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E-Consent for Data Privacy: Consent Management for Mobile Health Technologies in Public Health Surveys and Disease Surveillance
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Privacy and Security)ORCID iD: 0000-0001-9005-0543
Health and Biosecurity, Commonwealth Scientific and Industrial Research Organization, Australia.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Privacy and Security)ORCID iD: 0000-0002-6938-4466
University of Skövde.
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2019 (English)In: MEDINFO 2019: Health and Wellbeing e-Networks for All / [ed] Lucila Ohno-Machado, Brigitte Séroussi, IOS Press, 2019, Vol. 264, p. 1224-1227Conference paper, Published paper (Refereed)
Abstract [en]

Community health workers in primary care programs increasingly use Mobile Health Data Collection Systems (MDCSs) to report their activities and conduct health surveys, replacing paper-based approaches. The mHealth systems are inherently privacy invasive, thus informing individuals and obtaining their consent is important to protect their right to privacy. In this paper, we introduce an e-Consent tool tailored for MDCSs. It is developed based on the requirement analysis of consent management for data privacy and built upon the solutions of Participant-Centered Consent toolkit and Consent Receipt specification. The e-Consent solution has been evaluated in a usability study. The study results show that the design is useful for informing individuals on the nature of data processing, privacy and protection and allowing them to make informed decisions

Place, publisher, year, edition, pages
IOS Press, 2019. Vol. 264, p. 1224-1227
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365
Keywords [en]
mobile health, privacy, public health surveillance
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-70211DOI: 10.3233/SHTI190421ISBN: 978-1-64368-002-6 (print)ISBN: 978-1-64368-003-3 (electronic)OAI: oai:DiVA.org:kau-70211DiVA, id: diva2:1264726
Conference
MEDINFO 2019, the 17th World Congress on Medical and Health Informatics, Lyon, France, 25-30 August 2019
Available from: 2018-11-21 Created: 2018-11-21 Last updated: 2019-10-28Bibliographically approved
In thesis
1. Engineering Privacy for Mobile Health Data Collection Systems in the Primary Care
Open this publication in new window or tab >>Engineering Privacy for Mobile Health Data Collection Systems in the Primary Care
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Mobile health (mHealth) systems empower Community Health Workers (CHWs) around the world, by supporting the provisioning of Community-Based Primary Health Care (CBPHC) – primary care outside the health facility into people’s homes. In particular, Mobile Health Data Collection Systems (MDCSs) are used by CHWs to collect health-related data about the families that they treat, replacing paper-based approaches for health surveys. Although MDCSs significantly improve the overall efficiency of CBPHC, existing and proposed solutions lack adequate privacy and security safeguards. In order to bridge this knowledge gap between the research areas of mHealth and privacy, the main research question of this thesis is: How to design secure and privacy-preserving systems for Mobile Health Data Collection Systems? To answer this question, the Design Method is chosen as an engineering approach to analyse and design privacy and security mechanisms for MDCSs. Among the main contributions, a comprehensive literature review of the Brazilian mHealth ecosystem is presented. This review led us to focus on MDCSs due to their impact on Brazil’s CBPHC, the Family Health Strategy programme. On the privacy engineering side, the contributions are a Privacy Impact Assessment (PIA) for the GeoHealth MDCS and three mechanisms: (a) SecourHealth, a security framework for data encryption and user authentication; (b) an Ontology-based Data Sharing System (O-DSS) that provides obfuscation and anonymisation functions; and, (c) an electronic consent (e-Consent) tool for obtaining and handling informed consent. Additionally, practical experience is shared about designing a MDCS, GeoHealth, and deploying it in a large-scale experimental study. In conclusion, the contributions of this thesis offer guidance to mHealth practitioners, encouraging them to adopt the principles of privacy by design and by default in their projects.

Abstract [en]

Mobile health (mHealth) systems empower Community Health Workers (CHWs) around the world, by supporting the provisioning of Community-Based Primary Health Care (CBPHC). In particular, Mobile Health Data Collection Systems (MDCSs) are used by CHWs to collect health-related data about the families that they treat, replacing paper-based approaches. Although MDCSs improve the efficiency of CBPHC, existing solutions lack adequate privacy and security safeguards.

To bridge this knowledge gap between the research areas of mHealth and privacy, we start by asking: How to design secure and privacy-preserving systems for Mobile Health Data Collection Systems? To answer this question, an engineering approach is chosen to analyse and design privacy and security mechanisms for MDCSs.

Among the main contributions, a comprehensive literature review of the Brazilian mHealth ecosystem is presented. On the privacy engineering side, the contributions are a Privacy Impact Assessment (PIA) for the GeoHealth MDCS and three mechanisms: SecourHealth, a security framework for data encryption and user authentication; an Ontology-based Data Sharing System (O-DSS) that provides obfuscation and anonymisation functions; and, an electronic consent (e-Consent) tool for obtaining and handling informed consent.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2019. p. 55
Series
Karlstad University Studies, ISSN 1403-8099 ; 2019:1
Keywords
Privacy, data protection, information security, mobile health, community-based primary care, privacy impact assessment, consent management, anonymisation
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-70216 (URN)978-91-7063-900-5 (ISBN)978-91-7063-995-1 (ISBN)
Public defence
2019-01-31, 1A305, Lagerlöfsalen, Karlstad, 10:00 (English)
Opponent
Supervisors
Available from: 2019-01-08 Created: 2018-11-27 Last updated: 2019-09-19Bibliographically approved

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Iwaya, Leonardo HFischer-Hübner, SimoneÅhlfeldt, Rose-MharieMartucci, Leonardo

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