Driving reentry reform with quality real-time data and performance metrics.

The article focuses on enhancing reentry programs for formerly incarcerated individuals through the use of quality real-time data and performance metrics. It outlines five key support areas—housing, employment, education, healthcare, and social reintegration—and emphasizes the importance of data-dri...

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Detalles Bibliográficos
Publicado en:Corrections Today Vol. 88; no. 2; pp. 28 - 34
Autor principal: KAVALA, SRINIVASU
Formato: Artículo
Publicado: American Correctional Association Summer2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Summer2026
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      pub: American Correctional Association
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        atl: Driving reentry reform with quality real-time data and performance metrics.
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        au: KAVALA, SRINIVASU
      su:
        Recidivism
        Resource allocation
        Corrections (Criminal justice administration)
        Information sharing
        Key performance indicators (Management)
        Prediction models
        Real-time computing
      sug:
        subj:
          Recidivism
          Resource allocation
          Corrections (Criminal justice administration)
          Information sharing
          Federal correctional services
          Provincial correctional services
          Key performance indicators (Management)
          Prediction models
          Real-time computing
      ab: The article focuses on enhancing reentry programs for formerly incarcerated individuals through the use of quality real-time data and performance metrics. It outlines five key support areas—housing, employment, education, healthcare, and social reintegration—and emphasizes the importance of data-driven strategies to reduce recidivism, strengthen families, and support compliance with supervision conditions. The integration of digital case management systems and cross-agency data sharing improves coordination, accountability, and outcome measurement while safeguarding client privacy through secure technologies and ethical practices. Advanced analytics and predictive modeling are highlighted as future tools to tailor interventions, optimize resource allocation, and demonstrate cost-effectiveness to funders.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
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