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  1. Home > Articles & Issues >
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  3. Publishing Authentic ...
Conference paper

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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Publication details
Submitted on
June 20, 2018
Accepted on
June 20, 2018
Published on
June 20, 2018
Last modified on
March 31, 2025
Proceedings 1
Connecting the Knowledge Commons: From Projects to Sustainable Infrastructure
Short Papers
DOI
10.4000/proceedings.elpub.2018.15
License
Attribution 4.0 International (CC BY 4.0)
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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.
Keywords
  • [SHS.INFO]Humanities and Social Sciences/Library and information sciences
  • private health data
  • distributed ledgers
  • health data publication
Cited by

Source: OpenCitations

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

    Authors : Katie Seaborn ORCID, Norihisa P. Miyake ORCID, Peter Pennefather ORCID, Mihoko Otake-Matsuura ORCID

    Journal reference : Volume , 2020, pp.

    DOI : 10.2196/preprints.18778
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