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Communication dans un congrès

Publishing Authentic, Private, Personal Data About Service Quality of Healthcare for Pain

Peter Pennefather (1), West Suhanic (2), Fatima Lakha (2), Deborah Fels (2)
(1) Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Canada; 9Department of Biochemistry, Faculty of Medicine, University of Toronto
(2) University of Toronto
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Détails de publication
Soumis le
June 20, 2018
Accepté le
June 20, 2018
Publié le
June 20, 2018
Modifié le
March 31, 2025
Acte de conférence 1
Connecting the Knowledge Commons: From Projects to Sustainable Infrastructure
Short Papers
DOI
10.4000/proceedings.elpub.2018.15
Licence
Attribution 4.0 International (CC BY 4.0)
Indicateurs
308
Vues
288
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Publishing Authentic, Private, Personal Data About Service Quality of Healthcare for Pain

Peter Pennefather (1), West Suhanic (2), Fatima Lakha (2), Deborah Fels (2)
(1) Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Canada; 9Department of Biochemistry, Faculty of Medicine, University of Toronto
(2) University of Toronto
Abstract
An inclusive systemic design is specified for publishing data derived from personal private health records, owned and curated by patients. The design is specified with an example of a digital scrapbook of private personal records of care for medically significant pain. This scrapbook is designed to aggregate private records of patient pain experiences and of the care and accommodations they access. The design also specifies how to store, access and analyze those private records through distributed ledgers and how qualitative and quantitative data derived from that private data can be published as a common pool resource with polycentric governance.
Mots-clés
français
  • [SHS.INFO]Humanities and Social Sciences/Library and information sciences
anglais
  • private health data
  • distributed ledgers
  • health data publication
Cité par

Source : OpenCitations

  • Socially Embodied AI: A Framework for Recognizing the Dynamic Sociality of Artificial Agents Within and Beyond Healthcare (Preprint)

    Auteurs/Autrices : Katie Seaborn ORCID, Norihisa P. Miyake ORCID, Peter Pennefather ORCID, Mihoko Otake-Matsuura ORCID

    Référence de la revue : Volume , 2020, pp.

    DOI : 10.2196/preprints.18778
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