Using administrative data from adult protective services: opportunities and considerations.

As federal agencies support the development of data systems for adult protective services (APS), researchers and practitioners are increasingly using administrative data to study types of adult maltreatment, including self-neglect, and the systems that respond to them. To date, however, APS has work...

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Publicado en:Journal of Elder Abuse & Neglect Vol. 34; no. 1; pp. 77 - 93
Autores principales: Steinman, Kenneth J., Liu, Pi-Ju, Anetzberger, Georgia, Pettey Rockwood, Alyssa, Teferra, Andreas, Ejaz, Farida Kassim
Formato: Journal Article
Publicado: Taylor & Francis Ltd Jan/Feb 2022
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Taylor & Francis Ltd
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        atl: Using administrative data from adult protective services: opportunities and considerations.
      aug:
        au:
          Steinman, Kenneth J.
          Liu, Pi-Ju
          Anetzberger, Georgia
          Pettey Rockwood, Alyssa
          Teferra, Andreas
          Ejaz, Farida Kassim
        affil: College of Education and Human Ecology, The Ohio State University, Columbus, Ohio USA
      sug:
        subj:
          Elder Abuse Prevention and Control
          Resource Databases
          Data Management
          Database Management Software
          Quality Assessment
          Quality Assurance
          Self Neglect
      ab: As federal agencies support the development of data systems for adult protective services (APS), researchers and practitioners are increasingly using administrative data to study types of adult maltreatment, including self-neglect, and the systems that respond to them. To date, however, APS has worked with little guidance about how best to use these data. This situation has contributed to inconsistent findings and uneven quality of research. Based on the authors' experience in multiple states and using examples from research and practice, this paper reviews practical considerations related to organizing and analyzing APS administrative data. We address concerns related to time-limited, erroneous, and missing data, as well as defining metrics and accounting for the multilevel structure of data with repeated observations. Reviewing these methodological details can help APS practitioners strengthen quality assurance processes and improve research in this important area.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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