must collect all relevant documents and 

data, extract the information that applies to specific 

ASER questions, and enter the data manually without 

errors. Populating the ASER database from existing 

databases with data quality assurances eliminates 

many opportunities for error. Significant conclusions 

and recommendations are drawn from ASER data, and 

the importance of this data is growing. For example, 

the Office of The Surgeon General has funded a new 

Suicide Prevention Office that is charged, in part, with 

facilitating new Army-wide prevention efforts based 

on empirical evidence derived from ASER research, 

the only Army-wide source of information on most 

aspects of Army suicide. Improving the reliability of 

ASER data provides Army leadership and the Suicide 

Prevention Office an improved capacity to make sound 

conclusions and recommendations. 

Second, SRMSO is exploring options to improve the 

accessibility of ASER data for senior leaders. Currently 

ASER data are available in an Oracle database at the 

Fort Lewis, Washington, SRMSO office. Qualified requesters must submit a request for a report to SRMSO. 

A researcher at SRMSO must then query the database 

and analyze the results. SRMSO then checks and rechecks the results to assure that they are accurate and 

will answer the questions asked. Finally, the SRMSO 

research team must determine the most meaningful 

graphical representation, create the graphs, and return 

the results to the requestor. Although SRMSO has a 

solid track record of timeliness and efficiency, this process is less than ideal, especially given the importance 

of suicide and the short suspense that Department of 

Defense leaders often face. 

SRMSO is exploring options for a user-friendly data 

reporting tool that can be configured to rapidly extract 

information from data sets and provide reports using 

predetermined statistical analyses and intuitive visual 

output. The Web-based Injury Statistics Query and 

Reporting System on the Centers for Disease Control 

and Prevention Web site provides a good example of 

such a tool.6

 The user is prompted to select types of 

data and appropriate categorical grouping variables. 

The graphical interface is not only informative but also 

Table 24-1

Source Information Required to Complete an Army Suicide Event Report

Event Required Data Sources

Completed 

suicide

Review of medical and behavioral health 

records

Personnel and counseling records

Investigative agency records (eg, Criminal 

Investigation Division)

Records related to manner of death (casualty 

reports, toxicology, autopsy, suicide notes)

Interview of coworkers and supervisors as 

needed and appropriate

Interview of responsible investigative agency 

officer, as needed and appropriate

Interview of other involved professionals 

and family members when appropriate

Attempted 

suicide 

Interview of patient

Review of medical and behavioral health 

records

Interview of coworkers and supervisors as 

needed
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Combat and Operational Behavioral Health

interactive, allowing the user to drill down to get more 

specific information within a given domain. ASER 

data reported via a similar output generator would be 

delivered as an intuitive, interactive graphical output, 

rapidly generated to support the mission of senior 

leadership and healthcare providers. 

A number of additional future directions are in the 

planning stages. One goal is to provide behavioral 

health clinicians access to relevant local ASERs to 

improve clinical care and safety planning. In addition, SRMSO is pursuing software functionality for 

command and ASER POCs to view regional ASER 

data over time. Efforts are also underway to improve 

the size and quality of control samples to compare to 

Army data. A large control sample drawn from the 

Army at large would be of significant value. Finally, 

SRMSO is focusing on developing a longitudinal data 

set. Even with a population as large as the Army, some 

topics cannot be studied because of the low base rate 

of suicide completions (eg, many questions related to 

suicides in Iraq). Longitudinal data over several years 

will allow for richer analysis.

Summary

This chapter reviewed the issues and expectations associated with the prediction of suicides. 

A generally pessimistic conclusion was drawn 

regarding the ability to predict suicides with the 

current level of knowledge. After reviewing methods that may improve prediction of suicide risk, 

the authors recommended a surveillance model. 

Finally, the surveillance process within the Army 

was reviewed in detail, outlining its process, challenges, and goals. 

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