{"id":{"repo_id":"toronto-retro","oai_identifier":"oai:utoronto.scholaris.ca:1807/125525"},"canonical_url":"https://search.dev.ndltd.org/etd/toronto-retro/oai:utoronto.scholaris.ca:1807/125525","repository":{"repo_id":"toronto-retro","name":"University of Toronto","base_url":"https://utoronto.scholaris.ca/server/oai/request"},"display":{"title":"Structural Limitations of Data Protection Legislation for the Learning Health System: Proposing a Lex Specialis for Longitudinal Biomedical Data Use","abstract":"Data protection legislation imposes presumptive limitations on the capacity of institutions to collect, use, and disclose personal information to safeguard individual interests such as informational self-determination and privacy. This legislation has shown itself ill-suited to the regulation of emergent data-driven activities in the health sector, including public health surveillance, biomedical research, and personalised medicine. These difficulties are accentuated in transnational and intersectoral efforts, due to the heightened legal compliance challenges that arise from the simultaneous application of multiple laws. To alleviate these difficulties, a novel legal paradigm of data stewardship is proposed. A model of longitudinal information stewardship in reliance on appropriate organisational structures, expert oversight, and technical safeguards is proposed as an alternative to data protection law. Such a model should be enacted through special purpose health-sector legislation to align individual privacy and the pro-social use of health-related personal information in the public interest.","abstract_html":"Data protection legislation imposes presumptive limitations on the capacity of institutions to collect, use, and disclose personal information to safeguard individual interests such as informational self-determination and privacy. This legislation has shown itself ill-suited to the regulation of emergent data-driven activities in the health sector, including public health surveillance, biomedical research, and personalised medicine. These difficulties are accentuated in transnational and intersectoral efforts, due to the heightened legal compliance challenges that arise from the simultaneous application of multiple laws. To alleviate these difficulties, a novel legal paradigm of data stewardship is proposed. A model of longitudinal information stewardship in reliance on appropriate organisational structures, expert oversight, and technical safeguards is proposed as an alternative to data protection law. Such a model should be enacted through special purpose health-sector legislation to align individual privacy and the pro-social use of health-related personal information in the public interest.","abstract_has_math":false,"creators":["Bernier, Alexander"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Law","school":null,"contributors":[],"advisors":["Austin, Lisa"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-11","date_published":"2021-11","updated_at":"2026-07-27T21:28:07Z","subjects":["Bioethics","Biomedical data commons","Data protection law","Data stewardship","Health policy","Personalised medicine"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1807/125525","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Austin, Lisa"]},{"key":"dc:contributor.department","label":"Department","values":["Law"]},{"key":"dc:creator","label":"Author","values":["Bernier, Alexander"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-11"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-11-11T18:32:48Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-11-11T18:32:48Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-11"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Bioethics","Biomedical data commons","Data protection law","Data stewardship","Health policy","Personalised medicine"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1807/125525"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Data protection legislation imposes presumptive limitations on the capacity of institutions to collect, use, and disclose personal information to safeguard individual interests such as informational self-determination and privacy. This legislation has shown itself ill-suited to the regulation of emergent data-driven activities in the health sector, including public health surveillance, biomedical research, and personalised medicine. These difficulties are accentuated in transnational and intersectoral efforts, due to the heightened legal compliance challenges that arise from the simultaneous application of multiple laws. To alleviate these difficulties, a novel legal paradigm of data stewardship is proposed. A model of longitudinal information stewardship in reliance on appropriate organisational structures, expert oversight, and technical safeguards is proposed as an alternative to data protection law. 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Such a model should be enacted through special purpose health-sector legislation to align individual privacy and the pro-social use of health-related personal information in the public interest."],"dc:description.degree":["LL.M."],"dc:identifier.uri":["http://hdl.handle.net/1807/125525"],"dc:subject":["Bioethics","Biomedical data commons","Data protection law","Data stewardship","Health policy","Personalised medicine"],"dc:title":["Structural Limitations of Data Protection Legislation for the Learning Health System: Proposing a Lex Specialis for Longitudinal Biomedical Data Use"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:28:07Z"}