A Technology Approach to Improving Outcomes

About MindShare

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 has deployed and currently supports the first and only operationalized, child welfare focused, predictive models for daily use.

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 system is currently tracking over 100,000 children daily for safety and risk factors.

Mindshare’s modular data technology platform utilizes machine learning to enhance the visibility of data contained within the state managed  and provider information databases. Mindshare has demonstrated that children in foster care can experience enhanced safety and accelerated episodes in foster care with a reduced chance of reentering through its focus on operationalizing predictive models through its ICARE system. The Mindshare ICARE Predictive Analytical Module equips social workers to isolate the most vulnerable children based on a comprehensive understanding of the risks associated with maltreatment and poor outcomes, and has them refocus attention and priorities on the specific symptoms causing those risks.

Florida leaders, including former Florida Department of Children and Families Secretary, George H Sheldon and former Detective of Florida Department Law Enforcement, Dr. James D. Sewell, identified the use of Mindshare as an “outstanding application for better analytical and case management for child welfare data.”

Historically, business intelligence and program reporting focused solely on the past – on what has already occurred. Mindshare’s critical differentiator is its focus on forward looking analysis and the unique ability of its ICARE modular platform to surface potentially harmful issues that pose substantial and future risks to an individual child. The use of predictive analytics for the child welfare population, while still in its infancy relative to other human service populations, is continuing to be discussed and redefined. Often confused with standard business intelligence, predictive analytics represents an evolution from business intelligence in that it is more than mere statistical analysis, and is centered instead in data science that envelopes a process that is applied to refined sets of data. The Mindshare predictive analytical models are the result of three years of daily application to groups of individual children with remarkable positive results.

Child designees are finally given proactive insight to inject improvements in case management practices at the right time, for the right reasons.

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