SAS and Mindshare brighten outlook for children at risk

Combining analytics and child-welfare expertise will present caseworkers clearer picture of risk, improve outcomes

Analytics leaders SAS and Mindshare Technology are joining to provide social services a sharp view of the danger to a child, in near-real time. When overburdened child protection caseworkers can quickly gauge a child’s risk of abuse, they can better manage massive caseloads. And protect at-risk children.

Nearly 1,600 children died from abuse and neglect in the US in 2014, a rate that has been creeping upward in recent years. These children need more than protection – they need a stable living environment.

Mindshare has been operating a hosted and managed service for nearly 10 years, and is staffed by thought leaders and domain experts in child welfare data and outcomes improvement. Predictive models are applied to operational data daily to provide real-time decision supports for children in child welfare systems. Mindshare’s system helps child welfare advocates track more than 100,000 children for safety and risk factors, and it has proven to increase a child’s chance of meeting safety, well-being and permanency goals.

SAS has been in the predictive analytics business for 40 years, with models used across the world in all major industries, including a long history in public sector human services. With Mindshare joining the SAS Partner Program, the companies can harness deep domain expertise and proven analytics to provide nimble and timely analytics solutions to state and local child welfare agencies.

“Together, SAS and Mindshare will help departments tap data to determine root causes on the spot, recalculate risk patterns in minutes and detect dangerous behaviors,” said Greg Povolny, Mindshare founder and CEO. “When frontline staff can benefit from the power of analytics in an intuitive manner that caters to frontline needs, measurably improving outcomes becomes real-time and commonplace.”

Reports of child abuse or neglect pouring into social service agencies contain invaluable data for caseworkers. But adding in data from disparate sources, such as criminal justice and public health databases, reveals even more about children at highest risk of abuse or death. Such data might include 911 calls from the home, arrests of family members, new individuals in the home, increased school absences or new investigations.

“We ask so much of caseworkers,” said Will Jones, human services and child well-being expert at SAS. “Imagine if, when they come in each day, a dashboard feeds them the latest on each case and alerts them where risk of abuse has jumped. The humans will always make the decisions, but the system can put their limited time to the greatest good.”

Mindshare will integrate SAS^® Text Analytics to dig out new insights from text-based sources, such as worker and supervisor notes, which contain a wealth of case-relevant information. Also, as disparate data sources are integrated, SAS Data Quality will enable complex data cleansing, record linking, deduplication and entity resolution.

Caseworkers will gain a clearer picture of relationships between children and adults at different levels. Data scientists from the SAS Advanced Analytics Lab for State and Local Government have identified that the network of these relationships plays a critical role in identifying high-risk children. Through research in Florida and North Carolina, the lab discovered that the No. 1 predictor of future maltreatment, including fatality, is a child’s generational abuse history. That data is often missing or unclear in a caseworker’s file.

“SAS and Mindshare can provide new and more meaningful information to protect kids,” said Jones.

SAS offers a variety of analytics solutions to improve child well-being. Learn more about how data protects at-risk children.

About Mindshare Technology

Mindshare Technology is a Tampa, Florida based company and since 2004 has been researching and implementing new and improved methods to liberate the facts contained within data. Mindshare seamlessly interoperates with statewide and local systems to target relevant data to isolate key patterns, identify case file irregularities, and improve accountability at all levels. Mindshare’s data scientists are focused specifically on designing, developing and supporting operationalized predictive models for child welfare systems of care. Child designees are finally given proactive insight to inject improvements in case management practices at the right time, for the right reasons.