International journal of critical illness and injury science · 2026
Adoption, perceived value, and barriers to generative artificial intelligence in emergency medicine: A cross-sectional survey of Latin American clinicians.
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Baez Amado Alejandro, Acra Claudia, Difo Brailin
Аннотация
BACKGROUND: Generative artificial intelligence (AI) tools are increasingly used by healthcare professionals, yet empirical data on adoption among Latin American emergency medicine clinicians remain limited.
METHODS: A voluntary, anonymous, cross-sectional online survey was administered to emergency medicine professionals across Latin America (April-October 2025). The Spanish-language instrument, pilot-tested before deployment, assessed AI familiarity, use patterns, perceived value, risks, governance, and training needs. Descriptive statistics and Chi-square tests were used for analysis.
RESULTS: A total of 123 respondents from 16 countries were analyzed. Most practiced in public or mixed healthcare settings (71.3%) and had over 10 years of experience (61.3%). Familiarity with generative AI was moderate to high (76.9%), and professional use was common (78.3%), with ChatGPT the dominant platform (81.0%). Adoption patterns were homogeneous across countries, with no significant associations between country of origin and familiarity, frequency of use, or platform preference. Primary applications included research and literature review (66.1%), medical education (59.1%), and clinical documentation (40.9%). Nearly half reported high perceived utility (49.6%), and 51.7% noted improvements in productivity. Major concerns included misinformation, erosion of clinical judgment (56.2% each), algorithmic bias (53.7%), and legal liability (46.3%). Institutional AI governance was nearly absent, with only 7.4% reporting existing policies. Despite this, 88.4% expressed interest in formal AI training and 65.6% supported integration into clinical guidelines.
CONCLUSIONS: Latin American emergency clinicians are rapidly adopting generative AI with perceived benefits across multiple domains, but almost entirely without governance frameworks or structured training, highlighting an urgent need for regional policy and education infrastructure.
METHODS: A voluntary, anonymous, cross-sectional online survey was administered to emergency medicine professionals across Latin America (April-October 2025). The Spanish-language instrument, pilot-tested before deployment, assessed AI familiarity, use patterns, perceived value, risks, governance, and training needs. Descriptive statistics and Chi-square tests were used for analysis.
RESULTS: A total of 123 respondents from 16 countries were analyzed. Most practiced in public or mixed healthcare settings (71.3%) and had over 10 years of experience (61.3%). Familiarity with generative AI was moderate to high (76.9%), and professional use was common (78.3%), with ChatGPT the dominant platform (81.0%). Adoption patterns were homogeneous across countries, with no significant associations between country of origin and familiarity, frequency of use, or platform preference. Primary applications included research and literature review (66.1%), medical education (59.1%), and clinical documentation (40.9%). Nearly half reported high perceived utility (49.6%), and 51.7% noted improvements in productivity. Major concerns included misinformation, erosion of clinical judgment (56.2% each), algorithmic bias (53.7%), and legal liability (46.3%). Institutional AI governance was nearly absent, with only 7.4% reporting existing policies. Despite this, 88.4% expressed interest in formal AI training and 65.6% supported integration into clinical guidelines.
CONCLUSIONS: Latin American emergency clinicians are rapidly adopting generative AI with perceived benefits across multiple domains, but almost entirely without governance frameworks or structured training, highlighting an urgent need for regional policy and education infrastructure.