The EQ-5D is the most commonly used preference-based measure of health-related quality of life. There is limited evidence about the use of the EQ-5D in the Middle East and North Africa (MENA) region. This study aimed to systematically identify, review, summarize, and synthesize the published literature on using the EQ-5D in this region. A systematic literature review was conducted, according to the PRISMA 2020 guidelines, using PubMed, Cochrane, PsycINFO, and CINAHL and covering the period up to 30 August 2024. Studies using any version of the EQ-5D in adults or youth in the MENA region were included. Pilot studies, guidelines, study protocols, and reviews were excluded. Key study characteristics and outcomes assessed included study design, clinical area, population, type of EQ-5D data reported, reference value set used, and mode of administration. Title/abstract screening was conducted independently by two reviewers to assess eligibility for inclusion. Two researchers completed full-text screening and extracted data using a standardized form. Disagreements were referred to a third reviewer if not resolved by discussion. Results were summarized in systematic evidence tables. After removing duplicates, 18,034 references were considered for title/abstract screening. In total, 184 studies were included with a total sample size of 128,164 subjects. Of the included single-country studies, 42% were reported in Iran, 20% in Saudi Arabia, and 11% in Jordan. Patient populations were investigated in 86% of the studies, 23% of which targeted endocrine diseases. Study design was observational in 57% and experimental in 14% of the studies. Only 10% of the included studies applied the EQ-5D in an economic evaluation. The EQ-5D-3L version was used in 40% of the studies. However, the trend is towards a greater use of the 5L version in more recent years. Twenty percent of the studies reported EQ-5D results using the index score, frequencies of severity levels per dimension, and visual analog scale scores. EQ-5D modes of administration and funding sources were not reported in 16% and 20% of the studies, respectively. There is an increased use of the EQ-5D in the MENA region, especially since 2020. In the region, the use of the EQ-5D is more prevalent in clinical studies than in economic evaluation studies. The reporting heterogeneity indicates the need for guidance in reporting EQ-5D study results in this region.

Surgical waiting lists pose a major challenge for public healthcare systems, affecting access to care and the perceived quality of services. However, there is no standardized method for assessing the efficiency and management of waiting lists. This study proposes a model based on Key Performance Indicators (KPIs) to measure the Waiting List sustainability of surgical waiting lists, evaluating their balance, attractiveness, efficiency, and timeliness. Three main KPIs were defined and applied to both hypothetical and real datasets, analyzing data collected at the IRCCS Istituto Ortopedico Rizzoli from January 2024 to September 2024. Statistical analysis was conducted using Excel, calculating ratios between enrolled, admitted, canceled, and overdue patients on the waiting list. The analysis showed that some hospital departments have a balanced management of waiting lists, while others exhibit critical issues, with high rates of overdue or canceled patients. The graphical representation of the indicators helped identify areas for improvement in resource management. The adoption of standardized KPIs could serve as a valuable tool for monitoring and optimizing waiting lists, supporting strategic decisions to enhance access to healthcare services.

The rapid integration of digital health tools into clinical practice presents new opportunities for supporting clinical reasoning. But doctors and nurses must learn how they can use digital health tools such as AI and telehealth to support clinical reasoning (CR). Our objectives were to investigate how and which digital tools have been integrated in medical and nursing CR education. Rapid review of 46 studies about integrating digital health tools in medical and nursing CR education. Most studies reported about Large Language Models, EHRs and Clinical Decision Support Systems integrated into CR education. Digital tools are increasingly integrated into medical and nursing clinical reasoning education, yet the focus is limited to certain types of tools.

Integrating nursing informatics education into nursing is essential for advancing the digital transformation of nursing. The objective was to develop nursing informatics curricula tailored to the needs in Kosovo and Israel. Reviewing 16 international guidelines, conducting interviews with 22 national stakeholders, and undertaking an international Delphi study. The study identified key challenges and recommendations for nursing informatics education. It ranked a list of 40 nursing informatics topics and developed two national curricula. Effective nursing informatics education on a national scale requires the integration of national stakeholders and international perspectives to address diverse needs and contexts and to advance the field.

Europe's ageing society faces a growing gap in long-term care (LTC) resources. The Care about Care project developed a Remote Care Assist (RCA) system to support LTC staff. The project aimed to develop and evaluate a robust, mixed-reality- capable communication infrastructure for home care workers. This case report (a) details requirements for a communications infrastructure, (b) examines challenges in field testing, and (c) describes the transition to an alternative approach. It also provides a glimpse into a new solution used in a follow-up project. User requirements were gathered through co-creation workshops across three countries. Technical requirements focused on modularity, security, integration, and cross-platform usability. The initial implementation used Asterisk and was tested with ∼300 participants. The field test revealed persistent video quality issues with Asterisk, attributed to its WebRTC implementation. A switch to Kamailio resolved these issues, improving video quality but sacrificing group call capabilities. Pre-testing is limited, highlighting the necessity of field testing. Emerging frameworks like LiveKit could be an alternative for follow-up projects.

The use of Logic Models provides a structured approach to understanding and visualizing the impact of interventions in complex systems, such as Ambient or Active Assisted Living (AAL). To apply a Logic Model to represent and categorise findings from a study on using a robo-coach for training younger seniors in an AAL app. A Logic Model was developed to represent the effects that were observed in the interaction between 34 younger seniors and the robo-coach, focusing on how the training impacted their perceptions on the robo-coach. The Logic Model maps how specific training activities directly enhance user confidence, shaping perceptions of the robo-coach's usability and role in AAL adoption. The Logic Model proved to be an effective tool for retroactively analyzing the impact of the robo-coach intervention.

Large Language Models (LLMs) offer promising applications in oncology pathology report classification, improving efficiency, accuracy, and automation. However, the use of real patient data is restricted due to legal and ethical concerns, necessitating privacy-compliant alternatives. This study aimed to develop a synthetic oncology pathology dataset to serve as a benchmark for LLM evaluation, enabling reproducible and privacy-preserving AI research. A total of 227 synthetic pathology reports were generated using Microsoft Copilot, ChatGPT Plus, and Perplexity Pro to ensure structural and linguistic diversity. The dataset included cases of prostate (n=75), lung (n=78), and breast (n=74) cancer, evenly distributed between malignant (n=113) and benign (n=114) findings. Reports were reviewed and classified by three independent cancer registrars using a consensus-based validation process. The dataset provides a structured, clinically relevant benchmark for evaluating LLM performance in pathology text classification. It enables AI model assessment without compromising data privacy, paving the way for scalable and ethical AI-driven oncology documentation.

In refractory epilepsy and inherited metabolic disorders, Ketogenic Dietary Therapies (KDT) are established non-pharmacological treatments. Telemedicine might contribute to tackle various challenges related to KDT complexity and the respective target diseases. A questionnaire on the current use and future requirements was provided for health care professionals working in neuropediatrics, inherited metabolic diseases and nutrition within the region of German speaking countries. Distribution was facilitated via an established network. Response rate was 83% (24/29). Respondents were physicians (63%) and experts from the field of nutrition (37%). Telemedicine use in any way was reported by 71%. For future telemedicine aids, provision of digital patient information and aspects regarding ketone body, seizure and growth monitoring were ranked highest, while visualization of blood sugar and sensor integration were rated less relevant. Caution regarding legal aspects (liability), reimbursement and technical integration within the current hospital information system was addressed proactively by participants.

BackgroundThe Global Burden of Disease Study (GBD) produces prevalence estimates for ‘idiopathic epilepsy’ (ie, of unknown aetiology) and ‘secondary epilepsy’ (ie, with known aetiology) but does not report prevalence by underlying aetiologies for ‘secondary epilepsy’.MethodsWe used nationwide, population-based register data from Denmark to identify underlying causes of epilepsy and their contribution to prevalence of ‘secondary epilepsy’ and compared with global prevalence data from GBD 2019. We identified all persons with a hospital-based epilepsy diagnosis and a filled prescription for antiseizure medication between 1 January 2009 and 31 December 2018. Epilepsy was categorised into ‘idiopathic’ or ‘secondary’ and ‘total epilepsy’ as the sum of the two epilepsy categories.ResultsOn 31 December 2018, a total of 5 784 284 individuals (49.7% males) were living in Denmark including 40 336 with epilepsy (51.5% males). Perinatal conditions, traumatic brain injury, brain tumours and stroke were prominent underlying causes of ‘secondary epilepsy’. The prevalence of ‘total epilepsy’ in Denmark was 697 (95% CI 691 to 704) per 100 000 population (264 (95% CI 260 to 269) for ‘secondary epilepsy’ and 433 (95% CI 428 to 438) for ‘idiopathic epilepsy’). In the GBD 2019 Study, the prevalence of ‘total epilepsy’ in 2018 was 682 (95% uncertainty interval (UI) 586 to 784) per 100 000 population (359 (95% UI 324–397) for ‘secondary epilepsy’ and 324 (95% UI 249 to 404) for ‘idiopathic epilepsy’).ConclusionsPrevalence estimates of ‘total epilepsy’, ‘idiopathic epilepsy’ and ‘secondary epilepsy’ in Denmark align with the GBD 2019 estimates. In future studies, it is suggested to explicitly include all types of epilepsy, including ‘secondary epilepsy’, which is currently estimated as sequelae (consequences) of underlying diseases.