Oxford open digital health最新文献

{"title":"An artificial intelligence-based chatbot as a tool for promoting nutrition in a community setting.","authors":"Rajabu Simba, Gilbert Charles, John B Uiso, Jacqueline Wetson, Hyasinta Jaka, Leonard Katalambula","doi":"10.1093/oodh/oqag037","DOIUrl":"https://doi.org/10.1093/oodh/oqag037","url":null,"abstract":"<p><p>Malnutrition remains a major public health problem in Tanzania, worsened by limited access to personalized, culturally relevant nutrition information. Existing gaps in community nutrition education across sub-Saharan Africa, combined with conventional approaches ignoring individual dietary needs, contribute to undernutrition and chronic disease. However, while AI-powered chatbots have shown global effectiveness in scalable health education, evidence from low-resource, Swahili-speaking settings is scarce. This study, aligned with Sustainable Development Goals (SDGs) 2, 3, and 4, developed Lishe Yetu, a culturally localized digital nutrition tool aimed at bridging these gaps. A pre-post quasi-experimental mixed-methods design evaluated Lishe Yetu among 400 Tanzanian residents between January and April 2025. Built on retrieval-augmented generation using GPT-3.5-turbo, the platform drew from over 2500 expert-reviewed sources including World Health Organization (WHO), Food and Agriculture Organization of the United Nations (FAO), Tanzania Food and Nutrition Centre, and validated Swahili materials. Nutritional knowledge was measured using a validated 20-item questionnaire, with engagement tracked via server logs and satisfaction assessed through Likert-scale surveys and thematic analysis of qualitative feedback. Results showed strong engagement, with average sessions lasting 12 minutes and 15.2 messages exchanged; 87% completed at least one full session. Satisfaction averaged 4.3/5.0, and 88% found the tool easy to use. Knowledge scores improved significantly from 52% to 73%, a 21 percentage-point gain with a large effect size (Cohen's d = 1.57, <i>P</i> < 0.001). Additionally, 65% reported intentions to adopt healthier diets. These findings provide strong preliminary evidence that a Swahili-language AI chatbot can improve nutrition literacy in low-resource African settings, though randomized controlled trials are needed to confirm sustained behaviour change.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag037"},"PeriodicalIF":0.0,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13636458/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149122497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surviving institutional contradictions: routine data use practices at the subnational levels.","authors":"Bigten Kikoba, Merina Luambano, Masoud Mahundi, Wilfred Senyoni","doi":"10.1093/oodh/oqag036","DOIUrl":"10.1093/oodh/oqag036","url":null,"abstract":"<p><p>Routine Health Information System data are widely promoted as a foundation for evidence-informed planning, supervision, and service improvement in low- and middle-income countries. Yet their use in decentralized health systems is often shaped by contradictory institutional logics. In this study, contradictory institutional logics refer to conflicting expectations about what actors should prioritize, how data should be used, and which resources are made available to do so. We examined how these contradictions shape routine data use at subnational levels of the Tanzanian health system and how local actors respond to them. We conducted a qualitative study in the Dodoma City Council and the Bahi District Council, Tanzania, between 2024 and 2025. Data were generated through 31 key informant interviews and nonparticipant observations across 12 purposively selected health facilities and two council health management teams. Participants included facility in-charges, health management information system focal persons, facility programme coordinators, and council program coordinators. Data were analyzed thematically using institutional theory as an interpretive lens. The findings from the two councils reveal that routine data use was not absent; rather, it was improvised within a contradictory institutional environment. Strengthening data use, therefore, requires more than technical deployment. It requires institutionalized procedures for review and supervision, broader analytic capacity at the facility level, better alignment between DHIS2 and GoT-HOMIS, and target-setting and feedback practices that are meaningful to local service realities. These findings are analytically relevant to similar decentralized settings, although they are not statistically generalizable beyond the study context.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag036"},"PeriodicalIF":0.0,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13622350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149083553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telehealth to reduce compound pressures on the National Health Service and social care: a multi-methods study protocol.","authors":"Jennifer Downing, Rosie Kaur, Saddaf Naaz Akhtar, Elizabeth M Camacho, Konstantinos Daras, Anna Cooper, Thais Caprioli, Yuxuan Yang, Brendan Collins, Peter Almond, Wesam Baker, Hilary Garret, Patricia Jamal, Benjamin Barr, Anthony G Marson, Eduard Shantsila","doi":"10.1093/oodh/oqag032","DOIUrl":"10.1093/oodh/oqag032","url":null,"abstract":"<p><p>Telehealth and remote monitoring are increasingly used in the management of long-term health conditions and can improve access to care. The Mersey Care Telehealth Service (MCTS) provides technology-enabled support for people with heart failure, diabetes, and chronic obstructive pulmonary disease. The service has been operating for over a decade; however, the COVID-19 pandemic has led to its rapid expansion. This study aims to gather evidence on the impact of the MCTS, explore barriers and enablers to effective service delivery and evaluate its cost-effectiveness. This study comprises of four work packages (WP). WP1: A retrospective observational analysis to evaluate whether the MCTS is associated with reduced unplanned healthcare utilisation and to examine how outcomes vary by sociodemographic characteristics and service delivery type; WP2: Longitudinal analyses to compare patient-reported outcomes, including mental health, quality of life, and wellbeing, between telehealth users and a comparator group of non-users who meet the eligibility criteria for telehealth; WP3: Remote semi-structured interviews with MCTS staff and patients will be held to explore the barriers and enablers influencing the effective service delivery; WP4: An economic evaluation will determine whether the MCTS is cost-effective compared with usual care, and will assess how cost-effectiveness varies by patient characteristics and service delivery type. This multi-method evaluation will provide robust and comprehensive evidence of the impact, equitable delivery, implementation approach, and cost-effectiveness of the MCTS. Insights seek to inform service improvement, commissioning decisions, and future telehealth strategy within the NHS.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag032"},"PeriodicalIF":0.0,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13592275/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149019469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maintenance dynamics in digital health public goods: a quasi-experimental study of issue resolution during the 2025 USAID funding disruption.","authors":"Jinyou Sheng, Amy Finnegan","doi":"10.1093/oodh/oqag035","DOIUrl":"10.1093/oodh/oqag035","url":null,"abstract":"<p><p>Open-source digital public goods play a growing role in point-of-care health service delivery in low- and middle-income countries. Many of these systems are developed and maintained by organizations that rely heavily on donor funding, making their long-term sustainability vulnerable to funding instability. The January 2025 U.S. Agency for International Development funding freeze created a rare natural experiment to observe how different organizations maintaining these systems respond under external funding shocks. Using 7922 issues from eight repositories created between June 2023 and June 2025, a DistilBERT model was fine-tuned to classify bug severity. Organizations were categorized into three funding-based models: donor-driven (primarily grant-funded), revenue-driven (sustained through commercial or internal investment), and hybrid (combining grants and revenue). Interrupted time series and Cox proportional hazards models were then applied to evaluate changes in bug-resolution efficiency. Revenue-driven organizations did not exhibit a statistically significant immediate level change but experienced significant deterioration in the post-intervention period. Donor-driven organizations exhibited no substantial changes following the intervention, maintaining stable baseline levels. Hybrid organizations showed resilience to the immediate funding shock, with a gradual decline in bug resolution as time went on after the shock. These findings suggest that the funding shocks function as a stress test for digital public goods and highlight the resilience advantages of various governance models.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag035"},"PeriodicalIF":0.0,"publicationDate":"2026-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13617568/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149077202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Governing digital health transformation in South Africa: are policies, standards, and legislation fit for purpose?","authors":"Mandisa Msomi, Ngoako Marutha","doi":"10.1093/oodh/oqag033","DOIUrl":"10.1093/oodh/oqag033","url":null,"abstract":"<p><p>This study examines the legislative and regulatory governance mechanisms influencing digital health transformation within Provincial Departments of Health in South Africa. It aimed to evaluate the effectiveness of existing legislative, regulatory, and policy frameworks in supporting digital health implementation and to develop a Provincial Digital Health Governance and Implementation Model to strengthen governance across provincial health departments. A qualitative multiple case study design, underpinned by the interpretivist paradigm, was employed. Data were collected through semi-structured interviews with Chief Information Officers and Information and Communication Technology (ICT) Managers from six Provincial Departments of Health and complemented by content analysis of key legislative, regulatory, and policy documents. Data were analysed thematically. The findings indicate that South Africa has established comprehensive legislative, regulatory, and policy frameworks to support digital health transformation; however, implementation remains inconsistent across provinces. Although these frameworks provide a foundation for digital health governance, their effectiveness is constrained by weak implementation mechanisms, limited institutional capacity, inconsistent ICT governance, inadequate infrastructure, insufficient digital skills, fragmented interoperability, and uneven compliance with information governance and information security standards. The study demonstrates that the principal challenge is not the absence of legislative and policy frameworks, but the governance capacity required for effective implementation. In response, the study proposes a Provincial Digital Health Governance and Implementation Model that integrates legislative and regulatory frameworks, health standards, institutional policies, governance structures, and implementation mechanisms to strengthen coordination, accountability, interoperability, regulatory compliance, and institutional readiness. The study contributes to digital health governance literature by providing a contextually relevant governance framework to support sustainable digital health transformation within South Africa's provincial healthcare system.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag033"},"PeriodicalIF":0.0,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13592159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149019441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging digital pathology to enhance breast cancer diagnosis in low-resource settings: a cross-sectional study of major histopathology laboratories in Uganda.","authors":"Agnes R Semwanga, James Serubugo, Vincent M Kiberu, Hawa Nalwoga, Evelyn K Kahiigi, Nazarius M Tumwesigye, Sam Kalungi","doi":"10.1093/oodh/oqag034","DOIUrl":"10.1093/oodh/oqag034","url":null,"abstract":"<p><p>Breast cancer remains a leading cause of morbidity and mortality among Ugandan women, particularly in rural areas where pathology infrastructure and specialist access are limited. This study aimed to improve diagnostic efficiency and accuracy by digitizing breast cancer slides and implementing a web-based histopathology system to support remote diagnostics. A total of 100 glass slides from core breast biopsy samples were digitized using an Aperio AT2 slide scanner. A web-based breast histology information management system (BHIMS) was developed to store and provide remote access to these digital slides. Two experienced pathologists independently evaluated the slides using both conventional microscopy and the digital platform. Assessments focused on key morphological features, including cancer diagnosis, type, grade, mitosis, lymphatic invasion, nuclear pleomorphism, and tubule formation. Inter- and intra-observer agreement was analyzed using kappa statistics. Digital pathology showed high inter- and intra-observer reliability, particularly for cancer diagnosis and type. Slightly lower agreement was noted for nuanced features such as mitosis and lymphatic invasion. Conventional microscopy yielded stronger observer agreement and confidence, especially for mitotic count and invasion. Digital pathology offers a promising approach to improve breast cancer diagnosis in resource-limited settings. The BHIMS system enabled remote access and collaborative review of cases, supporting decentralized pathology services. However, broader adoption will require investment in high-resolution scanners, reliable internet, data storage, and training of pathologists. With these enhancements, digital pathology could significantly strengthen cancer care delivery in rural Uganda.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag034"},"PeriodicalIF":0.0,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13595349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149027021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of patient-facing digital health interventions on patient safety outcomes: a meta-analysis of meta-analyses.","authors":"Goran Erfani, Jemma McCready, Beckie Gibson, Alison Steven, John Unsworth, Heidi Siira, Erika Jarva, Kristina Mikkonen, Marco Tomietto","doi":"10.1093/oodh/oqag031","DOIUrl":"10.1093/oodh/oqag031","url":null,"abstract":"<p><p>Patient safety is a critical concern in healthcare, with preventable adverse events contributing significantly to morbidity and mortality. Digital health interventions (DHIs) are increasingly integrated into healthcare systems to improve patient safety outcomes. However, their effectiveness remains unclear. This study focuses on DHIs adopted by patients and, in detail, it aims to assess the effectiveness of patient-facing DHIs in improving patient safety outcomes, including medication adherence, healthcare utilization, falls, mortality, adverse events, relapse rate, and readmissions. This meta-analysis of meta-analyses follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, and it is registered in PROSPERO. The eligible meta-analyses were identified across major databases (PubMed, Web of Science, Cochrane Reviews, EPISTEMONIKOS, CINAHL, ProQuest, Scopus, PsychARTICLES) from 2010 until 2024. The quantitative synthesis adopted a random-effects model. The corrected covered area method quantified the studies' overlap and heterogeneity was assessed using the I² statistic. Publication bias was examined using Egger's test. The JBI Critical Appraisal Checklist was adopted. In total, 72 meta-analyses were included. Findings indicate that patient-facing DHIs improve medication adherence (SMD = 0.33; 95% CI = 0.22-0.44), reduce mortality risk (RR = 0.84; 95% CI = 0.78-0.90) and hospital readmissions (RR = 0.90; 95% CI = 0.81-0.98). Additionally, patient-facing DHIs reduce fall risk among older adults (SMD = 0.30; 95% CI = 0.13-0.46). However, the impact on healthcare utilization reported increased patient visits, while relapse rate (RR = 1.00; 95% CI = 0.87-1.16) and adverse events (RR = 0.94; 95% CI = 0.66-1.34) showed no significant association with patient-facing DHIs. While these digital solutions demonstrate the potential to enhance medication adherence, reduce mortality, and prevent falls, their effectiveness varies. Challenges such as usability issues, digital literacy gaps, and infrastructure limitations should be addressed to optimize patient safety outcomes.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag031"},"PeriodicalIF":0.0,"publicationDate":"2026-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13587088/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming perinatal health with AI-predictive models in precision and digital innovations for maternal and fetal well-being: a systematic review.","authors":"Shahrzad Kaveh, Zahra Khedri, Solmaz Sohrabei","doi":"10.1093/oodh/oqag020","DOIUrl":"https://doi.org/10.1093/oodh/oqag020","url":null,"abstract":"<p><p>The convergence of artificial intelligence (AI) and wearable monitoring devices is revolutionizing the management of high-risk pregnancies, offering unprecedented opportunities for early detection, personalized care, and improved outcomes. These technologies address critical challenges in maternal and fetal health, especially in resource-limited settings, by enabling proactive and continuous care. This systematic review specifically focuses on the integration of artificial intelligence and wearable devices for managing high-risk pregnancies and highlights regulatory and ethical challenges. Databases like PubMed (Medline), Scopus, and Web of Science were explored for pertinent studies (from 2015 to 2024). Articles were chosen based on specific inclusion and exclusion criteria, and essential data including technology type, AI algorithms employed, and their influence on perinatal care were collected. The Risk of Bias in the studies was evaluated utilizing standard assessment tools such as PROBAST+AI, and study quality was assessed with TRIPOD+AI. Ultimately, the findings were examined through narrative analysis, leading to the identification of challenges and future research directions. This systematic review examined 16 studies focusing on the application of AI and digital innovations in maternal and fetal healthcare. The studies investigated various AI techniques, including machine-learning models for predicting risks to maternal health, deep learning for monitoring fetal well-being, and wearable sensor technologies for remote health tracking. Many studies produced encouraging outcomes, with AI models reaching high levels of accuracy in early detection, risk assessment, and real-time patient monitoring. However, issues such as dataset biases, generalizability, and ethical concerns continue to pose significant challenges. Additional research is necessary to validate these AI-driven methods across diverse populations to ensure equitable and effective healthcare outcomes. The integration of technologies has the potential to significantly improve the management of high-risk pregnancies. However, a critical regulatory gap exists that must be addressed to ensure that these technologies are used ethically, safely, and effectively. This will involve the development of new regulatory frameworks, a focus on transparency and accountability, and a commitment to addressing bias and data security to provide the best care possible. AI has the potential to transform maternity services by improving risk prediction, enabling remote monitoring, and supporting clinical decisions. However, realizing this potential requires addressing limitations related to data quality, algorithm accuracy, user privacy, and ethical considerations.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag020"},"PeriodicalIF":0.0,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13483983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148804960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TikTok as a source of information for migraine: a content quality analysis.","authors":"Isabella M de Jesus, Regor David N Balonga, Liamuel Giancarlo V Untalan, Roland Dominic G Jamora","doi":"10.1093/oodh/oqag019","DOIUrl":"10.1093/oodh/oqag019","url":null,"abstract":"<p><p>Migraine is one of the most common neurological conditions affecting people worldwide. Migraine is the second leading cause of the global burden of neurological diseases. Studies have found the information on TikTok on migraine to be inaccurate, yet it has been a source of health information among the public. The objective of the study was to describe the TikTok videos discussing migraine, to evaluate its content in terms of reliability, quality, and understandability, and investigate the factors of these videos. A search was conducted using the keyword '#migraine' and the top videos were assessed by two independent raters. Video parameters such as type of uploader, views, likes, comments, shares, and duration were also collected. The evaluated videos had low quality and reliability on the Global Quality Scale (GQS) and the modified DISCERN tool, with low understandability and actionability. Higher scores overall in Patient Education Materials Assessment Tool (PEMAT) showed a positive correlation with higher scores on the GQS. Video length (in seconds) had a positive correlation with GQS and PEMAT scores [length with GQS <i>r</i> = 0.393 (<i>P</i> < .001); length with PEMAT Total <i>r</i> = 0.420 (<i>P</i> < .001)]. TikTok videos on migraine were found to be of low quality, reliability, and understandability. These findings highlight the role of social media in contributing to the health illiteracy of its audiences, further lobbying that healthcare institutions should create official social media accounts to spread reliable health information to the public on migraines.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag019"},"PeriodicalIF":0.0,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13502392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148815457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effectiveness of the diversion of patients from an emergency department waiting room to a virtual medical consultation.","authors":"Jennie Hutton, Clare Matheson, Suzanne Miller, Jason Talevski, Rebecca L Jessup, Adam I Semciw, James H Boyd, Hayley Gray, Abbey Gwyther-Jones, Vivienne King, Joanna Lawrence, Loren Sher","doi":"10.1093/oodh/oqag018","DOIUrl":"10.1093/oodh/oqag018","url":null,"abstract":"<p><p>The increase in number of presentations to Emergency Departments (EDs) has continued to contribute to poor health outcomes worldwide. The diversion of suitable patients from the waiting room to receive a virtual medical consultation potentially addresses this problem. This retrospective study was undertaken at a metropolitan ED utilizing the public state-wide Victorian Virtual Emergency Department (VVED) service. Nonurgent patients were identified and offered services in a soundproof room adjacent to the waiting room. The proportions of successful diversions from the physical ED and subsequent presentations in the following 7 days were reported. A review of all representations to the hospital was undertaken via a modified Institute of Healthcare Improvement framework. A total of 339 patients were treated via this pathway, resulting in 258 (76%) of patients being diverted from the ED. Eighty-one (24%) participants were advised to visit the ED as planned. A total of 206 participants (61%) had no further contact with the VVED or the ED. A total of 20 (6%) patients undertook a subsequent VVED consultation, and 30 (9%) presented to the ED in ˂7 days and two were directly admitted to a short-stay unit. Twelve patients had hospital admissions of ˂7 days, and no deaths were reported. In the case reviews, three patients were identified as having an adverse event resulting in temporary harm. Virtual consultation services can be integrated into the ED waiting room, resulting in the successful diversion of patients with a small number of adverse events.</p>","PeriodicalId":520498,"journal":{"name":"Oxford open digital health","volume":"4 ","pages":"oqag018"},"PeriodicalIF":0.0,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13386168/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148551982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}