Background: There has been growing acknowledgement that undergraduate medical education (UME) must play a formal role in instructing future physicians on the promises and limitations of artificial intelligence (AI), as these tools are integrated into medical practice. Methods:We conducted an exploratory survey of medical students' knowledge of AI, perceptions on the role of AI in medicine, and preferences surrounding the integration of AI competencies into medical education. The survey was completed by 321 medical students (13.4% response rate) at four medical schools in Ontario.Results: Medical students are generally optimistic regarding AI's capabilities to carry out a variety of healthcare functions, from clinical to administrative, with reservations about specific task types such as personal counselling and empathetic care. They believe AI will raise novel ethical and social challenges. Students are concerned about how AI will affect the medical job market, with 25% responding that it was actively impacting their choice of specialty. Students agree that medical education must do more to prepare them for the impact of AI in medicine (79%), and the majority (68%) believe that this training should begin at the UME level.Conclusions: Medical students expect AI will be widely integrated into healthcare and are enthusiastic to obtain AI competencies in undergraduate medical education.
BackgroundThere has been growing acknowledgement that undergraduate medical education (UME) must play a formal role in instructing future physicians on the promises and limitations of artificial intelligence (AI), as these tools are integrated into medical practice.MethodsWe conducted an exploratory survey of medical students’ knowledge of AI, perceptions on the role of AI in medicine, and preferences surrounding the integration of AI competencies into medical education. The survey was completed by 321 medical students (13.4% response rate) at four medical schools in Ontario.ResultsMedical students are generally optimistic regarding AI’s capabilities to carry out a variety of healthcare functions, from clinical to administrative, with reservations about specific task types such as personal counselling and empathetic care. They believe AI will raise novel ethical and social challenges. Students are concerned about how AI will affect the medical job market, with 25% responding that it was actively impacting their choice of specialty. Students agree that medical education must do more to prepare them for the impact of AI in medicine (79%), and the majority (68%) believe that this training should begin at the UME level.ConclusionsMedical students expect AI will be widely integrated into healthcare and are enthusiastic to obtain AI competencies in undergraduate medical education.
Aims To use a database of national essential medicine lists to determine how many include the three tobacco dependence medicines: nicotine replacement therapy, varenicline and bupropion. Methods Retrospective observational study using national essential medicine lists for 137 countries. Results Of the 137 countries, 34 listed at least one of the three tobacco dependence medicines included in this analysis. Bupropion was listed by 23 countries, nicotine replacement therapy by 17 countries and varenicline by eight countries. Conclusions Tobacco dependence medicines do not appear on the essential medicines lists of most countries.
Aim: Diabetes is the ninth leading cause of death. Improving access to diabetes medicines may decrease mortality. Diabetes medicines on national essential medicines lists (NEMLs) vary considerably. We examine the association between diabetes population health outcomes relating to mortality and the listing of diabetes medicines on national essential medicine lists for 127 countries.Materials and methods: We conducted a cross-sectional study. We determined the number of diabetes medicines on NEMLs and used multiple linear regression to analyse the association between diabetes health outcomes and the number of medicines on NEMLs. We used linear regression to assess the association between diabetes health outcomes and the listing of or not listing of medicines that were listed by 25-75% of countries. Diabetes prevalence, gross domestic product (GDP) per capita and mean expenditure per person with diabetes were controlled for in all analyses.Results: The total number of diabetes medicines listed on NEMLs ranged from 0 to 16 (median: 4; interquartile range: 3-6). Diabetes health outcome scores were associated with the number of diabetes medicines on NEMLs [1.3-point increase (95% confidence interval, 95% CI 0.5-2.1) for every additional medicine on NEMLs; P = .002] and GDP per capita [19.5-point increase (95% CI 5.4-33.6) for every 10-fold increase in GDP; P = .003]. Diabetes expenditure was not associated with health outcome scores (P = .23). Increases in diabetes health outcomes score were associated with the listing of glimepiride (7.9-point increase, 95% CI 2.3-13.5, P = .006) and glipizide (5.8-point increase, 95% CI 0.03-11.6, P = .049) on NEMLs.Conclusions: Listing of diabetes medicines on NEMLs has the potential to improve population health outcomes related to mortality in countries with diverse incomes and diabetes prevalence without necessarily increasing diabetes health expenditure.diabetes, essential medicines, health equity, health outcomes, mortality 1 | INTRODUCTION Diabetes is the ninth major cause of death globally 1 and many patients with diabetes are still inadequately treated, particularly in low-and middle-income countries (LMICs). 2 The World Health Organization (WHO) has set a voluntary target of 80% availability and 50% use of affordable essential medicines to treat non-communicable diseases in the public and private sectors by 2025. 3 However, this target is only consistently met in high-income countries. 2 The International Diabetes Federation (IDF) conducted a global survey, in 2016,
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