Data-Driven Justice

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    Data-Driven Justice

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    Every year, about 11 million people move through America’s 3,100 local jails, many on low-level, non-violent misdemeanors. Many of the people in county and other local jails have behavioral health conditions that impact their quality of life, including mental illnesses and substance use disorders. Left untreated, these conditions can contribute to homelessness and difficulty with maintaining a steady, sufficient income, which also makes accessing services and getting treatment challenging. Furthermore, the physical health of individuals in jails is often poor, including significantly higher rates of chronic conditions such as hypertension, diabetes and asthma than the general population. 

    Some individuals with behavioral and physical health conditions frequently cycle through jails, homeless shelters, emergency rooms and other crisis services. These individuals are often called frequent utilizers. Many places around the country have anecdotes about individuals who are well known to the police or emergency room doctors. Despite the multiple interventions and services that are used in response to frequent utilizers' conditions, fragmented care and a lack of coordination across justice, health and human services systems leads to unhealthy outcomes. Moreover, without alternatives to jails or emergency rooms, police and other first responders have few options for diverting frequent utilizers in crisis to treatment and services.

    Focusing efforts on frequent utilizers represent an opportunity for targeted, resource-saving interventions that can improve their health and well-being.

    The Data-Driven Justice (DDJ) initiative brings communities together to disrupt the cycle of incarceration and crisis. Communities participating in the initiative develop strategies that promote better outcomes for frequent utilizers by aligning justice, health and human services systems around data. These communities have committed to creating or expanding real-time or near real-time local data exchanges that combine justice, health and/or other system data to identify frequent utilizers of multiple systems. In addition, DDJ communities are identifying the ways and options for diverting frequent utilizers from the justice system to community-based services and treatment providers.

    Find Resources

    • Building Community Support
    • Diverting to What
    • Funding and Sustainability
    • Identifying High Utilizers
    • Case Studies
    • Using and Sharing Data
    • Events, Webinars and Call Logs
    • All Resources

    The Network of DDJ County, Cities and States

    • Acton, MA
    • Albany County, NY
    • Albany, NY
    • Allegany County, MD
    • Allegheny County, PA
    • Anderson County, SC
    • Anne Arundel County, MD
    • Arapahoe County, CO
    • Arlington, MA
    • Ashland, MA
    • Baltimore City, MD
    • Bedford, MA
    • Berks County, PA
    • Bernalillo County, NM
    • Bexar County, TX
    • Billerica, MA
    • Birmingham, AL
    • Black Hawk County, IA
    • Boone County, MO
    • Boulder County, CO
    • Boxborough, MA
    • Burlington, MA
    • Cambridge, MA
    • Camden County, NJ
    • Carlisle, MA
    • Champaign County, IL
    • Charleston County, SC
    • Chelmsford, MA
    • Chester County, PA
    • Clark County, NV
    • Coconino County, AZ
    • Codington County, SD
    • Colorado
    • Concord, MA
    • Connecticut
    • Cook County, IL
    • Cuyahoga County, OH
    • Dakota County, MN
    • Dallas County, TX
    • Dane County, WI
    • Delaware
    • Denver City and County, CO
    • Detroit, MI
    • Doña Ana County, NM
    • Douglas County, KS
    • Douglas County, NE
    • Dracut, MA
    • Dunn County, WI
    • DuPage County, IL
    • Dutchess County, NY
    • Eau Claire County, WI
    • El Paso County, TX
    • Everett, WA
    • Fairfax County, VA
    • Flagstaff, AZ
    • Franklin County, OH
    • Franklin County, PA
    • Fulton County, GA
    • Groton, MA
    • Harris County, TX
    • Harrisonburg, VA
    • Hartford, CT
    • Hennepin County, MN
    • Hood River County, OR
    • Hudson County, NJ
    • Hudson, MA
    • Illinois
    • Indianapolis and Marion County, IN
    • Jefferson County, CO
    • Johnson County, IA
    • Johnson County, KS
    • Kentucky
    • King County, WA
    • Knoxville, TN
    • Lafayette Parish, LA
    • LaGrange, GA
    • Lake County, IL
    • Lane County, OR
    • Lehigh County, PA
    • Leon County, FL
    • Long Beach, CA
    • Los Angeles County, CA
    • Los Angeles, CA
    • Louisville-Jefferson County Metro Government, KY
    • Lowell, MA
    • Lucas County, OH
    • Lynn, MA
    • Marathon County, WI
    • Marion County, OR
    • Marlborough, MA
    • Maryland
    • McLean County, IL
    • Mecklenburg County, NC
    • Mercer County, PA
    • Miami-Dade County, FL
    • Middlesex County, MA
    • Milwaukee County, WI
    • Minnehaha County, SD
    • Montgomery County, AL
    • Montgomery County, MD
    • Multnomah County, OR
    • New Orleans Parish, LA
    • New York City, NY
    • North Reading, MA
    • Northampton County, PA
    • Oakland, CA
    • Oregon
    • Pennington County, SD
    • Pennsylvania
    • Philadelphia County, PA
    • Pima County, AZ
    • Pinellas County, FL
    • Polk County, IA
    • Portland, ME
    • Potter County, PA
    • Prince George's County, MD
    • Pulaski County, AR
    • Ramsey County, MN
    • Reading, MA
    • Rhode Island
    • Rio Arriba County, NM
    • Rockingham County, VA
    • Roseau County, MN
    • Sacramento, CA
    • Salt Lake City, UT
    • Salt Lake County, UT
    • San Diego County, CA
    • San Francisco City & County, CA
    • Santa Clara County, CA
    • Santa Cruz County, CA
    • Shelby County, OH
    • Shelby County, TN
    • Snohomish County, WA
    • Somerville, MA
    • Suffolk County, City of Boston, MA
    • Suffolk County, NY
    • Tewksbury, MA
    • Townsend, MA
    • Travis County, TX
    • Troup County, GA
    • Utah
    • Wake County, NC
    • Wakefield, MA
    • Walla Walla County, WA
    • Washington, DC
    • Watertown, MA
    • Wayne County, MI
    • Winchester, MA
    • Winona County, MN
    • Yavapai County, AZ
    • Clinton County, IA
    The Data-Driven Justice initiative represents a growing network of counties that are reducing incarceration by developing strategies to identify frequent users of jails, hospitals, homeless shelters and other crisis and emergency services and divert them to effective, community-based treatment and care.
    2016-10-21
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    2020-09-23

Join the Initiative!

If your county or city is interested in participating in the initiative, please submit a letter committing to support the development of a smarter, more data-driven criminal justice system to cresing@naco.org. A sample letter can be found here.

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