Big data breaks the incarceration cycle
On an average day in the US, more than 700,000 people are confined in county and city jails. Over half of these inmates struggle with mental illness, substance abuse, chronic health issues, or some combination of the three. A number of them will return to jail at least once within three years of their release; some will return multiple times.
These highly vulnerable people cycle repeatedly through not just local jails but also emergency medical services, shelters, and other public systems, receiving fragmented care that delivers substandard outcomes at a great cost to the community.
In Johnson County, Kansas, as in many jurisdictions, mental health, EMS, and jail systems rarely share data. Lack of coordination between agencies makes it difficult to discern patterns that could predict future system contacts, meaning that individuals with complex needs often return to jail.
In 2016, Data Science for Social Good researchers from the University of Chicago identified individuals who had contact with multiple systems. They used this model to predict individual jail bookings.
The team of Erika Salomon, Matt Bauman, Kate Boxer, Tzu-Yun Lin, and Hareem Naveed connected with Johnson County through the Obama White House’s Data Driven Justice Initiative, taking earlier initiatives focused on frequent visitors to hospital emergency departments as a starting point.
“By connecting patients with more comprehensive and proactive care, many hospitals have been able to reduce readmissions and improve long-term outcomes,” says Bauman, data science fellow with the Center for Data Science and Public Policy. “We hope to do something similar for jail time.”
Johnson County is a suburban area near Kansas City with a population of nearly 600,000. In 2010, over 100,000 individuals had contact with emergency medical services. In the same year, 50,000 individuals were booked into the county jail.
Hoping to reduce that number, the team identified individuals at risk of going to jail but who would be better served by receiving mental health or other services.
“At-risk individuals with complex problems are less likely to have police encounters if they are connected to services,” says Robert Sullivan, criminal justice coordinator for Johnson County.
The team began by analyzing more than six years of individual-level historical data from the county’s criminal justice, mental health, and ambulance transport records.
