Engineering Privacy for Mobile Health Data Collection Systems in the Primary Care

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Engineering Privacy for Mobile Health Data Collection Systems in the Primary Care

Iwaya, Leonardo H (författare): Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013),Privacy and Security

Fischer-Hübner, Simone (preses): Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)

Åhlfeldt, Rose-Mharie (preses): University of Skövde

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Martucci, Leonardo (preses): Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)

Andersen, Anders, Professor (opponent): University of Tromsø - The Arctic University of Norway

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ISBN 9789170639005
Karlstad : Karlstads universitet, 2019
Engelska 55 s.

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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)

Abstract Ämnesord

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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.

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.

Ämnesord

NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)

Nyckelord

Privacy
data protection
information security
mobile health
community-based primary care
privacy impact assessment
consent management
anonymisation
Computer Science
Datavetenskap

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