Background: While the global maternal mortality ratio (MMR) shows a decreasing trend, there is room for improvement. Midwifery education has been under scrutiny to ensure that graduates acquire knowledge and skills relevant to the local context. Objective: To review the basic professional midwifery qualification and pre-practice requirements in countries with lower MMR compared with Malaysia. Methods: A rapid review of country-specific Ministry of Health and Midwifery Association websites and Advanced Google using standardised key words. English-language documents reporting the qualifications of midwives or other requirements to practise midwifery from countries with a lower MMR than Malaysia were included. Results: Sixty-three documents from 35 countries were included. The minimum qualification required to become a midwife was a bachelor’s degree. Most countries require registration or licensing to practise, and 35.5% have implemented preregistration national midwifery examinations. In addition, 13 countries require midwives to have nursing backgrounds. Conclusion: In countries achieving better maternal outcomes than Malaysia, midwifes often have a degree or higher qualification. As such, there is a need to reinvestigate and revise the midwifery qualification requirements in Malaysia.

Purpose: Manual grading is time-consuming and prone to inconsistencies, prompting the exploration of generative artificial intelligence tools such as GPT-4 to enhance efficiency and reliability. This study investigated GPT-4’s potential in grading pharmacy students’ exam responses, focusing on the impact of optimized prompts. Specifically, it evaluated the alignment between GPT-4 and human raters, assessed GPT-4’s consistency over time, and determined its error rates in grading pharmacy students’ exam responses.Methods: We conducted a comparative study using past exam responses graded by university-trained raters and by GPT-4. Responses were randomized before evaluation by GPT-4, accessed via a Plus account between April and September 2024. Prompt optimization was performed on 16 responses, followed by evaluation of 3 prompt delivery methods. We then applied the optimized approach across 4 item types. Intraclass correlation coefficients and error analyses were used to assess consistency and agreement between GPT-4 and human ratings.Results: GPT-4’s ratings aligned reasonably well with human raters, demonstrating moderate to excellent reliability (intraclass correlation coefficient=0.617–0.933), depending on item type and the optimized prompt. When stratified by grade bands, GPT-4 was less consistent in marking high-scoring responses (Z=–5.71–4.62, P<0.001). Overall, despite achieving substantial alignment with human raters in many cases, discrepancies across item types and a tendency to commit basic errors necessitate continued educator involvement to ensure grading accuracy.Conclusion: With optimized prompts, GPT-4 shows promise as a supportive tool for grading pharmacy students’ exam responses, particularly for objective tasks. However, its limitations—including errors and variability in grading high-scoring responses—require ongoing human oversight. Future research should explore advanced generative artificial intelligence models and broader assessment formats to further enhance grading reliability.

The growth in medicine consumption in the Asia-Pacific region is estimated to be amongst the highest in the world (Aitken et al., 2024). Driven by the growing burden of chronic diseases, ageing-ass...