National Health Insurance Fund

Generative artificial intelligence (GenAI) tools such as ChatGPT are rapidly transforming health care education. Understanding how health care professionals perceive these technologies is vital for responsible adoption. This study examines the readiness, perceived benefits, and ethical concerns of European health care professionals. A cross-sectional online survey was conducted among 47 health care professionals from clinical and academic institutions across Europe. The questionnaire assessed familiarity with GenAI, perceived usefulness in education and clinical contexts, ethical concerns, and readiness for adoption. Descriptive and inferential analyses, including chi-square tests, factor analysis, and regression, were applied to address seven predefined research questions. Participants showed limited experience with GenAI but recognized its educational value, especially in preparing teaching materials and supporting student learning. Ethical concerns centered on accuracy, privacy, and loss of human interaction. Familiarity significantly predicted readiness to adopt, while demographic differences (eg, age, professional role) influenced attitudes modestly. Five user profiles were identified, ranging from education-focused to clinically oriented users. Findings indicate cautious optimism toward GenAI. Health care professionals see clear educational potential but stress the need for accuracy, accountability, and ethical safeguards. Structured faculty training, institutional support, and AI literacy development are essential to balance innovation and responsibility.

A 52-year-old man with multiple scalp nodules for more than 30 years and a right occipital mass that had been progressively enlarging for the past 2 years and rupturing and draining for more than 6 months was pathologically confirmed to be secondary malignant proliferating trichilemmal cyst (MPTC). 18 F-FDG PET/CT showed active glucose metabolism in the scalp lesion and similar hypermetabolism in the dorsal and right iliac spine skin nodules. This case demonstrates the significant advantages of 18 F-FDG PET/CT whole-body imaging in evaluating malignant proliferating trichilemmal cyst, a rare disease.

Diffuse gastric metastasis of esophageal squamous cell carcinoma (SCC) manifested as linitis plastica is extremely rare. A 49-year-old man complained of postprandial vomiting and epigastric colicky pain, and biopsy indicated mucosal inflammation. 18F-FDG PET/CT revealed diffuse wall thickening of mid-to-lower esophagus and diffuse gastric wall thickening accompanied by mediastinal lymph node, perigastric, and peripancreatic lesions with intense FDG accumulation. Malignancy of mid-to-lower esophagus and linitis plastica accompanied by lymph node, perigastric, and peripancreatic metastases was suspected. Biopsies of multiple sites of esophagus and stomach confirmed SCC. 18F-FDG PET/CT is instrumental for evaluating rare metastasis of esophageal SCC and guiding biopsy.

Workers compensation claim processing is extraordinarily inefficient and causes claimants and employers to suffer. In a typical Australian workers compensation insurer, the Claim Establishment Process can require up to 28 manual steps performed by claim adjuster. Claims departments follow strict business rules that stipulate if a claimant is eligible for certain claim benefits as well as the appropriate medical certificates, certificates of capacity, statutory reserves and claim flags to allocate to the claimant. These are often automated or semi-automated in complexity, however in practice, require considerable agentic decision-making to complete the processing. Claim adjusters perform these decisions, which can be expensive and introduce wait times that delay claimants and employers from receiving their benefits. This feasibility study presents a deep learning framework designed to automate the workers compensation claim process using generative AI. A proof of concept application, entitled ClaimGPT, was implemented using the OpenAI API and Salesforce Einstein GPT, providing agentic AI capabilities for claim generation and decision-making. These capabilities were combined with natural language processing models for claim textual data and image generation for claim documentation. The framework was implemented in two existing workers compensation insurers, focusing on the Claim Establishment and Claim Decision Process. Both implementations were successful in accelerating the claim processing, while reducing the size of the claim reserves allocated to each claim established. The image generation models for claim documentation synthesised novel claim scenes and demonstrated claim simulation capability on a specific insurance use case.

Abstract Background Providing fair access to haemodialysis treatment is a major difficulty in regions with limited resources and large territories. This investigation explores how geographic obstacles, logistical constraints, and health system structure affect the delivery of haemodialysis services in the Northern State of Sudan. Methods We performed a mixed methods study, integrating operational data from September 2025 from all 13 haemodialysis centres in Northern State. Quantitative assessment employed Gini coefficients and Lorenz curves to evaluate inequality in the distribution of resources. For qualitative insights, we applied thematic analysis to open ended feedback from centre managers about operational difficulties and potential remedies. Results Services were found to be highly concentrated (Gini coefficient = 0.58). A single urban centre provided care for 44.4% of all patients, whereas the five smallest centres collectively served only 12.3%. For remote facilities, a strong link was observed between greater distance from the central supply depot and delays in receiving materials (Spearman’s ρ = 0.72, p < 0.01). These centres faced prolonged wait times (extending to 30 days), recurring shortages of critical medications, and increased operating expenses. Qualitative evaluation revealed three core themes: (1) Vulnerability of the centralised supply system, (2) Financial instability of outlying centres, and (3) The pervasive burden of distance as a fundamental barrier. Conclusions Inequities in haemodialysis access in Northern State are rooted in the structure of a centralised and vulnerable system. A deliberate policy move towards decentralising service delivery and supply management is crucial for promoting fairness in kidney care. These insights are relevant for reconfiguring specialised healthcare delivery in other resource constrained environments facing similar geographic hurdles.

Abstract Background The Revolving Drug Fund (RDF) model has been widely implemented across low- and middle-income countries (LMICs) since the 1980s as a market-based mechanism to address chronic medicine shortages. Despite early successes in improving drug availability, many RDFs have experienced significant challenges leading to failure or substantial modification. This systematic review examines the full lifecycle of RDF implementation in LMICs, analysing systematic patterns of decline and transition. Methods Following PRISMA 2020 guidelines, we conducted comprehensive searches across PubMed, Scopus, Embase, and Web of Science (2000–2023). Sixty-seven studies met the inclusion criteria, representing diverse LMIC contexts. Thematic analysis identified failure patterns across financial, governance, and operational dimensions, with critical appraisal based on Joanna Briggs Institute protocols. Results Our analysis delineates three distinct RDF lifecycle phases: (1) Initiation (years 0–3), characterized by 40–70% reductions in stock-outs and 70–90% cost recovery; (2) Consolidation (years 4–7), marked by emerging governance challenges and inflationary pressures; and (3) Decline/Demise (years 8+), wherein only 31% of programs retained their original structure. Primary failure pathways included financial unsustainability (85% of studies), weak governance structures (78%), macroeconomic shocks (71%), equity violations (66%), and supply chain inefficiencies (59%). The Sudanese transition from RDF to the National Medical Supplies Fund (NMSF) exemplifies strategic adaptation to these systemic limitations. Conclusion RDFs exhibit predictable lifecycle patterns with inherent structural vulnerabilities in LMIC settings. Sustainable pharmaceutical financing requires integrated approaches that combine efficient procurement with robust equity protections. Future models must navigate the tension between cost recovery and universal access through hybrid financing mechanisms and stronger integration within health systems.

<title>Abstract</title> <bold>Background:</bold> Community pharmacies (CPs) in Sudan are accessible and cost-effective points of healthcare. However, Pharmaceutical Care Services (PhCS) has not been widely adopted. So far, adoption depends critically on resolving challenges and effectively utilizing the available opportunities. <bold>Objective:</bold> To assess the challenges and opportunities for pharmaceutical care adoption in private community pharmacies(CPhs), Wad-Madani, Gezira State, Sudan. <bold>Methods:</bold> This cross-sectional study was conducted from December 2019 to August 2020, involving 120 community pharmacists. A pre-tested, self-administered, structured questionnaire was used for data collection. The Statistical Package for the Social Sciences (version 26) was used for the analysis of categorical data variables. The p-value (α = 0.05) is the cutoff point for determining the significance of the results. <bold>Results:</bold> The response rate among participants was 87.1%. The demographic characteristics showed younger age dominance (82.5% aged ≤ 40), with 63.3% females, less experience (&lt; 20 years, 92.5%), and most holding a B.Pharm degree (91.7%). Over half of pharmacists (52.5%) engaged in multitasking roles, including dispensing, counseling, handling money, and managerial activities, often without a separate counseling area. Awareness regarding PhCS was high (81%). However, the main barriers included 40% as insufficient continuous professional development (CPD) and 31.7% due to public perceptions. In comparison, the top supporting factor was the presence of organized staff members (55.8%). Pharmacists prioritized CPD (61.7%) as a means of supporting PhCS adoption. Overall, the observed difference between pharmacy groups was statistically insignificant for all variables (X² and Fisher's Exact test, p-values &gt; 0.05), indicating uniformity among community pharmacists. <bold>Conclusions:</bold> The demographic profile presents both opportunities and challenges. High awareness suggests rich ground for interventions. Interestingly, systemic barriers and discouraging factors can be overcome through coordinated strategies that involve education reform, regulatory frameworks, infrastructure design, and workforce planning. Results are essential for transforming community pharmacy practice into effective models of pharmaceutical care services.

High-quality datasets are crucial for computer vision in endangered fish monitoring. Species similarities and dynamic environments pose challenges. The Pomeranian region, a key salmonid refuge with ongoing restoration efforts, necessitates robust monitoring to assess restoration success. To facilitate environmentally sustainable research, we introduce a dataset, Pomerania Fish (PomerFish), comprising two sub-datasets: PomerFishObj and PomerFishSeg, each with corresponding annotations. This dataset, compiled by salmonid experts, focuses on endangered Central European salmon populations. It was collected from 2015 to 2024 in the Pomerania Region, Central Europe, using a GoPro Hero 5 camera. The dataset comprises: (1) PomerFishObj, containing 14,989 high-resolution images with manually annotated bounding boxes and 3,273 negative samples (fish absence); and (2) PomerFishSeg, containing 1,115 images, including 1,038 with polygon-based segmentation masks and 77 negative samples. Characterized by high-resolution imagery, large data volume, and comprehensive habitat records beyond species, it enables training for detailed underwater observations and precise species growth estimations. This dataset supports targeted conservation and habitat management, providing crucial resources for research, species detection, and conservation practices.

ABSTRACTBackgroundInsurance data allow insights into dispensations of medications. This retrospective study over 49 months examined dispensations of monoclonal antibodies against calcitonin gene‐related peptide (CGRP‐mAbs).MethodsUsing nationwide insurance data, we examined dispensations of erenumab, fremanezumab, or galcanezumab from September 1, 2018 to September 30, 2022. We examined the duration of treatment and breaks (Kaplan–Meier curves, medians, quartiles), persistence (proportion of days covered), and switches, acute medications, and other preventatives.ResultsOf 8.8 million persons, 8934 were at least once dispensed a CGRP‐mAb (83.5% women, median age 45 years). Median individual follow‐up time was 710 days, median duration of treatment with any CGRP‐mAb was 297 days, 42.9% had CGRP‐mAbs for at least 1 year. Median duration of treatment with the first‐ever CGRP‐mAb was 327 days; 63.4% experienced a therapy break. Within 1 year after stopping, 53.5% resumed the same CGRP‐mAb, 16.9% another CGRP‐mAb, 29.6% did not resume any CGRP‐mAb; 13.7% started a second CGRP‐mAb and 1.7% a third. 22% definitively stopped therapy within their follow‐up. Dispensation of triptans decreased during and after therapy with CGRP‐mAbs; dispensation of other acute prescription medications was low without change. 11.4% had other preventatives before and 2.4% during CGRP‐mAb therapy. The proportion of days covered was 96%.ConclusionsIn this nationwide study persistence with CGRP‐mAbs was excellent; dispensations of triptans and other preventatives decreased during CGRP‐mAb therapy. Therapy breaks were common, but the majority resumed CGRP‐mAbs, which indicates the need for long‐term prophylaxis.

Retirement transition represents a critical life stage associated with significant health risks. This study aimed to develop an evidence-based framework of preventive clinical practices to facilitate healthy retirement transition and minimize health deterioration risks. Modified Delphi consensus methodology with French physicians' experts. Experts in prevention, geriatrics, and life transitions were consulted through two online rounds. A preliminary framework containing 35 evidence-based proposals was developed from literature review. Experts rated their agreement using a 9-point Likert scale, with consensus defined as median scores ≥7. Seventeen and fifteen medical experts participated in rounds one and two respectively (participation rates: 53.1% and 88.2%). All experts considered retirement-specific preventive examinations essential (50%) or very important (28%), recommending 2-h consultations (39%). Consensus was achieved on 34 proposals across three domains: health counseling (n=7), screening (n=26), and immunization (n=1). Priority counseling included healthy eating promotion, adapted physical activity, and systematic social isolation detection. Essential screening encompassed cancer screening (cervical, colorectal, breast, prostate, lung, skin), cardiometabolic disorders (hypertension, dyslipidemia, diabetes, obesity), mental health assessment using validated tools, sensory impairments, cognitive disorders, fall risk evaluation, and oral health assessment. All items achieved median scores of 7-9 with >70% expert agreement. Systematic vaccination status verification received unanimous support. This consensus of French physicians provides a comprehensive, structured framework for preventive clinical practice during retirement transition, potentially improving retirees' quality of life through systematic health risk identification and management. However, this physician-centered consensus requires validation through multidisciplinary input and patient perspectives to ensure comprehensive retirement transition support. These recommendations represent a foundation requiring multidisciplinary validation before implementation.