Partner Success with AWS / General Public Services / United States

September 2024

Stop Soldier Suicide Uses Pariveda Data Platform on AWS to Better Predict Risk for Veterans

Learn how Pariveda and AWS are helping Stop Soldier Suicide reduce the military suicide
rate.

Ingests

device data in minutes and enriches it with other contextual information

Enables

redaction and cleansing of millions of data points per device in hours

Helps

better predict risk of suicide for veterans

Supports

goal of reducing military suicide rate by 40% by 2030

Overview

Stop Soldier Suicide is a nonprofit organization striving to solve the issue of suicide among US veterans and service members. Because it wanted to understand its data better to gain new insights, the organization worked with AWS Partner Pariveda to implement the Suicide Intelligence Platform (SIP), which ingests forensic device data, integrates it with health cloud data, and stores it in an AWS-based data lake.

Using the SIP solution, Stop Soldier Suicide can ingest and enrich data from multiple sources to better predict the risk of veteran suicide and help clinicians mitigate that risk. As a result, Stop Soldier Suicide can support its mission of reducing the military suicide rate by 40 percent by 2030.

Affectionate military reunion between father and daughter

Opportunity | Struggling to Analyze Forensic Data

Every year since 2001, more than 6,000 US military veterans die by suicide, with many of those showing no signs of mental illness or risk of suicide. Stop Soldier Suicide is on a mission to help stop this growing problem. The only national nonprofit focused solely on solving the issue of suicide among US veterans and service members, Stop Soldier Suicide provides evidence-based therapies and suicide-specific interventions for the most at-risk veterans and service members. “Our vision is a nation where veterans and service members have no greater risk for suicide than any other American. We have an aggressive goal to reduce the military suicide rate by 40 percent by no later than 2030,” says Austin Grimes, chief product officer at Stop Soldier Suicide. To support its mission, Stop Soldier Suicide needed to understand its data better to see trends and offer new insights to those who are helping the veteran community prevent the veteran suicide rate from rising.

As part of its efforts, the organization started the Black Box Project, a forensic data analysis project that uses artificial intelligence to identify and analyze clinically meaningful data from digital devices of veterans who died by suicide. However, Stop Soldier Suicide struggled to analyze the data collected from the project. Grimes says, “We were stuck with local, disorganized data that simply could not be used due to the amount of variance in both data quality and taxonomy of extracted device data.” To solve the problem, Stop Soldier Suicide wanted to create a new solution that quickly ingested data from different sources and simplified analysis. “We wanted to build the world's best suite of tools and models that can understand and predict an individual’s risk and build a deeper understanding of who these veterans and service members are,” Grimes says.

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Through a focus on predicting acute levels of risk with the Pariveda and AWS platform, we can assist clinicians in applying the right resources at the right time to mitigate the risk of suicide.”

Austin Grimes
Chief Product Officer, Stop Soldier Suicide

Solution | Building the Suicide Intelligence Platform on AWS

As an Amazon Web Services (AWS) customer, Stop Soldier Suicide knew it wanted to build a cloud-based solution. The organization met that requirement by working with Pariveda, a technology and management consulting firm and AWS Partner. Grimes explains, “Because we are a lean nonprofit organization without internal capabilities to fully build and deploy cloud infrastructure, Pariveda serves as both an engineering team and strategic advisor.”

Pariveda helped build a Suicide Intelligence Platform (SIP) to ingest various data sources to aid in predicting and preventing death by suicide of veterans and active duty military personnel. “We wanted to create a platform that brings in additional clinical data to enrich what’s already collected from Black Box Project,” says Daniel Clements, manager at Pariveda. "With SIP, we can help Stop Soldier Suicide produce unique insights into the causes and correlating factors of suicide in the veteran and service member population.” In addition to building the platform’s architecture, Pariveda led a multi-day workshop with Stop Soldier Suicide leaders to create the platform’s vision and find ways to bring data-driven clinical experience into practice through predictive data analysis.

The SIP solution ingests Black Box Project and health cloud data and stores it in Amazon Simple Storage Service (Amazon S3). The solution relies on AWS Glue to index data, with governance through AWS Lake Formation. Data enrichment and transformation between layers is managed via Apache Spark, using both AWS Lambda and AWS Glue. Stop Soldier Suicide data scientists interact with data from the platform by taking advantage of Amazon QuickSight dashboards for visualization and exploration, plus Amazon SageMaker studio notebooks for analytics and machine learning. “The other piece that’s fundamentally brought about by the architecture of this platform is the ability to enrich and transform data at great scale on AWS,” Clements says. The SIP platform went live in March 2024.

Outcome | Integrating and Enriching Data to Better Predict Suicide Risk

With the SIP solution, Stop Soldier Suicide can quickly ingest and enrich device data with health data and other contextual information. Ingestion takes place in minutes, and Stop Soldier Suicide can redact and cleanse millions of data points per device in hours. The organization can import this data from other relevant sources at the click of a button. Grimes says, “Through our work with AWS and Pariveda, we can now ingest, normalize, and redact device extractions on the fly, which, in turn, allows our data scientists and engineers to focus on working with the data as opposed to cleansing and prepping.”

With a broader repository of knowledge, Stop Soldier Suicide is increasing the quality and depth of its analysis of what contributes to the risk of suicide. For instance, the organization is conducting machine learning on the data, along with known suicide risk factors such as social isolation. “By analyzing things like frequency of contacts and conversations, we now have ways to objectively measure these risk factors,” says Grimes. This is helping the organization uncover new insights and make better predictions. “Through a focus on predicting acute levels of risk with the Pariveda and AWS platform, we can assist clinicians in applying the right resources at the right time to mitigate the risk of suicide,” Grimes says.

Stop Soldier Suicide is continuing its work with Pariveda, building on the foundation the two organizations have built together. Grimes says, “We anticipate having predictive models in the hands of clinicians in early 2025, which will be a major breakthrough for Black Box Project and the Suicide Intelligence Platform.”

About Stop Soldier Suicide

Stop Soldier Suicide is a veteran-founded and veteran-led nonprofit organization that focuses solely on solving the issue of suicide among US veterans and service members. The organization provides care and research specific to reducing veteran and service member suicide.

About AWS Partner Pariveda

Pariveda, an AWS Partner, is a leading management and technology consulting firm specializing in improving clients’ performance through strategic consulting and technology. The company’s cloud services include solution architecture, cloud application delivery, big data solutions, mobile/IoT, DevOps automation, data center transformation, and cloud advisory services.

AWS Services Used

Amazon S3

Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance.

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Amazon SageMaker

Amazon SageMaker is a fully managed service that brings together a broad set of tools to enable high-performance, low-cost machine learning (ML) for any use case.

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Amazon QuickSight

Amazon QuickSight powers data-driven organizations with unified business intelligence (BI) at hyperscale.

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AWS Glue

AWS Glue is a serverless data integration service that makes data preparation simpler, faster, and cheaper. 

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