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Åhlfeldt, Rose-Mharie
Publications (4 of 4) Show all publications
Iwaya, L. H., Li, J., Fischer-Hübner, S., Åhlfeldt, R.-M. & Martucci, L. (2019). E-Consent for Data Privacy: Consent Management for Mobile Health Technologies in Public Health Surveys and Disease Surveillance. In: Lucila Ohno-Machado, Brigitte Séroussi (Ed.), MEDINFO 2019: Health and Wellbeing e-Networks for All. Paper presented at MEDINFO 2019, the 17th World Congress on Medical and Health Informatics, Lyon, France, 25-30 August 2019 (pp. 1224-1227). IOS Press, 264
Open this publication in new window or tab >>E-Consent for Data Privacy: Consent Management for Mobile Health Technologies in Public Health Surveys and Disease Surveillance
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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
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365
Keywords
mobile health, privacy, public health surveillance
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-70211 (URN)10.3233/SHTI190421 (DOI)978-1-64368-002-6 (ISBN)978-1-64368-003-3 (ISBN)
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
Iwaya, L. H., Fischer-Hübner, S., Åhlfeldt, R.-M. & Martucci, L. (2019). Mobile Health Systems for Community-Based Primary Care: Identifying Controls and Mitigating Privacy Threats. JMIR mhealth and uhealth, 7(3), 1-16, Article ID e11642.
Open this publication in new window or tab >>Mobile Health Systems for Community-Based Primary Care: Identifying Controls and Mitigating Privacy Threats
2019 (English)In: JMIR mhealth and uhealth, E-ISSN 2291-5222, Vol. 7, no 3, p. 1-16, article id e11642Article in journal (Refereed) Published
Abstract [en]

Background: Community-based primary care focuses on health promotion, awareness raising, and illnesses treatment and prevention in individuals, groups, and communities. Community Health Workers (CHWs) are the leading actors in such programs, helping to bridge the gap between the population and the health system. Many mobile health (mHealth) initiatives have been undertaken to empower CHWs and improve the data collection process in the primary care, replacing archaic paper-based approaches. A special category of mHealth apps, known as mHealth Data Collection Systems (MDCSs), is often used for such tasks. These systems process highly sensitive personal health data of entire communities so that a careful consideration about privacy is paramount for any successful deployment. However, the mHealth literature still lacks methodologically rigorous analyses for privacy and data protection.

Objective: In this paper, a Privacy Impact Assessment (PIA) for MDCSs is presented, providing a systematic identification and evaluation of potential privacy risks, particularly emphasizing controls and mitigation strategies to handle negative privacy impacts.

Methods: The privacy analysis follows a systematic methodology for PIAs. As a case study, we adopt the GeoHealth system, a large-scale MDCS used by CHWs in the Family Health Strategy, the Brazilian program for delivering community-based primary care. All the PIA steps were taken on the basis of discussions among the researchers (privacy and security experts). The identification of threats and controls was decided particularly on the basis of literature reviews and working group meetings among the group. Moreover, we also received feedback from specialists in primary care and software developers of other similar MDCSs in Brazil.

Results: The GeoHealth PIA is based on 8 Privacy Principles and 26 Privacy Targets derived from the European General Data Protection Regulation. Associated with that, 22 threat groups with a total of 97 subthreats and 41 recommended controls were identified. Among the main findings, we observed that privacy principles can be enhanced on existing MDCSs with controls for managing consent, transparency, intervenability, and data minimization.

Conclusions: Although there has been significant research that deals with data security issues, attention to privacy in its multiple dimensions is still lacking for MDCSs in general. New systems have the opportunity to incorporate privacy and data protection by design. Existing systems will have to address their privacy issues to comply with new and upcoming data protection regulations. However, further research is still needed to identify feasible and cost-effective solutions.

Place, publisher, year, edition, pages
JMIR Publications, 2019
Keywords
Mobile health, mHealth, information security, information privacy, data protection, privacy impact assessment, community-based primary care, family health strategy
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-70212 (URN)10.2196/11642 (DOI)2-s2.0-85067895402 (Scopus ID)
Available from: 2018-11-21 Created: 2018-11-21 Last updated: 2019-07-10Bibliographically approved
Iwaya, L. H., Fischer-Hübner, S., Åhlfeldt, R.-M. & Martucci, L. (2018). mHealth: A Privacy Threat Analysis for Public Health Surveillance Systems. In: Bridget Kane (Ed.), 2018 IEEE 31st International Symposium on Computer-Based Medical Systems: . Paper presented at Proceedings of 31st IEEE Symposium on Computer-Based Medical Systems (CBMS 2018). Karlstad, Sweden: IEEE
Open this publication in new window or tab >>mHealth: A Privacy Threat Analysis for Public Health Surveillance Systems
2018 (English)In: 2018 IEEE 31st International Symposium on Computer-Based Medical Systems / [ed] Bridget Kane, Karlstad, Sweden: IEEE, 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, 2018
Series
IEEE International Symposium on Computer-Based Medical Systems, E-ISSN 2372-9198
Keywords
Privacy, Data privacy, Security, Surveillance, Data collection, Public healthcare
National Category
Computer Sciences
Research subject
Computer Science; Information Systems
Identifiers
urn:nbn:se:kau:diva-68003 (URN)10.1109/CBMS.2018.00015 (DOI)978-1-5386-6060-7 (ISBN)978-1-5386-6061-4 (ISBN)
Conference
Proceedings of 31st IEEE Symposium on Computer-Based Medical Systems (CBMS 2018)
Available from: 2018-07-11 Created: 2018-07-11 Last updated: 2019-11-10Bibliographically approved
Iwaya, L. H., Fischer-Hübner, S., Åhlfeldt, R.-M. & Martucci, L. (2018). Overview of Privacy Challenges in Mobile Health Data Collection Systems. In: : . Paper presented at Medical Informatics Europe: MIE 2018, Gothenburg, Sweden, 24-26 April, 2018..
Open this publication in new window or tab >>Overview of Privacy Challenges in Mobile Health Data Collection Systems
2018 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Community Health Workers (CHWs) have been using Mobile HealthData Collection Systems (MDCSs) for public health surveys, feeding the national-level databases with the families’ personal data. Since such systems are inherentlyused for public surveillance and manage sensitive data (i.e., health data), deal-ing with the privacy issues is crucial to successful deployments. In this poster wepresent the privacy challenges related to MDCSs, providing a summary speciallyimportant to health managers and developers.

Keywords
mobile health, privacy, security, mHealth data collection system
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-70414 (URN)
Conference
Medical Informatics Europe: MIE 2018, Gothenburg, Sweden, 24-26 April, 2018.
Available from: 2018-12-05 Created: 2018-12-05 Last updated: 2019-09-11Bibliographically approved

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