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mHealth: A Privacy Threat Analysis for Public Health Surveillance Systems
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
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
School of Informatics, University of Skövde, Skövde, Sweden.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-9980-3473
2018 (English)In: 2018 IEEE 31st International Symposium on Computer-Based Medical Systems / [ed] Bridget Kane, Karlstad, Sweden: IEEE conference proceedings, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Community Health Workers (CHWs) have been using Mobile Health Data Collection Systems (MDCSs) for supporting the delivery of primary healthcare and carrying out public health surveys, feeding national-level databases with families’ personal data. Such systems are used for public surveillance and to manage sensitive data (i.e., health data), so addressing the privacy issues is crucial for successfully deploying MDCSs. In this paper we present a comprehensive privacy threat analysis for MDCSs, discuss the privacy challenges and provide recommendations that are specially useful to health managers and developers. We ground our analysis on a large-scale MDCS used for primary care (GeoHealth) and a well-known Privacy Impact Assessment (PIA) methodology. The threat analysis is based on a compilation of relevant privacy threats from the literature as well as brain-storming sessions with privacy and security experts. Among the main findings, we observe that existing MDCSs do not employ adequate controls for achieving transparency and interveinability. Thus, threatening fundamental privacy principles regarded as data quality, right to access and right to object. Furthermore, it is noticeable that although there has been significant research to deal with data security issues, the attention with privacy in its multiple dimensions is prominently lacking.

Place, publisher, year, edition, pages
Karlstad, Sweden: IEEE conference proceedings, 2018.
Keywords [en]
Privacy, Data privacy, Security, Surveillance, Data collection, Public healthcare
National Category
Computer Sciences
Research subject
Computer Science; Information Systems
Identifiers
URN: urn:nbn:se:kau:diva-68003DOI: 10.1109/CBMS.2018.00015ISBN: 978-1-5386-6060-7 (electronic)ISBN: 978-1-5386-6061-4 (print)OAI: oai:DiVA.org:kau-68003DiVA, id: diva2:1232367
Conference
Proceedings of 31st IEEE Symposium on Computer-Based Medical Systems (CBMS 2018)
Available from: 2018-07-11 Created: 2018-07-11 Last updated: 2018-12-06Bibliographically 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: 2019-01-08Bibliographically approved

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Iwaya, Leonardo H.Fischer-Hübner, SimoneÅhlfeldt, Rose-MharieMartucci, Leonardo
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