Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsinyY V Dolzhenkova, E V Kamneva
The implementation of digital technologies in the work of both health care professionals and the industry as a whole is a key factor in improving health care efficiency. The digitization of the Russian health care is implemented in accordance with the strategy of digital transformation. The digital transformations not only condition changes in the existing organization of functioning of medical institutions but also cardinal transformations in content, nature and organization of labor of medical workers. The transformations in labor sphere of health care are related to appearance of telemedicine, digital ecosystems and application of databases, knowledge bases and AI in treatment of patients. The changes in labor sphere in conditions of digitization result in both positive outcomes (development of professional knowledge and skills, expansion of functional, labor enrichment) and negative outcomes (workers overload, resistance to innovations, professional burnout).
Australasian journal on ageingKaleab Taye Haile, Wejdan Shahin, Eyob Alemayehu Gebreyohannes, Abdella Birhan Yabeyu, Amina Hareem, Mulugeta Hayelom Kalayou, Xun Yi, Kate Wang
OBJECTIVE: To review evidence on the type, characteristics and effect of digital health interventions (DHIs) on medication adherence among older people. METHODS: Articles were searched from inception to May 2025 in PubMed, Embase, CINAHL, Scopus and Web of Science. Randomised and non-randomised studies were included if they: involved older people aged 65 years or older; applied any DHI(s); compared the intervention with a comparator group or baseline; and reported medication adherence as an outcome. Risk of bias was assessed using the Cochrane risk of bias tools, and certainty of evidence using GRADE (Grading of Recommendations, Assessment, Development and Evaluation). A narrative synthesis was conducted. RESULTS: A total of 35 articles were included, most of which were randomised controlled trials (n = 22). Risk of bias ranged from low to high, and certainty from very low to moderate. Nearly half of the studies (n = 17) reported DHIs improved medication adherence compared with control or baseline. Mobile apps (3/5), electronic reminders (3/3), social assistive robots (1/1), telenursing (1/1) and combined DHIs (2/2) showed the most promise. Interventions that used multiple functionalities or strategies to support behaviour change (reminders or prompts) were most likely to improve adherence. The other DHIs had mixed results or no significant effects. CONCLUSIONS: While findings across DHIs varied, interventions incorporating tailored reminders, multicomponent features and interactivity may have the potential to be more effective in improving medication adherence among older adults. Further research is needed to identify usage patterns and investigate the factors underlying differences in effectiveness.
Clinical and experimental dental researchEzgi Can Cekic, Mertkan Kumru, Burcu Yilmaz, Berk Celikkol, Oğuz Tavsan
OBJECTIVES: Traumatic dental injuries (TDIs) are frequent in clinical practice and require rapid, guideline-based decisions, yet accessing accurate and reliable information may be challenging. Large language models (LLMs) such as ChatGPT, Gemini, DeepSeek, and Qwen are increasingly used as quick online information tools; however, evidence regarding their accuracy, consistency, and the influence of different user interfaces is limited. This study aimed to evaluate the performance of several LLMs in answering TDI-related questions through both web-based interfaces and mobile phone applications. MATERIAL AND METHODS: Twenty questions were prepared according to the 2020 International Association of Dental Traumatology (IADT) guidelines, including 10 open-ended and 10 yes-no items. Four LLMs (ChatGPT-4o, DeepSeek-V3, Gemini 2.0 Flash, Qwen2.5-Max) were queried simultaneously via web and mobile interfaces over five consecutive days, generating 800 responses. Open-ended answers were assessed using the Global Quality Score (GQS) and modified DISCERN (mDISCERN), while yes-no responses were compared with a predetermined answer key. Statistical analyses were performed using IBM SPSS v23.0, with significance set at p < 0.05. RESULTS: Qwen2.5-Max demonstrated comparatively higher GQS and mDISCERN scores across both interfaces. Accuracy for yes-no questions ranged from 86% to 91% without significant differences among models. Interface comparisons showed that ChatGPT-4o generated comparatively higher-quality responses on the web, whereas Qwen2.5-Max performed better on mobile. Over the 5-day period, Qwen2.5-Max showed relatively higher temporal consistency, while DeepSeek-V3 exhibited notable day-to-day variation. CONCLUSIONS: LLMs may serve as useful supplementary tools for providing guideline-based information on TDIs, especially for straightforward, closed-ended clinical questions. However, their performance varies by model, interface, and question type. Qwen2.5-Max demonstrated comparatively higher performance across several evaluated measures. Despite these results, LLM-generated information should be interpreted cautiously and verified by dental professionals before being used in clinical decision-making.
Obesity science & practiceMichele L Patel, John A Gallis, Amanda B Zeitlin, Phoebe C Crosthwaite, Annalisa W Lim, Kayla A Collins, Marily A Oppezzo, Lisa G Rosas
BACKGROUND: Goal setting is a key component in behavioral weight loss interventions. Goal setting theory emphasizes having harder goals rather than easier goals. However, few studies have experimentally manipulated goal difficulty levels in digital weight loss interventions. Further, when multiple goals are assigned, it is unclear if harder goals are effective or too overwhelming. METHODS: Ignite was a pilot optimization trial guided by the Multiphase Optimization Strategy. A 24 factorial design was used to randomize 32 participants (U.S. adults with overweight or obesity) to either an easier or harder goal for four goal domains: calories, steps, eating windows, and Red Zone Foods (i.e., high-calorie, low-nutrition foods). All participants received a 10-week fully digital weight loss intervention with daily self-monitoring of goals, weekly lessons, action plans, and feedback. Data were collected via digital tools (daily) and surveys (baseline, 4-, 10 weeks); feasibility and acceptability were assessed descriptively, while proof of concept was assessed via linear mixed models. Findings were compared to a priori benchmarks. RESULTS: Participants had a mean (SD) age of 47.7 (13.3) years and BMI of 30.1 (3.8) kg/m2 and 47% racial/ethnic minority. Feasibility and acceptability benchmarks were largely met, with high engagement, 94% retention (30/32) at 10 weeks, and 97% recommending the program. For proof of concept, the 3%, but not 5%, weight loss benchmark was met (mean (SD) -3.3 (2.5) kg, or -4.0% (3.6%) at 10 weeks). Participants with a harder calorie goal had greater weight loss than those with an easier calorie goal (difference: -2.3 kg [95% CI, -4.1, -0.6 kg]). No main effects were observed for other goals. CONCLUSION: With high feasibility of study procedures, high engagement, and moderate-to-high acceptability, the intervention needs only minor refinements prior to proceeding to a fully powered trial testing the efficacy of easier versus harder goals for weight loss. TRIAL REGISTRATION: ClinicalTrials.gov NCT05715242. Registered on February 6, 2023.
International journal of qualitative studies on health and well-beingLi-Ting Chen, Hsin-Tien Hsu, Meei-Fang Lou, Chia-Yi Wu, Cheng-Han Lin, Yueh-Hsiu Lin
BACKGROUND: Most applications for depression lack comprehensive theoretical integration and qualitative assessments of university students' needs remain insufficient. OBJECTIVE: This study aimed to explore the needs and experiences of university students with depressive symptoms and develop a theory-driven app design framework tailored to the target population. METHODS: A post-positivist qualitative framework was used to recognize the value of subjective experience. Semi-structured interviews were conducted with 32 students with moderate to moderately severe depression. Reflexive thematic analysis was used to identify themes in the data. RESULTS: Three themes emerged: app design, help-seeking processes, and core features of cognitive behavioral therapy. Students emphasized the importance of discreet, user-friendly design, such as positive naming, privacy protection, and flexible reminder functions. Although some expressed concerns regarding the empathy and reliability of artificial intelligence, others valued its anonymity and capacity to provide immediate support. Regarding theoretical integration, participants considered monitoring emotions and physical sensations essential but also highlighted the need for diverse and personalized methods. The conceptualization of self-monitoring data was considered useful for facilitating clinical consultations. CONCLUSION: Students considered theory-based health education as effective for improving mental health knowledge and promoting help-seeking awareness. The findings support clinical decision-making in developing more effective digital tools.
Meningococcal infections represent a significant public health concern due to their high mortality and morbidity rates. In Turkey, meningococcal vaccines are not included in the routine immunization schedule, and families increasingly seek health-related information through digital platforms. YouTube, as a widely used video-sharing platform, has the potential to influence public attitudes toward vaccination; however, concerns remain regarding the reliability and quality of its content. This study aimed to evaluate the characteristics and quality of YouTube videos related to meningococcal vaccines in Turkey. This cross-sectional study analyzed 158 YouTube videos retrieved using the keywords "meningococcal vaccines" and "private vaccines." Videos were evaluated according to uploader type, content features, message tone, and audio-visual quality. The Global Quality Scale (GQS) and the Journal of the American Medical Association (JAMA) benchmark criteria were used for quality assessment. Of the videos, 55.7% were uploaded by physicians and 92.4% were intended for patient education. Most videos (86.7%) conveyed positive messages about vaccination. Physician-produced videos demonstrated significantly higher quality scores, while videos uploaded by pharmaceutical companies were more up-to-date and had higher view counts. Overall, a considerable proportion of the videos were of moderate or low quality. The quality and reliability of YouTube content on meningococcal vaccines vary substantially. Increasing the availability of evidence-based, high-quality content and encouraging greater involvement of healthcare professionals in digital media are essential to support informed vaccination decisions and reduce vaccine hesitancy.
Internet interventionsJeanette Röhrig, Lorenz Sutter, Lena Rademacher, Vanessa-Emily Müller-Schoch, Franziska Träuble, Antonia Groß, Danja Bogdan, Sabrina Stebe-Frick, Hannes Schier…
BACKGROUND: Psychoactive substance use often begins during adolescence, and early initiation increases risks of problematic use and adverse health outcomes. Few evidence-based, technology-supported substance use prevention programs for adolescents exist in Europe. OurFutures (previously Climate Schools) is a web-based substance use prevention program developed in Australia that has been shown to improve substance-related knowledge and strengthen refusal and harm-minimization skills. This study aimed to adapt the OurFutures Alcohol and Cannabis course for German schools and to evaluate its feasibility and preliminary effectiveness. To strengthen the link between prevention and early intervention, the program was connected to the Mobile Online Portal for Questions on Addiction (MOFA), enabling students to access counseling services via chat, email, or telephone. METHODS: The Alcohol and Cannabis course was adapted for the German school and addiction systems, and the online portal was created. Effectiveness and implementation were assessed in four German secondary schools using a controlled pilot study with quantitative surveys, complemented by exploratory qualitative feedback from a focus group (n = 2) and three individual interviews. RESULTS: Analyses of covariance demonstrated that the intervention group's knowledge about alcohol (n = 62) and cannabis (n = 63) increased significantly more than of controls (n = 28 and 31). No significant differences were observed for attitudes or intentions to use. Most students evaluated the Alcohol module positively and relevant. Qualitative findings indicated satisfaction among students and teachers, with suggestions for school implementation. CONCLUSION: This blended-learning program increased substance-related knowledge and may strengthen school-based prevention in Germany. Wider implementation requires coordination between education and addiction systems.
Health information science and systemsTaslima Khanam, Siuly Siuly, Kate Wang, Hua Wang
PURPOSE: The rise of large language models (LLMs) such as GPT-4 and DeepSeek has transformed healthcare information processing by enabling natural language-based clinical reasoning. However, the integration of LLMs with privacy-sensitive biomedical signals, particularly electroencephalogram (EEG) data used in brain-computer interface (BCI) systems, remains underexplored. EEG signals, especially during motor imagery (MI) tasks, are critical for assistive neurotechnologies but pose significant privacy risks due to their capacity to reveal cognitive and medical information. Traditional encryption techniques often distort signal structure or require decryption with additional noise, compromising classification performance and real-time usability. METHODS: To address this gap, we propose a deep denoising structure-preserving neural encoding network (DSNet) that enables accurate classification of privacy-preserving encoded EEG representations without requiring decryption. EEG features were extracted using common spatial pattern (CSP) and transformed into privacy-preserving encoded representations while preserving their statistical structure. Here, encoding refers to a non-reversible neural transformation designed for privacy preservation rather than a formal cryptographic guarantee. Two deep learning architectures, a feedforward neural network (NN) and a recurrent neural network (RNN), were evaluated for classification in the encoded feature space. Furthermore, we integrated an LLM (GPT-4) to generate clinical-style summaries based on model outputs, enhancing interpretability for clinician review and potential clinical support use. RESULTS AND CONCLUSION: Using publicly available datasets, DSNet-NN achieved over 87% accuracy for every subject, outperforming both the RNN variant and baseline models. It also demonstrated resilience to simulated privacy attacks. LLM-generated reports provided clinician-friendly interpretations of MI predictions, supporting potential real-world applicability. This study introduces an AI framework that bridges privacy-preserving EEG decoding with LLM-based clinical reasoning, offering a practical solution for privacy-preserving neurorehabilitation and digital health systems.
Internet interventionsMarvyn R Arévalo Avalos, Junlin Chen, Tess Fairchild, Kalisha Goodwin, Janice Tsoh, Adrian Aguilera, Jason M Satterfield
Chronic pain (CP) disproportionately affects underserved populations who often experience barriers to evidence-based nonpharmacologic treatments. Digital health interventions can address these barriers by providing scalable and accessible CP management resources. However, culturally and linguistically tailored digital interventions are rare, which may limit engagement and effectiveness. The Integrating Nonpharmacologic Strategies for Pain with Inclusion, Respect, and Equity (INSPIRE) intervention combines a tailored mobile app with culturally and linguistically concordant health coaching to deliver cognitive behavioral therapy (CBT), mindfulness-based interventions (MBI), and movement-focused interventions (MFI) for CP management. This manuscript describes the process of linguistically and culturally tailoring the INSPIRE app for three target adult populations-African American/Black, Spanish-speaking Latinx, and Cantonese-speaking Chinese. Iterative tailoring was driven by multiple rounds of stakeholder focus groups followed by generative artificial intelligence (GenAI) and expert review to ensure accuracy and cultural congruence while optimizing limited resources. After initial GenAI content generation in English, the adaptation process began with surface-level adjustments in language translation and cultural representation in visual and audio elements. Deep-level adaptations incorporating culturally rooted values and beliefs about CP were made to address culturally specifically experiences with stigma and bias relevant to CP. This study highlights a replicable, efficient framework for adapting digital health interventions to improve equity and inclusion in CP management by combining AI-driven tools with human expertise to achieve optimal cultural and linguistic adaptations. Future research will evaluate the effectiveness of the INSPIRE intervention in a randomized controlled trial to assess engagement, acceptability, and improved pain outcomes across diverse populations.
Complementary therapies in medicineXin Liu, Xiaona He, Yuyue Yang, Jiayan Chen, Jun Xiong, Wei Gao
OBJECTIVE: This review evaluates the effects of wearable device-telemonitored Baduanjin on exercise tolerance and cardiac function in patients with chronic heart failure (CHF). METHODS: A comprehensive literature search was performed in PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database and Chinese Biomedical Literature Database (CBM) from their inception to 1 January 2026. The search aimed to identify randomised controlled trials investigating Baduanjin for CHF that explicitly used wearable devices. Study screening, data extraction and Cochrane RoB 2.0 bias assessment were performed independently by two reviewers with discrepancies were resolved by a third. Given significant clinical heterogeneity across the included studies, a narrative synthesis of the findings was conducted, supported by tabulated presentation of outcome data. RESULTS: Three randomized controlled trials involving 248 participants were included. Individual studies reported that wearable device-telemonitored Baduanjin was associated with improvements in several clinical outcomes in patients with CHF. Reported benefits included increased 6-minute walking distance (568.58 m vs. 367.47 m, P < 0.05), higher peak oxygen uptake (19.00 vs. 17.00 ml/[kg·min], P < 0.001) and improved left ventricular ejection fraction (52.60% vs. 45.28% and 42.79%, P < 0.05). Improvements were also observed in quality of life, depression symptoms, cardiovascular readmission in the intervention group of individual studies. No exercise-related adverse events were reported. CONCLUSION: Current evidence suggests that wearable device-telemonitored Baduanjin may potentially improve key outcomes in patients with chronic heart failure, However, these findings are based on a narrative synthesis of individual studies and should therefore be interpreted cautiously. Further high-quality, standardised randomised controlled trials are urgently needed.
Public health challengesYusuf Abdullahi Hubow, Ilyas Abdullahi Khalif, Sharmake Gaiye Bashir, Ahmed Mohamed Omar, Narura Omar Mohamed, Ayan Abdullahi Mohammed, Hibo Hassan Mohamed, No…
Primary health care (PHC) is widely recognized as the foundation of equitable health systems and is a critical pathway towards universal health coverage and improved population health. In fragile and conflict-affected settings, such as Somalia, weak PHC systems have contributed to persistently high maternal and child mortality, preventable infectious diseases, rising noncommunicable disease burdens, and profound health inequities affecting rural communities, internally displaced persons, women, and children. This narrative review examines how strengthening PHC can improve population health outcomes and advance health equity in Somalia. Drawing on peer-reviewed literature, global PHC frameworks, and Somalia-specific policy and health system evidence, this review synthesizes key challenges and opportunities across core PHC domains, including governance, financing, workforce development, service delivery, quality improvement, resilience, and community engagement. The findings highlight that fragmented governance, high out-of-pocket spending, workforce maldistribution, and limited rural and displacement-sensitive service delivery constrain PHC performance and reinforce inequality. Simultaneously, recent policy reforms, community health worker programs, and digital health innovations offer promising entry points for equity-oriented PHC transformation. The review concludes that PHC strengthening in Somalia must be pursued as a system-wide and political priority, anchored in progressive universalism and community partnerships, to deliver sustained improvements in population health while systematically reducing avoidable health disparities.
PURPOSE: Urban-rural healthcare disparities remain a global challenge, driven by the concentration of medical resources in urban centers. We developed a circulation-based model integrating medical resource allocation, education, and digital health. Since 2020, this program has been implemented in Hokkaido, Japan. This study examines its structure and outcomes. METHODS: The model includes physician and trainee rotation, structured referral pathways, community-based medical education, and digital infrastructure. A three-tier system was established: Esashi (primary/secondary care), Hakodate (tertiary center), and Sapporo (education and physician dispatch hub). Outcomes were assessed in three domains: health outcomes, financial sustainability, and educational outcomes. Educational outcomes were based on a previously published study in the same cohort. RESULTS: Health outcomes showed overall improvement, with the standardized mortality ratio decreasing from 103.4 to 98.3 in males and from 104.8 to 100.5 in females, although these changes were not statistically significant. Pneumonia-related SMR decreased significantly in both males and females. Financial indicators improved, with inpatient revenue per patient increasing significantly from 26,553 to 38,478 JPY. In addition, medical students reported increased confidence in clinical competencies. CONCLUSION: This model improved health, financial, and educational outcomes by coordinating physician mobility, tiered regional collaboration, and digital connectivity.(195words).
Clinical value is now produced in two distinct registers: one that requires physical presence, and one that does not. Performance measurement frameworks, however, were built for mainly the first. Where digital work is counted, it is rarely counted equitably; where it is counted equitably, it is rarely connected to the outcomes it produces. This structural gap, which is termed here value-time-place misalignment, gives rise to the productivity illusion: a system that appears busy, measurable and accountable, while systematically failing to capture the outcomes that it purports to deliver. Drawing on teleconsultation, artificial intelligence (AI)-supported decision-making, remote multidisciplinary teams and digital follow-up, this paper demonstrates how current metrics penalise efficiency, suppress innovation and render care increasingly illegitimate to the patients it serves. Redefining the unit of healthcare work is not a technical adjustment; it is a foundational one.
Internet interventionsMichelle Semonella, Giada Rapelli, Carlotta Rodighiero, Alberto De Luca, Gerhard Andersson, Monica Buhrman, Valeria Donisi, Giulia Landi, Chiara Manna, Ilenia …
BACKGROUND: Chronic pain (CP) is a leading cause of disability worldwide and is associated with substantial psychological, functional, and social burden. Acceptance and Commitment Therapy (ACT) has demonstrated efficacy in improving pain acceptance and functioning; however, access to psychological care remains limited. Internet-based interventions (IBIs) may help bridge this gap. To date, no ACT internet-based intervention has been developed and tested for individuals with CP in Italy. The present pilot randomized controlled trial (RCT) evaluated feasibility, acceptability, usability, and exploratory changes in pain acceptance of MobACT, a guided internet-based ACT intervention translated and adapted for the Italian context. METHODS: A two-arm pilot RCT with parallel groups (1:1 allocation) was conducted. Forty adults with CP were randomized to either the MobACT intervention (n = 20) or a waitlist control group (n = 20). The seven-week guided intervention was delivered via the Iterapi platform. Feasibility outcomes included recruitment, retention, usability, satisfaction, intervention experience, and participant feedback. The primary exploratory clinical outcome was pain acceptance, measured using the Chronic Pain Acceptance Questionnaire (CPAQ-20) at baseline (T0) and post-intervention (T1). Feasibility, usability, and participant experiences were explored through post-intervention questionnaires and semi-structured interviews analyzed using thematic analysis. RESULTS: Pain acceptance significantly improved over time across participants (p < .001), but the time × group interaction was not significant (p = .978), indicating no evidence of a differential change between MobACT and waitlist during the pilot period. Reliability of the CPAQ-20 was good at both time points (α = 0.802-0.842). Qualitative findings indicated high usability, satisfaction, and perceived applicability of ACT strategies. Participants reported increased awareness, reduced rumination, improved emotional regulation, and greater engagement in valued activities, despite limited changes in pain intensity. CONCLUSIONS: Findings support the feasibility, acceptability, and usability of MobACT as a culturally adapted internet-based ACT intervention for CP in Italy. Exploratory outcome findings should not be interpreted as evidence of efficacy; rather, they support further evaluation in a larger, fully powered RCT with more comprehensive engagement monitoring and longer follow-up.
International journal of medical informaticsWenyong Wang, Mahnaz Samadbeik, Gaurav Puri, Donald S A McLeod, Elton Lobo, Tuan Duong, Titus Kirwa, Clair Sullivan
BACKGROUND: Electronic medical records (EMRs) are widely implemented across health settings and function as sociotechnical systems that shape clinical workflows, information use, and patient-clinician interaction. While EMR impacts on clinician experience have been extensively studied, patient experience of EMR-enabled care remains underexplored. This study aims to examine patient experience in an EMR-enabled outpatient clinic and identify actionable recommendations to optimise clinic outcomes. METHODS: A cross-sectional, convergent mixed-methods survey was conducted in a fully digital public diabetes outpatient clinic in Queensland, Australia. Quantitative data, collected using the Patient Experience Monitor (PEM) Adult Outpatient short-form aligned with Picker principles, assessed patient experience across multiple outpatient care domains. Qualitative data, collected through two open-ended items, explored how patients experienced care in the context of clinician-mediated EMR use during consultations and identified opportunities for improvement. Data were collected concurrently and analysed separately. Integration occurred at the reporting stage, where qualitative findings were used to explain and contextualise the quantitative results and to inform practical recommendations. RESULTS: One hundred patients participated. Quantitative findings showed highly favourable but ceiling-affected patient experience ratings across PEM domains. Qualitative analysis identified four themes: perceived facilitation of informational continuity and coordination of care; perceived reduction in personal interaction; limited patient and GP access beyond the public hospital EMR environment; and background trust and neutral perceptions of EMR use. Integration of findings informed a set of actionable recommendations to optimise EMR-supported workflows, preserve interpersonal engagement, strengthen information continuity across care settings, and enable more participatory models of outpatient care. CONCLUSIONS: Patients perceived aspects of EMR-enabled outpatient care as supporting patient-centred care, particularly when clinicians used integrated information effectively during consultations. Findings highlight the importance of implementing EMRs as sociotechnical systems that not only align with consultation workflows but also preserve interpersonal connection and support participatory care. Achieving this requires meaningful information access and sharing across patients, clinicians, and care settings, providing practical guidance for designing digitally enabled outpatient services.
International journal of medical informaticsVanessa Pereira Corrêa Rampinelli, Ranieri Alves Dos Santos, Ianka Cristina Celuppi, Gabriel Norde Santos, Jades Fernando Hammes, Célio Luiz Cunha, Raul Sidnei…
BACKGROUND: The Fast Healthcare Interoperability Resources (FHIR) standard is a global benchmark for digital health data exchange. Despite its widespread adoption, the scientific literature on the methodological processes for creating FHIR Implementation Guides (IGs) remains fragmented and lacks systematization. OBJECTIVE: This scoping review aims to synthesize the scientific literature on the process of developing FHIR IGs for electronic health records, identifying methodological steps, toolchains, governance patterns, and critical gaps that limit clinical adoption. METHODS: Following JBI and PRISMA-ScR guidelines, a comprehensive search was conducted across nine databases in August 2025. From an initial 5,552 records, eleven studies published between 2021 and 2025 were selected for analysis. Data extraction focused on development stages, team composition, authoring tools, and validation workflows. RESULTS: The study identified a synthesized seven-step implementation lifecycle: requirements, modeling, terminology, narrative documentation, technical validation, clinical validation, and publication. A significant methodological shift toward "Infrastructure as Code" was observed, with frequent use of FHIR Shorthand (FSH) and Continuous Integration/Continuous Deployment (CI/CD) pipelines, particularly in European national initiatives. While technical validation was nearly universal (10 out of 11 studies), clinical validation was inconsistently addressed (7 out of 11 studies), often relegated to future work, resulting in IGs that are syntactically correct but insufficiently aligned with real-world clinical workflows. Narrative documentation, essential for non-technical stakeholders, was reported as comprehensive in only four studies, limiting broader clinical adoption. All studies reported multidisciplinary team involvement, confirming that IG development is fundamentally an exercise in clinical governance and consensus. CONCLUSION: The creation of FHIR IGs has evolved into a complex discipline requiring a convergence of software engineering, clinical semantics, and institutional governance. This review advances beyond existing FHIR literature by providing the first systematic synthesis focused specifically on the IG creation process, presenting a replicable seven-step cycle that can guide implementers, researchers, and policy makers. Closing the gap between technical readiness and clinical applicability remains a critical challenge. Future research should prioritize ongoing clinical validation, the establishment of standardized reporting frameworks for IG development, and the integration of generative AI tools to enhance narrative documentation and terminology binding.
ESMO real world data and digital oncologyD Pesántez, G Fucà, A Magrì, L Koulai, K Bliznashki, A Soltani, M Khan, F Multari, M Moschetta
BACKGROUND: Early-phase oncology trials involve complex protocols and extensive documents, making timely resolution of study queries challenging. We developed the Study Document Assistant (SDA), a retrieval-augmented generation (RAG) system that integrates semantic search with large language models to generate context-specific answers from clinical trial documentation. MATERIALS AND METHODS: SDA processes study documents and delivers responses through a secure, conversational interface. A two-arm experiment was conducted in which sponsor clinical study team members answered protocol-related queries either with or without SDA. Questions were stratified by difficulty and assessed by blinded subject matter experts (SMEs) and artificial intelligence (AI) models. The primary endpoint was mean response time. Main secondary endpoints included response time as a time-to-event outcome and overall accuracy. SDA user satisfaction was also assessed. Data were analyzed using Welch t-test for the primary endpoint, Kaplan-Meier method and log-rank test for time-to-event analysis, Mann-Whitney U test for accuracy, and descriptive statistics for satisfaction. RESULTS: In the experiment (N = 10 per arm), SDA users achieved a mean response time of 14.9 [95% confidence interval (CI) 9.3-20.6] versus 26.5 (95% CI 16.8-36.1) minutes in controls, corresponding to a 43.8% reduction (95% CI 11.9% to 64%, P = 0.0347). A similar reduction for median time to response was observed. Accuracy, measured as the median SME score (scale 1-4), was ∼3 ("Mostly Correct") for both arms, with no statistically significant difference. Evaluation by AI models showed similar results. CONCLUSIONS: Our findings demonstrate that SDA accelerates query resolution without compromising answer quality, highlighting the potential of RAG-based digital assistants to streamline clinical trial operations and enhance research efficiency.
Surgery open scienceMaud Reynier, Sarah Shank, Matthew Venegoni, Matthias Regling, Arthur de Gast
BACKGROUND/HYPOTHESIS: Preoperative planning software has gained traction in shoulder arthroplasty, enabling surgeons to better visualize patient's anatomy and optimize implant positioning. Widespread adoption of such tools depends not only on their efficacy but also on surgeon satisfaction and perceived utility in day-to-day practice. However, data on surgeons' satisfaction and perceived utility of such software remain limited. This survey aimed to evaluate surgeons' overall satisfaction, perception and the willingness to recommend the software as a training tool for fellows. MATERIALS AND METHODS: A retrospective observational survey was conducted to evaluate overall satisfaction and usage patterns among orthopedic surgeons using pre-operative 3D planning software (Blueprint®). All surgeons were contacted via email with a web-based questionnaire. Reponses were analyzed with descriptive statistics to assess overall surgeon satisfaction, level of agreement with predefined statements, likelihood of future use and willingness to recommend the software to others. RESULTS: The web-based questionnaire was distributed to 1100 orthopedic surgeons between September 30, 2024, and November 11, 2024. 312 responses were received, of which 273 were evaluable responses. Most respondents were low-volume or medium-volume surgeons, and high-volume surgeons were underrepresented (<7.7%). 270 responses were collected from surgeons evaluating their overall satisfaction, with 97% of the feedback being positive. 96% of surgeons said the planning software boosted their confidence in their preoperative plan and 33% during surgery, and 86% reported lower stress compared to performing the procedure without it. CONCLUSIONS: This survey suggests that pre-operative 3D planning software (Blueprint®) is a well-received digital solution in shoulder arthroplasty, with perceived benefits regarding surgical planning, surgeon's stress level, confidence and training.
Global health research and policyChen Chen, Jialong Tan, Luiz Andrade, Garibaldi Gurgel, Ivana Barreto, Jian Wang
Primary health care (PHC) is fundamental to achieving universal health coverage and health equity, yet building sustainable PHC systems remains a global challenge. This commentary compares the contrasting yet complementary experiences of Brazil and China along four analytical dimensions: community embeddedness, financial protection and sustainability, continuity of care and coordination across levels, digital support and its dual equity effect. Brazil's Family Health Strategy (FHS), rooted in community-based multidisciplinary teams and a rights-based framework, has significantly reduced mortality from preventable conditions and expanded access for marginalized populations, but faces sustainability threats from underfunding and political instability. China, by contrast, has adopted a state-driven, technologically enabled approach, leveraging telemedicine, electronic records, and AI-enabled tools to scale up PHC. Despite impressive coverage and financial protection, China struggles with limited public trust in frontline providers, fragmented care continuity, and a notable dual pattern in digital health: telemedicine has helped narrow the rural-urban gap, while the gap between younger and older users has widened. Drawing on recent policy documents and empirical studies, we distinguish broadly transferable principles from resource-intensive pathways, offering low- and middle-income country (LMIC) policymakers an integrative framework that prioritizes human-centered relational care reinforced by context-appropriate digital tools, predictable financing, and strong referral linkages within an equity-focused PHC foundation.
BACKGROUND: Ethiopia's health system faces a triple burden of infectious diseases, notably tuberculosis (TB), non-communicable diseases (NCDs), and injuries, challenging service delivery in resource-limited settings. METHODS: We conducted a mixed-methods analysis of TB program performance and health system determinants across 112 Ethiopian health care facilities using a historical baseline dataset (2010-2011). We integrated quantitative data (spatial analysis and mixed-effects logistic regression) with qualitative insights (policy analysis and stakeholder interviews), adhering to RECORD and COREQ guidelines. RESULT: Pediatric TB detection was critically low (2.1% vs. WHO's 12%), and treatment success varied significantly by facility type (hospitals: 88.2%; primary health care units [PHCUs]: 63.8%; chi^2 = 34.2, p < 0.001). Key system bottlenecks included low staff density (0.7/1000) and supply chain interruptions strongly correlated with treatment failure (r = 0.72). Qualitative triangulation revealed that diagnostic uncertainty and irregular supervision directly compounded these institutional gaps. INTERPRETATION: We propose a "Five-Pillar Framework" diagnostic strengthening, community systems, supply chain reform, digital health, and governance improvements to advance universal health coverage (UHC). While based on foundational baseline data, these findings offer a transferable model for low- and middle-income countries (LMICs).