Big data is helping to reduce army suicides!

Big data benefits are many and that is already evident from ‘n’ number of articles displaying on Google Search. But do you know that big data is also helping in preventing army suicides? Yes, you’ve heard it right!

For those connected to data field, this might be an old news piece. But for those who are in defense and army field it can prove as an encouraging fact. And the info goes on as such-

In the year 2008, the Department of Defense recognized that soldier suicides were growing at an alarming rate. That year, the Center for Disease Control and Prevention reported that the average rate of suicides in United States was 11.9 deaths per 100,000 people.

But in the US Army an organization which is having approximately 500,000 members, in contrast, saw a rate of 20.2 suicide deaths per 100,000 people that same year, which is approximately double the civilian rate. This is when the army realized that an immediate and decisive action is needed to stop these suicides.

The problem, however, was that no two leaders agreed on what was causing such an increase in suicidal deaths, leaving the armed forces at a loss for how to address the problem.

To better understand the factors driving so many soldiers to take their own lives, the Army partnered with the National Institute of Mental Health (NIMH) to create the largest military-based mental health study ever undertaken, the Army Study to Assess Risk and Resilience in Service members or Army STARRS project, in 2009.

The project was taken up to understand what was driving these suicidal numbers? what were the risks faced by the soldiers and what was acting as a tipping point to push the soldiers into trouble?

The controlling power was given to Terri Tanielian, a senior research analyst for the RAND Corporation and co-director of the Invisible Wounds of War project, an independent, large-scale assessment of the psychological and cognitive effects of the wars in Iraq and Afghanistan.

The ray of hope from the project was to see patterns across different cases that would help them identify important risk factors. And if they could do that, they had hope of targeting interventions and reducing the overall number of suicides.

Now, six years later, the Army STARRS partnership has yielded important data on the problem of soldier suicides. The initial results may have the power to inform how the military can better prevent both attempted and completed suicidal death in the future.

Michael Schoenbaum, PhD, an NIMH scientific principal for STARRS, says that trying to look at suicide risk factors is a challenge — especially since suicide is not your typical epidemiological problem.

“Suicide remains a rare event,” he explains. “The vast majority of people with any given risk factor or factors will never reach that outcome.”

Also, he points out; people who do attempt suicide don’t always have much in common. “It’s clear that there’s no single answer here. We need an approach that, if we’re lucky, will help us find a lot of little answers.”

That’s where big data, or the analysis of extremely large data sets to identify patterns and trends, come into play. The Army collects and keeps an astonishing amount of data about each soldier, says STARRS administrative principal investigator Ronald Kessler, PhD, professor of health care policy at Harvard Medical School.

It is evident that each soldier has a single ID number that can be used to link medical data with criminal justice data, human service data, school data and employee data. This data, when falls into the right hands has the richness that we can use to help target soldiers at high suicide risk.

The STARRS research team has now published a series of studies in the Journal of the American Medical Association for Psychiatry over the past year about the various, and somewhat surprising, factors that did rise to the top in data collected from active duty soldiers between 2004 and 2009.

Initial STARRS studies looked solely at those individuals who had committed suicide — and found that factors including a recent demotion and family problems were common. Those who committed suicide were also more likely to be white and male — and while a previous or current combat deployment was a slight risk factor, it was more so for women than men.

Additional research by the STARRS consortium revealed that approximately one-third of Army suicide attempts were linked to mental disorders that existed prior to a soldier’s inclusion into armed forces.

Now, the project has reached to such a level that it has collected enough info which will help in predicting and reducing the suicidal tendencies among soldiers.

As a first stepping, the STARRS group has published a study analyzing approximately 40K soldiers who had been hospitalized at least once for a mental health issue. This group is at a particularly high risk for suicide as 68 soldiers from the said group took their own lives within one year of hospital discharge, making up approximately 12% of all Army suicides.

Out of the said number of individuals who committed suicide, the data study made on them in a different angle helped in discovering other common risk factor beyond hospitalization that could help in predicting who would go on to commit suicide once released.

The STARRS team analyzed the records of patients with a history of hospitalization for mental health disorders, focusing on more than 300 different variables thought to be related to an increased risk of suicide.

Using this approach, they discovered that about 20 of those variables showed strong predictive quality. These included a hearing loss, prior criminal offenses, an initial enlistment after the age of 26, previous suicide attempts and a higher IQ score.

The research was carried in such a way that the causalities were never over-attributed. At the same time the studies do confirm that there is no one factor even in this high-risk group that predicts suicide. On the other hand, these factors are useful as a checklist that might help clinicians determine if a particular patient might need more help once he or she is released from the hospital.

With this data at fingertips doctors can target patients who could be assigned with post-hospital aftercare services.

After analyzing risk factors among psychiatric inpatient soldiers, the STARRS team is now working on a similar risk-prediction model for soldiers who visited the hospital for psychiatric outpatient therapy, using an even larger data set.

The goal is to continuously fine-tune the factors that could lead to suicide. Army STARRS hoped to show that it is possible to use data to identify the 5,000 people who are at higher risk out of the 500,000 total people in the Army so that we can offer them something more intensive before the real catastrophe occurs.

If this study stands out, then Big Data will not only help in reducing the suicidal count among soldiers, but can also help in bringing down the suicides count to ‘0’.



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