INTRODUCTION:The proportion of women entering UK medical schools has increased rapidly, with women now making up 60% of students. The changing gender composition of the medical workforce brings to the forefront the National Health Service's (NHS) need to adapt to help women thrive in the workplace. METHODS:Our Women's Clinical Network organised a free Trust-based half-day event called 'Navigating the NHS and Having a Family', open to all doctors of any gender, grade and specialty, with presentations on topics including NHS family leave entitlements and less than full-time training. Pre-event and post-event surveys collected qualitative and quantitative data. RESULTS:Pre-event, we identified a lack of knowledge regarding family leave entitlements and processes. A quarter of attendees felt it possible to have a great career and a family, pre-event. This rose to over three-quarters, post-event. We also demonstrated improved knowledge on how to navigate the NHS and have a family post-event. DISCUSSION:Changes need to be made to ensure clinicians make informed decisions when planning a family. Our half-day information session highlighted one relatively simple way in which this can be addressed. Integrating events such as ours will help disseminate information effectively and with lasting impact.
Background: Artificial intelligence (AI) is increasingly embedded in medical imaging workflows, yet many imaging professionals report limited preparation to evaluate, implement, and govern AI tools safely. This educational gap risks inappropriate reliance on AI systems and undermines effective clinical oversight and patient safety. Methods: We undertook a Three-phase mixed-methods study to co-design and evaluate a tiered AI education framework for healthcare professionals, with an emphasis on medical imaging. A hybrid co-design workshop involving 52 healthcare stakeholders identified AI knowledge gaps, role-specific needs, and training preferences, informing a Three-pathway framework spanning foundational AI literacy, imaging-focused proficiency, and policy and governance. Two continuing professional development courses - AI Literacy in Healthcare and AI in Medical Imaging – were subsequently designed and delivered to over 300 healthcare professionals. Pre- and post-course surveys (132/59 responses for AI literacy; 26/30 for AI in medical imaging) captured self-reported changes in knowledge, confidence, and understanding of ethical and regulatory issues; quantitative data were analysed descriptively and qualitative free-text responses thematically. Results: Workshop participants reported widespread gaps in foundational AI literacy, critical appraisal skills, and awareness of governance and regulatory requirements, and strongly endorsed the need for structured, role-specific training. For the AI literacy course, participants reported substantial short-term gains in core AI concepts, clinical use cases, and responsible AI principles, alongside increased confidence in discussing AI with colleagues and patients. Among imaging professionals, the AI in medical imaging course was associated with marked perceived improvements in understanding AI model training and validation, performance metrics, AI explainability, bias, and workflow integration with PACS/RIS, and in readiness to engage with AI-enabled imaging tools under appropriate human oversight. Conclusion: A co-designed, tiered AI education framework can address heterogeneous AI literacy and capability needs across the healthcare and medical imaging workforce, strengthening confidence and perceived preparedness for safe AI adoption. The proposed pathways offer a clinically grounded, governance-aware, and scalable structure that healthcare organisations and educators can adapt to support progressive, role-aligned AI capability building in medical imaging and related domains.
BACKGROUND:Clinical teaching fellows (CTFs) provide continuity for undergraduate clinical education, including induction delivery, timetabling coordination, bedside/clinical skills teaching, and day-to-day liaison between students and clinical teams. At Sandwell and West Birmingham Hospitals NHS Trust, West Bromwich, England, the CTF team supports placements for Aston University and the University of Birmingham medical students across Years 3-5 (>150 students), making reliable cohort-to-cohort handover critical. METHODS:We conducted a closed-loop clinical audit of CTF handover package usability and perceived operational readiness using an anonymous Google Forms (Google LLC, Mountain View, CA, USA) questionnaire with two Likert-scale items (clarity of the handover document; ease of navigation, scale 1-5), four yes/no process measures (access details current; responsibilities clear; induction information sufficient; digital tools effective), and free-text comments. Baseline data reflected the 2024-2025 cohort's received handover (8th to 22nd July 2025; n=6/6). Following a structured improvement package (formal handover presentation; rewritten and reorganised handover document; updated operational access information and signposting), re-audit data were collected from the incoming 2025-2026 cohort (4th to 10th August 2025; n=5/7; only five were able to attend the handover meeting due to prior work commitments). This was a local, closed-loop quality improvement clinical audit within a single NHS Trust. RESULTS:Mean ratings improved from 2.5/5 to 4.6/5 for document clarity and from 2.7/5 to 4.8/5 for ease of navigation. Process measures improved from 33% to 100% for access details, 17% to 100% for role clarity, 0% to 100% for induction sufficiency, and 83% to 100% for digital tool implementation. CONCLUSIONS:A structured handover package was associated with substantial improvement in handover package usability and perceived operational readiness for incoming CTFs. Standardised annual handover (slide deck plus version-controlled document and checklist) is recommended to sustain improvements.
Background In high-income countries (HIC), an increasing number of women giving birth require support to communicate in the host-country language. Interpreter services and translated resources should be provided for all who require them in healthcare settings. However, interpreter and translation provision in maternity services remain inconsistent. Language barriers are associated with poorer birth outcomes and contribute to maternal morbidity and mortality. This qualitative systematic review and synthesis explored women’s experiences of language barriers in high-income maternity settings. Methods Systematic searches across six electronic databases yielded 2652 results between January 2023 and November 2025. Two reviewers independently screened titles, abstracts, and full text against eligibility criteria, resolving discrepancies through discussion with team members. Data were analysed using interpretive thematic synthesis and reported and interpreted against the Socio-Ecological Model framework. Results Eighty-four studies (86 articles) encompassing 1,801 women’s voices from 22 HICs were included. Themes were integrated into a model describing outcomes for women based on interactions with maternity services and interpreting provision in the context of language barriers. Women’s experiences of maternity services in the context of a language barrier were mediated by two key factors: 1) interactions with professional interpreters and 2) ‘Work arounds’ in the absence of a professional interpreter. Women frequently reported inadequate or lack of interpreter and translation provision, inconsistent communication and system-level failures to recognise and address linguistic needs. These experiences contributed to disengagement, isolation and reduced trust in services, while increasing perceived and actual risk for women and infants. The model illustrates how structural and organisational constraints perpetuate inequalities in maternity care. Conclusion This synthesis highlights the inconsistency in provision of professional interpreting services and how this perpetuates disparities in care in high-income maternity settings. Institutional and individual level understanding of language barriers may contribute to perpetuating lack of access to safe care for women. System and personal changes are required to improve equity, understanding, and safety in maternity care. Appropriate, effective, 24/7 interpreter services and enhanced cultural awareness among healthcare providers are essential. Failure to address language barriers negatively impacts women’s maternity experiences leading to disengagement and isolation of women, increasing risks to safety. Registration: This review was prospectively registered on PROSPERO (CRD42023416095).
Musculoskeletal (MSK) conditions place a significant burden on individuals and healthcare systems. The MIDAS-GP study collected anonymised electronic health record (EHR) data from MSK primary care consulters in Staffordshire and Stoke-on-Trent, United Kingdom. This retrospective EHR analysis aimed to 1) characterise this cohort of individuals, 2) to explore MSK condition consultation rates and frequent attender rates over time, between practices, and between MSK pain sites and 3) explore inequalities in MSK primary care frequent attender rates between cohort sub-groups. We extracted EHR data of all adult MSK consulters in 30 GP practices in one English region over seven years. Consultation prevalence was reported per 1,000 of the registered adult population for each GP practice, based on the number of unique consulters in six-monthly time windows. Frequent attendance was defined as a consulter who had ≥ 5 consultations in the six months after their index consultation. Variation in frequent attender rates was reported crudely and using a fixed-effect regression model to evaluate their association with patient-level covariates. Between July 2016-June 2023, there were 768,870 MSK primary care appointments by 148,708 unique MSK consulters in the 30 GP practices that participated in the study. The mean six-month consultation prevalence was 126.18 per 1,000 of the registered adult population, although this started much higher in 2016, fell rapidly during the COVID-19 pandemic, with substantial variation in recovery by 2023. Overall, MSK frequent attender rates were 8.32
