As of September 30, 2018, there were 4.74 million veterans receiving VA disability compensation. Each veteran’s data records store vital clues that could help improve the health care and well-being of other veterans. The U.S. Department of Veterans Affairs (VA) has been partnering with tech companies, such as Alphabet, to develop tools and techniques that can predict disease and injury in veterans.
To learn more, check out the infographic below created by the Ohio University Online Master of Business Analytics program.

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Veterans in the U.S.
After discharge, veterans face a different kind of battle at home; regaining their physical and mental health. The VA has conducted numerous studies to identify the health challenges veterans face in order to improve VA services.
2018 Statistics
There were 19,602,316 veterans living in the US in 2018, 90.3% of which were male. The National Health Study for a New Generation of U.S. Veterans was a study surveying 60,000 of these vets, specifically Operating Enduring Freedom (OEF) veterans, Operation Iraqi Freedom (OIF) veterans, and veterans who served in the military between October 2001 and June 2008. Its goals were to “provide insight on the overall health of recent veterans,” “improve VA’s understanding of what health services veterans need,” and “maximize the quality of care that VA offers.” The methodology used was a questionnaire that covered topics disease and reproductive health. 2,000 of the study’s participants allowed researchers to review their medical records.
The survey revealed that 57.3% of veterans were either current or former smokers. It also showed 41.5% of women had experienced military sexual trauma, compared to just 4% of men. Additionally, 13.5% of those surveyed had screened positive for PTSD. 15.8% of women and 13.8% of men surveyed also experienced infertility. Finally, it was determined that sinusitis was 29% more likely in deployed veterans than in non-deployed veterans.
Tackling Kidney Conditions with Big Data Analytics Tools
Kidney conditions have been the subject of numerous studies conducted by the VA and its partners. The VA recently partnered with Alphabet’s DeepMind to identify VA patients at risk of acute kidney injury.
Kidney Conditions
One of the more prominent kidney conditions is chronic kidney disease or CKD. Per the National Kidney Foundations, this “is a condition characterized by a gradual loss of kidney function over time.” It can be caused by diabetes and high blood pressure.
Another key kidney condition is acute kidney injury (AKI), which occurs when sudden kidney failure hinders proper waste removal from the body. AKI can be caused by antibiotics, disease, or crushing injuries like blast injuries. Though tests can detect AKI, according to an article by Wired, doctors can only work to “prevent further damage, not directly treat the injury itself.”
Studying AKI and CKD
The National Kidney Disease Registry was created in 2012 to monitor kidney disease among veterans. A 2015 study “found that patients who developed AKI while hospitalized for any reason were at substantial risk of developing CKD.” A second 2015 study of veterans with CKD revealed an increased likelihood of contracting vascular disease, hypertension, diabetes, and cancer, compared with veterans without CDK.
DeepMind and VA
The VA and DeepMind signed a Collaborative Research and Development Agreement in early 2018. This collaboration yielded a study sample of some 700,000 medical records from U.S. veterans, with a twofold goal: They wanted to study patient deterioration and its risk factors, including AKI, and they wanted to predict a patient’s likelihood of developing acute kidney injury (AKI) and prevent the condition. They gathered data via neural network technology, which is a type of deep learning technology used for pattern recognition. The study phases were split between a study of VA-provided records and live data from current VA patients to, per Wired, “track the accuracy of DeepMind’s AKI predictions over time.”
The VA Reach Vet Program
Every day, an average of 20 veterans commit suicide. The VA launched the REACH VET program in 2017 to identify patients at risk and prevent suicide.
How it Works:
According to the Federal News Network, “The REACH VET” program draws on the agency’s vast trove of electronic health records and uses predictive analytics to identify patients who might be at risk of suicide.”
TechTarget defines predictive analytics as “a form of advanced analytics that uses both new and historical data to forecast activity, behavior, and trends.” Data seta are manipulated using statistical analysis techniques, analytical queries, and automated machine learning algorithms. This creates predictive models that then score the probability that a particular event will occur.
A REACH VET coordinator identifies providers who should offer this program to their veteran patients. The provider then reviews patient files and identifies patients who may benefit from the program. VA clinicians can then reach out to a dedicated group of psychologists, social workers, and other clinicians hired by the VA with any questions about the program. The program is especially critical to veterans’ health because individuals with a high risk of suicide can also be at high risk for issues like overdose, violence, and opioid abuse.
More than 30,000 veterans were reached via the program, including roughly 6,700 active monthly VA users. These participating veterans experienced fewer admission to mental health impatient units, increased visits to the VA, and increased attendance for primary care and mental health appointments. This is important – many veterans miss appointments, and the VA struggles to reach veteran patients.
Conclusion
The road to preventing veteran suicide and improving veterans’ physical and mental well-being will entail partnerships between the VA and tech companies. Data analysis professionals will play an active role in using technology to uncover insights that could lead to life-saving solutions.
Learn more about Ohio University’s Online Master of Business Analytics program.