The legal and ethical dimensions of artificial intelligence in managing medical records in Oman

Abstract This research investigates the legal and ethical implications surrounding the application and management of artificial intelligence (AI) in healthcare record management in Oman, particularly analyzing the role of such aspects for building healthcare professionals’ trust on such AI-based systems. Using international regulations (GDPR, WHO, EU HLEG) and national legislation (Personal Data Protection Law, Royal Decree 6/2022, Executive Regulation 34/2024), the research is quantitatively descriptive. A validated questionnaire was used to collect the data from 309 healthcare professionals in public as well as private healthcare organizations in Oman. The four-factor measurement model consisted of constructs of privacy/data protection, legal framework/accountability, ethical safeguards, and trust in AI. The confirmatory factor analysis confirmed that the four-factor model had a good fit, and the structural equation model analysis explained the determinants of trust. The findings indicate that perceived privacy and data protection were most strongly associated with healthcare professionals’ trust in AI-assisted medical records. Ethical safeguards were also positively associated with trust. By contrast, the perceived legal framework and accountability dimension was negatively associated with trust, suggesting that healthcare professionals may view current legal arrangements as unclear or insufficiently reassuring regarding liability, redress, and accountability. Given the cross-sectional survey design, these results should be interpreted as associations between perceptions rather than causal effects. The study suggests that privacy-by-design practices, clearer accountability procedures, and visible ethical governance may support more trustworthy implementation of AI-enabled medical record systems in Oman.

Authors

Institutions

Publication Details

Journal
Discover Artificial Intelligence
Published
2026-08-24
DOI
https://doi.org/10.1007/s44163-026-01884-y
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The legal and ethical dimensions of artificial intelligence in managing medical records in Oman

Abderrazak Mkadmi, Faten Hamad, Naifa Bait Bin Saleem
Discover Artificial Intelligence
Artificial Intelligence in Healthcare and Education
article

The legal and ethical dimensions of artificial intelligence in managing medical records in Oman

Abderrazak Mkadmi, Faten Hamad, Naifa Bait Bin Saleem
article en

Abstract

Abstract This research investigates the legal and ethical implications surrounding the application and management of artificial intelligence (AI) in healthcare record management in Oman, particularly analyzing the role of such aspects for building healthcare professionals’ trust on such AI-based systems. Using international regulations (GDPR, WHO, EU HLEG) and national legislation (Personal Data Protection Law, Royal Decree 6/2022, Executive Regulation 34/2024), the research is quantitatively descriptive. A validated questionnaire was used to collect the data from 309 healthcare professionals in public as well as private healthcare organizations in Oman. The four-factor measurement model consisted of constructs of privacy/data protection, legal framework/accountability, ethical safeguards, and trust in AI. The confirmatory factor analysis confirmed that the four-factor model had a good fit, and the structural equation model analysis explained the determinants of trust. The findings indicate that perceived privacy and data protection were most strongly associated with healthcare professionals’ trust in AI-assisted medical records. Ethical safeguards were also positively associated with trust. By contrast, the perceived legal framework and accountability dimension was negatively associated with trust, suggesting that healthcare professionals may view current legal arrangements as unclear or insufficiently reassuring regarding liability, redress, and accountability. Given the cross-sectional survey design, these results should be interpreted as associations between perceptions rather than causal effects. The study suggests that privacy-by-design practices, clearer accountability procedures, and visible ethical governance may support more trustworthy implementation of AI-enabled medical record systems in Oman.

Discover Artificial IntelligenceVol. 6(1)
University of Jordan (JO), Sultan Qaboos University (OM)
Openalex Percentile: Top 13%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.