Unpacking Ethical, Privacy, And Governance Risks in AI-IoT Based Healthcare Environments: A thematic analysis

Objective: The paper aimed to examine ethical, privacy, and governance challenges in AI-IoT (Artificial Intelligence-based Internet of Things) healthcare environments. Design: A total of 39 peer-reviewed open-access studies were screened and used for a systematic review using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. A multi-stage thematic analysis was used for identifying recurring patterns within the literature and answering the research questions. Results/outcomes: The identified challenges in the AI-IoT healthcare ecosystems, arising from the thematic analysis, are privacy and continuous surveillance, algorithmic bias and lack of explainability, limitations for informed consent, and fragmented governance and accountability. Conclusion: The findings, in sync with STS theory, indicate that challenges in AI-IoT healthcare systems cannot be addressed solely through technological innovations. In response, the study proposed an Integrated Human-Centric Trust Framework to integrate human intervention with technological advancements.

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Publication Details

Journal
Asia Pacific Journal of Health Management
Published
2026-10-28
DOI
https://doi.org/10.24083/apjhm.v21i2.5921
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Unpacking Ethical, Privacy, And Governance Risks in AI-IoT Based Healthcare Environments: A thematic analysis

B Mahalakshmi, Asmat Ara Shaikh, Pankaj Sahu, Joana Jaya et al.
1 links
Asia Pacific Journal of Health Management
Artificial Intelligence in Healthcare and Education
article

Unpacking Ethical, Privacy, And Governance Risks in AI-IoT Based Healthcare Environments: A thematic analysis

B Mahalakshmi, Asmat Ara Shaikh, Pankaj Sahu, Joana Jaya, Olina Jaya
article en

Abstract

Objective: The paper aimed to examine ethical, privacy, and governance challenges in AI-IoT (Artificial Intelligence-based Internet of Things) healthcare environments. Design: A total of 39 peer-reviewed open-access studies were screened and used for a systematic review using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. A multi-stage thematic analysis was used for identifying recurring patterns within the literature and answering the research questions. Results/outcomes: The identified challenges in the AI-IoT healthcare ecosystems, arising from the thematic analysis, are privacy and continuous surveillance, algorithmic bias and lack of explainability, limitations for informed consent, and fragmented governance and accountability. Conclusion: The findings, in sync with STS theory, indicate that challenges in AI-IoT healthcare systems cannot be addressed solely through technological innovations. In response, the study proposed an Integrated Human-Centric Trust Framework to integrate human intervention with technological advancements.

Asia Pacific Journal of Health Management
INTI International University (MY), COEP Technological University (IN), Dibrugarh University (IN)
Good health and well-being, Peace, justice, and strong institutions
Openalex Percentile: Top 20%
Artificial Intelligence in Healthcare and Education
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