Security, privacy, and healthcare-related conversational agents: a scoping review

May, Richard; Denecke, Kerstin (2021). Security, privacy, and healthcare-related conversational agents: a scoping review Informatics for Health and Social Care, 47(2), pp. 194-210. Taylor & Francis 10.1080/17538157.2021.1983578

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Health chatbots interview patients and collect health data. This process makes demands on data security and data privacy. To identify how and to what extent security and privacy are considered in current health chatbots. We conducted a scoping review by searching three bibliographic databases (PubMed, ACM Digital Library, IEEExplore) for papers reporting on chatbots in healthcare. We extracted which, how, and where data is stored by health chatbots and identified which external services have access to the data. Out of 1026 retrieved papers, we included 70 studies in the qualitative synthesis. Most papers report on chatbots that collect and process personal health data, usually in the context of mental health coaching applications. The majority did not provide any information regarding security or privacy aspects. We were able to determine limitations in literature and identified concrete challenges, including data access and usage of (third-party) services, data storage, data security methods, use case peculiarities and data privacy, as well as legal requirements. Data privacy and security in health chatbots are still underresearched and related information is underrepresented in scientific literature. By addressing the five key challenges in future, the transfer of theoretical solutions into practice can be facilitated.

Item Type:

Journal Article (Original Article)

Division/Institute:

School of Engineering and Computer Science > Institute for Patient-centered Digital Health
School of Engineering and Computer Science

Name:

May, Richard and
Denecke, Kerstin0000-0001-6691-396X

Subjects:

Q Science > Q Science (General)
T Technology > T Technology (General)

ISSN:

1753-8165

Publisher:

Taylor & Francis

Language:

English

Submitter:

Kerstin Denecke

Date Deposited:

12 Nov 2021 11:34

Last Modified:

25 Oct 2023 13:56

Publisher DOI:

10.1080/17538157.2021.1983578

URI:

https://arbor.bfh.ch/id/eprint/15649

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