ArticleBMC medical informatics and decision making2026
Ethical, legal, and social issues of AI use in emergency healthcare: a scoping review.
Article in BMC medical informatics and decision making, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Artificial Intelligence in Emergency Medical Call-Taking and Dispatch Operations: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundAdvances in artificial intelligence (AI) systems suggest that they can be used to improve healthcare outcomes via diagnosis, prognostication, patient management, risk assessment, etc. AI systems could be particularly useful in emergency healthcare (EHC) by synthesizing data to generate accurate conclusions rapidly. But the use of AI in EHC raises ethical, legal, and social concerns.
objectiveThe present study undertakes a scoping review to collate, map, and synthesize existing literature on the ethical, legal and social issues (ELSIs) associated with AI in EHC. The aim was to assess which ELSI issues were recognized and analyzed in the current literature and which were under-explored. DESIGN/
methodsOnline databases were used to identify papers published on the identified topic. An initial search strategy of IEEE, Pubmed, and Scopus yielded 156 unique records; 40 records underwent textual review, after which another 7 were excluded due to scope. The final 33 were analysed for content.
resultsOverall, the literature was mostly positive towards AI applications on EHC, with key themes aligning with the general AI ethics literature: transparency, bias, benefit/harm, justice, accountability, privacy and trust. Analyses of these issues, however, were mostly superficial and did not substantially engage with some of the distinctive features of EHC like urgency and high-stakes decision-making. In particular, urgency and stakes were under-recognised or under-explored in the EHC AI literature. Arguably, urgency in some emergency scenarios could justify more flexible ethical/regulatory standards, while conversely high-stakes contexts might require more stringent standards.
conclusionLack of discussion of these contextual nuances suggests a significant gap in the literature of deeper research into the unique ethical, legal and social issues arising from AI use in EHC. This paper extends current knowledge by highlighting the need for deeper and more contextualized investigation of AI ethics in EHC.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.