Interoperability

Hufnagel, Stephen P.

doi:10.7205/milmed-d-03-9808

Cited by 7 publications

(2 citation statements)

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“…AT 12 represents all the different facets of health records and disease management tools [ 86 - 89 ], which collect detailed health information, allowing them to offer functionality tailored to users’ needs and individual peculiarities or to provide other apps with the information required for tailoring offered functionality. Apps of AT 12 could rise to central hubs in the emerging mHealth environment if interoperability issues are solved [ 12 , 90 ] and information security and privacy is sufficiently addressed so that users can safely trust apps of AT 12 to protect their information [ 14 , 91 , 92 ].…”

Section: Discussionmentioning

confidence: 99%

Exploring the Far Side of Mobile Health: Information Security and Privacy of Mobile Health Apps on iOS and Android

Dehling¹,

Gao²,

Schneider³

et al. 2015

JMIR mHealth uHealth

224

159

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BackgroundMobile health (mHealth) apps aim at providing seamless access to tailored health information technology and have the potential to alleviate global health burdens. Yet, they bear risks to information security and privacy because users need to reveal private, sensitive medical information to redeem certain benefits. Due to the plethora and diversity of available mHealth apps, implications for information security and privacy are unclear and complex.ObjectiveThe objective of this study was to establish an overview of mHealth apps offered on iOS and Android with a special focus on potential damage to users through information security and privacy infringements.MethodsWe assessed apps available in English and offered in the categories “Medical” and “Health & Fitness” in the iOS and Android App Stores. Based on the information retrievable from the app stores, we established an overview of available mHealth apps, tagged apps to make offered information machine-readable, and clustered the discovered apps to identify and group similar apps. Subsequently, information security and privacy implications were assessed based on health specificity of information available to apps, potential damage through information leaks, potential damage through information manipulation, potential damage through information loss, and potential value of information to third parties.ResultsWe discovered 24,405 health-related apps (iOS; 21,953; Android; 2452). Absence or scarceness of ratings for 81.36% (17,860/21,953) of iOS and 76.14% (1867/2452) of Android apps indicates that less than a quarter of mHealth apps are in more or less widespread use. Clustering resulted in 245 distinct clusters, which were consolidated into 12 app archetypes grouping clusters with similar assessments of potential damage through information security and privacy infringements. There were 6426 apps that were excluded during clustering. The majority of apps (95.63%, 17,193/17,979; of apps) pose at least some potential damage through information security and privacy infringements. There were 11.67% (2098/17,979) of apps that scored the highest assessments of potential damages.ConclusionsVarious kinds of mHealth apps collect and offer critical, sensitive, private medical information, calling for a special focus on information security and privacy of mHealth apps. In order to foster user acceptance and trust, appropriate security measures and processes need to be devised and employed so that users can benefit from seamlessly accessible, tailored mHealth apps without exposing themselves to the serious repercussions of information security and privacy infringements.

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Section: Discussionmentioning

confidence: 99%

Exploring the Far Side of Mobile Health: Information Security and Privacy of Mobile Health Apps on iOS and Android

Dehling¹,

Gao²,

Schneider³

et al. 2015

JMIR mHealth uHealth

224

159

View full text Add to dashboard Cite

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“…Currently, there is a multitude of companies and government institutions whose task is to develop HISs, each of them implementing its own data model, which is specific to that system's functionality [ 4 ]. These data models differ from system to system and are always changing according to the changing requirements of the systems based on continuous scientific developments in medicine, government policies, and the standards of healthcare insurance companies [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Convergence of Health Level Seven Version 2 Messages to Semantic Web Technologies for Software-Intensive Systems in Telemedicine Trauma Care

2016

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ObjectivesTo present the technical background and the development of a procedure that enriches the semantics of Health Level Seven version 2 (HL7v2) messages for software-intensive systems in telemedicine trauma care.MethodsThis study followed a multilevel model-driven approach for the development of semantically interoperable health information systems. The Pre-Hospital Trauma Life Support (PHTLS) ABCDE protocol was adopted as the use case. A prototype application embedded the semantics into an HL7v2 message as an eXtensible Markup Language (XML) file, which was validated against an XML schema that defines constraints on a common reference model. This message was exchanged with a second prototype application, developed on the Mirth middleware, which was also used to parse and validate both the original and the hybrid messages.ResultsBoth versions of the data instance (one pure XML, one embedded in the HL7v2 message) were equally validated and the RDF-based semantics recovered by the receiving side of the prototype from the shared XML schema.ConclusionsThis study demonstrated the semantic enrichment of HL7v2 messages for intensive-software telemedicine systems for trauma care, by validating components of extracts generated in various computing environments. The adoption of the method proposed in this study ensures the compliance of the HL7v2 standard in Semantic Web technologies.

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