{ "version": "https://jsonfeed.org/version/1", "title": "Digital Health Evidence (most recently added)", "home_page_url": "http://www.digitalhealthevidence.net/", "feed_url": "http://www.digitalhealthevidence.net/feed/added/json", "description": "The most recently added Digital Health evidence", "icon": "http://www.digitalhealthevidence/logo_horizontal_small.png", "author": { "name": "James BonTempo", "url": "https://www.linkedin.com/in/jamesbontempo/" }, "items": [ { "id": "http://doi.org/10.1136/military-2026-003524", "content_html": "", "url": "http://doi.org/10.1136/military-2026-003524", "title": "Operational evaluation of offline voice interpretation to support deployed military medical care: a UK Defence operational pilot.", "summary": "Operational evaluation of offline voice interpretation to support deployed military medical care: a UK Defence operational pilot. - BMJ military health", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Cumpsty, R; Offord, M; Yerelian, D; Sharp, W; Pynn, H", "url": "https://orcid.org/0009-0006-3501-0198" } }, { "id": "http://doi.org/10.1016/j.ccc.2026.07.010", "content_html": "Intensive care is defined by providing a higher level of patient monitoring, but only a fraction of the data created through continuous hemodynamic monitoring are captured in the electronic health record. The monitoring data that is captured misses clinically important deterioration events and is not adequate to represent critical illness physiology for care at the bedside or for research. This article describes the current state of patient monitoring in intensive care, advanced monitors in development, metadata and its role in creating rich intensive care data sources, and machine learning and its current and future applications in intensive care medicine. ", "url": "http://doi.org/10.1016/j.ccc.2026.07.010", "title": "Intensive Monitoring, Big Data, and Artificial Intelligence in Critical Care.", "summary": "Intensive Monitoring, Big Data, and Artificial Intelligence in Critical Care. - Critical care clinics", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Rzewnicki, DI; Bhavani, SV", "url": "http://emory.edu" } }, { "id": "http://doi.org/10.1111/1742-6723.70392", "content_html": "To describe fibrinogen concentrate (FC) supply across Queensland Health. Statewide FC supply from January 2016 to September 2026 was analysed by service type, geography, major trauma designation, viscoelastic haemostatic assay (VHA) availability and temporal trends. Of 24,717 g FC supplied, 97.0% was distributed to 54 hospitals, 2.0% to retrieval services and 1.0% to ambulance services. Of hospital supply, 25.4% reached regional and 6.1% remote/very remote hospitals; 66.2% was supplied to major trauma services and 92.9% to VHA-capable hospitals. Population-adjusted FC supply increased from 8.19 to 59.2 g per 100,000 population between 2016 and 2025. FC supply has increased substantially across Queensland, extending to regional, remote and prehospital services. This highlights the value of statewide patient-level utilisation data for haemovigilance. ", "url": "http://doi.org/10.1111/1742-6723.70392", "title": "Supply of Fibrinogen Concentrate Across Queensland Health.", "summary": "Supply of Fibrinogen Concentrate Across Queensland Health. - Emergency medicine Australasia : EMA", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Latona, A; Brennan, R; Pothulu, P; Casey, J; Ho, A; Mitra, B", "url": "https://orcid.org/0000-0003-4275-2588" } }, { "id": "http://doi.org/10.1016/j.preteyeres.2026.101539", "content_html": "Slit-lamp colour photography remains a cornerstone of anterior segment documentation and longitudinal monitoring. However, conventional slit-lamp photography has seen relatively limited technological advancement compared with the rapid development of quantitative anterior-segment modalities such as AS-OCT, Scheimpflug tomography and confocal microscopy. Despite the wide diffusion of digital cameras, smartphones, and high-end slit-lamp systems, ocular surface photography (OSP) remains hampered by the absence of standardised acquisition and processing protocols. The convex, aspheric geometry of the ocular surface, off-axis illumination, peripheral defocus, automatic colour correction, and pupil-driven exposure variation in retroillumination limit reproducibility, inter-device comparability, and clinical utility. In this review we critically appraise current OSP applications across major ocular surface conditions (dry eye disease, conjunctival hyperaemia, infectious keratitis, ocular surface burns, and ocular surface neoplasia), mapping the hardware, software, and reproducibility limitations that constrain clinical practice. We then examine how these limitations propagate into artificial intelligence (AI) development, where the absence of large, well-annotated, demographically diverse OSP datasets, together with the lack of reproducible quantitative phenotypes and reliable labels, is now the principal bottleneck to clinically deployable models; we discuss patient-level data partitioning and external validation, and outline how deep learning, federated learning and foundation models can both utilise and improve OSP. Finally, we propose a minimum acquisition and dataset specification, tiered by clinical setting from research to community screening, and a staged roadmap that combines hardware standardisation (focus-stacked, illumination-controlled, colour-calibrated acquisition), interoperable metadata-rich storage (DICOM where infrastructure permits), quantitative phenotype definition, and diverse international dataset collaborations, so that the ocular surface can benefit from quantitative imaging and AI as other areas of ophthalmology have begun to. ", "url": "http://doi.org/10.1016/j.preteyeres.2026.101539", "title": "Standardising ocular surface photography for artificial intelligence: current limitations and a proposed roadmap.", "summary": "Standardising ocular surface photography for artificial intelligence: current limitations and a proposed roadmap. - Progress in retinal and eye research", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Romano, V; Steger, B; Airaldi, M; Giuliano, F; Ferrara, M; Romano, D; Romano, MR; Zheng, Y; Ting, DSJ", "url": "http://unibs.it" } }, { "id": "http://doi.org/10.1111/1475-6773.70183", "content_html": "To estimate the effect of tele-emergency care (TEC) on emergency department (ED) use, downstream care, and costs among patients triaged as needing urgent evaluation. We studied TEC within the Veterans Health Administration (VHA) using a regression discontinuity design that exploited brief, routine operational pauses in TEC availability. Patients who called a nurse advice line shortly before a pause were substantially more likely to receive TEC than otherwise comparable patients who called shortly after the pause began. We used VHA records, including VA-provided and VA-paid community care encounters, for 35,249 nurse triage calls with an urgent recommendation placed during business hours at VA facilities offering TEC between December 2023 and June 2025. Calling just after a pause began raised the probability of an ED visit within 3 days by 7.5 percentage points (baseline, 45.8%). Scaling by the first stage, TEC reduced ED visits within 3 days by 27.5 percentage points, with the reduction concentrated at VA-paid community care facilities (-18.4 percentage points). TEC increased primary care visits within 7 days by 9.3 percentage points. Thirty-day mortality and inpatient admission were unchanged. Total 30-day health care costs were not significantly different (+$983 per recipient; SE, $822). Tele-emergency care reduced avoidable ED visits and redirected patients toward primary care without detectable effects on mortality or admission. Health systems should consider TEC to redirect avoidable ED visits. ", "url": "http://doi.org/10.1111/1475-6773.70183", "title": "Tele-Emergency Care Reduced Emergency Department Visits and Shifted Care to Primary Care Settings in the Veterans Affairs System.", "summary": "Tele-Emergency Care Reduced Emergency Department Visits and Shifted Care to Primary Care Settings in the Veterans Affairs System. - Health services research", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Rose, L; Tran, LD; Urech, TH; Li, KY; Vashi, AA", "url": "https://orcid.org/0000-0001-7195-2939" } }, { "id": "http://doi.org/10.1016/j.gerinurse.2026.104405", "content_html": "The present study explored older adults' experience in using herbs and to identify the need for nurse involvement. A descriptive qualitative study was conducted to investigate older adults' experience using herbs, their reasons for choosing them, and the methods of use. Twelve participants aged 60 years and older who use herbs were interviewed in this study. The Braun and Clarke's six-step reflexive thematic analysis framework was applied to process and evaluate data. The study also used the ATLAS.ti program to organize, analyze, visualize, and present the research findings. Three themes were identified, conveying seven sub-themes: (1) The source of herbal use information, (2) considerations for using herbs, and (3) challenges during herb use. The source of information was the media, family/relatives, and health facilities. Older adults considered the purpose and reason to choose herbs over prescription drugs when deciding to use herbs. In addition, there was a harbor concern of the long-term consequences of consuming prescription drugs. Nurses needed to ensure that older adults had adequate e-health literacy skills to filter and select valid herbal information including discussion of using herbal experience for treatment. On the other hand, they are required to have sufficient knowledge of recommended herb usage through formal training. They should also provide time to explore herb usage among older people during nursing assessment. Openly acknowledge and encourage discussion to ensure safe interaction of herb usage and prescribed drug will promote successfulness of disease management among older people. ", "url": "http://doi.org/10.1016/j.gerinurse.2026.104405", "title": "Exploring herb use among community-dwelling older adults: A qualitative study.", "summary": "Exploring herb use among community-dwelling older adults: A qualitative study. - Geriatric nursing (New York, N.Y.)", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Irwan, AM; Bahtiar, B; Fatmawati, S; Suhartini, S; Astuti, MD; Amalia, R; Syahrul, S", "url": "http://med.unhas.ac.id" } }, { "id": "http://doi.org/10.2196/64941", "content_html": "Smartphone-delivered travel-record and health-code systems were deployed across China during the COVID-19 pandemic to classify risk based on travel history and regulate access to venues and travel. The geographic classification rule is a key design choice for these systems. A city-boundary rule (city-cut) is administratively convenient but may group areas with different mobility patterns under one risk label, whereas a fixed-radius rule (radius-cut) offers greater spatial precision but may exclude more distant areas connected by routine travel. Whether a classification rule aligns with observed mobility is a design question distinct from evaluating a deployed system's epidemiological effects. This study examined whether observed mobility in Shanghai supported a city-cut or a radius-cut geographic design for a mobile health travel-record system and whether mobility-derived communities corresponded to administrative districts. We conducted a retrospective observational analysis of 1.44 billion deidentified China Unicom mobility records collected for two 46-day periods in 2019 and 2020. The analytical unit was the daily origin-area movement proportion. We calculated within-Shanghai, confirmed external-city, and nonadjacent-district movement proportions; for each origin area, we paired them by calendar day. We constructed grid-level transition matrices, used spectral clustering followed by k-means++, and checked the groupings across repeated initializations and selected dates. Across 46 daily city-average observations in 2019, the intracity proportion was 97.2% (95% t CI 97.1%-97.3%). Nonadjacent-district movement was 13.7% (95% t CI 13.5%-13.9%), compared with 2.8% (95% t CI 2.7%-2.9%) for confirmed external-city movement. A paired, 2-tailed Newey-West heteroskedasticity- and autocorrelation-consistent (HAC) t test (α=.05) gave a mean difference of 10.9 (95% HAC CI 10.7-11.1; P<.001) percentage points. At the Chongming border, the corresponding difference was -3.1 (95% HAC CI -4.1 to -2.1; P<.001) percentage points. This study moves the question from postdeployment evaluation to predeployment design, treating geographic calibration as an upstream mobile health decision. It differs from prior work that assessed uptake, privacy, or epidemiological outcomes after fielding, and from mobility research that treated movement data as a predictor, an outcome, or a model input rather than as a criterion for choosing a boundary rule. The contribution is threefold: it formulates a boundary-fit question that can be answered before a system is built; it provides a reproducible, auditable workflow (daily origin-area proportions, a paired HAC-based comparison, and a mobility-clustering check) that agencies and developers can rerun on their own data; and it demonstrates the workflow from end to end in a large municipality. Practically, a city-level unit is a defensible starting reference where movement is predominantly internal, whereas border areas warrant separate local assessment. Agencies should document where a boundary fits local movement and where exceptions may be needed. Decisions about restrictions also require epidemiological evidence and assessment of proportionality, public acceptability, and social costs. ", "url": "http://doi.org/10.2196/64941", "title": "Evaluating City-Cut Geographic Risk Classification for a Pandemic Travel-Record System in Shanghai, China: Retrospective Observational Analysis.", "summary": "Evaluating City-Cut Geographic Risk Classification for a Pandemic Travel-Record System in Shanghai, China: Retrospective Observational Analysis. - JMIR mHealth and uHealth", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Wang, R; Shi, B; Li, S; Xie, C; Zhang, Q", "url": "https://orcid.org/0000-0002-7665-4460" } }, { "id": "http://doi.org/10.2196/102164", "content_html": "The rapid integration of digital technologies into art therapy reflects both technological advances and the growing need for flexible, accessible mental health care. This scoping review aimed to systematically map and synthesize empirical research in English on technology-integrated art therapy published from 2016 to August 2026. A comprehensive search across 9 electronic sources yielded 697 records, of which 47 empirical studies met the inclusion criteria according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The included studies were methodologically heterogeneous, comprising qualitative (n=19, 40.4%), quantitative (n=12, 25.5%), and mixed methods (n=16, 34%) designs, and were largely characterized by small samples and exploratory or feasibility-oriented approaches. Among the quantitative and mixed methods studies, 9 used randomized controlled or randomized experimental designs, while the remainder used nonrandomized or other designs. Reported quantitative outcomes included improvements in cognitive functioning, emotional regulation, mental health, behavioral symptoms, and functional outcomes; however, evidence for clinical effectiveness remained limited and heterogeneous. Qualitative and mixed methods studies reported potential benefits related to engagement, reduced performance-related anxiety, agency, emotional expression, and creative exploration. Digital affordances such as editing, layering, and multimodal creation were associated with iterative meaning-making and expanded expressive possibilities. In immersive contexts, particularly virtual reality, participants described altered sensory and embodied experiences. At the same time, technology raises concerns regarding privacy, data security, boundaries and setting, and the potential impact on the therapeutic relationship. Technology-integrated art therapy appears to offer promising possibilities for expanding access, engagement, expression, and therapeutic experience, but the current evidence remains too limited and heterogeneous to establish clinical effectiveness or mechanisms of change. ", "url": "http://doi.org/10.2196/102164", "title": "Technology-Integrated Art Therapy: Scoping Review of Outcomes and Processes.", "summary": "Technology-Integrated Art Therapy: Scoping Review of Outcomes and Processes. - JMIR mental health", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Goldner, L; Szyfer Lipinsky, A; Salomon-Gimmon, M", "url": "https://orcid.org/0000-0002-5237-8051" } }, { "id": "http://doi.org/10.2196/94570", "content_html": "AI-enabled digital medicine platforms in Europe are developed within overlapping rules for personal data, medical devices, AI, clinical research, health data access, and health technology assessment. This viewpoint represents the authors' experience and interpretation from the preimplementation phase of INTERCEPT, an Innovative Health Initiative consortium that plans to validate biomarkers and develop a blood-based risk score for early Crohn disease interception. It does not report original empirical research, a systematic regulatory review, a deployed platform, or a validated AI model. Our aim is to explain how compliance-by-design can be translated into an auditable governance architecture and to identify what still requires scientific evaluation. We advance 3 messages. First, governance must begin with intended purpose and boundary mapping: a digital platform may contain research, operational, and medical device software functions, and conformity of one module cannot be inferred for the platform as a whole. Second, overlapping obligations can be operationalized through 5 linked controls: modular responsibility and change control, federated data governance, traceable AI life cycle management, consent and participant rights orchestration, and a common cross-border governance core with local adaptations. Third, compliance is not a surrogate for model validity, clinical benefit, trust, scalability, or market access. Before clinical deployment, planned AI components require prespecified labels and cohorts, leakage prevention, missing data and imbalance strategies, calibration, subgroup assessment, external validation, human factors evaluation, and postdeployment algorithmovigilance. A hypothetical biomarker risk score update illustrates how the 5 controls interact. INTERCEPT is informative because it combines cross-border biomarker research, planned predictive analytics, and heterogeneous institutional settings while key design decisions remain modifiable. Its contribution is nevertheless conceptual: the proposed framework is a testable governance hypothesis, not evidence of implementation success. Prospective studies should compare it with alternative governance models and assess safety, workload, participant experience, evidence generation, and regulatory performance. ", "url": "http://doi.org/10.2196/94570", "title": "Compliance-by-Design in an AI-Enabled Platform for Early Crohn Disease Interception: A Viewpoint.", "summary": "Compliance-by-Design in an AI-Enabled Platform for Early Crohn Disease Interception: A Viewpoint. - Journal of medical Internet research", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Scaldaferri, F; Puca, P; Fiorelli, E; Bosmans, J; Vesely, R; D'Haens, G; Colombel, JF; Torres, J; Gasbarrini, A; Cesario, A", "url": "https://orcid.org/0000-0001-8334-7541" } }, { "id": "http://doi.org/10.2196/94439", "content_html": "AI is increasingly embedded in health care and digital health applications, shaping clinical processes as well as how patients access information and participate in care. Research on bias in medical AI has largely focused on technical and performance-related disparities. Less attention has been paid to how such biases may affect patients' access, understanding, trust, and opportunities for meaningful involvement in care. This scoping review aimed to map how studies of bias in medical AI describe patient-related consequences relevant to patient empowerment and the digital divide and to identify gaps across technical, social, structural, and patient-centered perspectives. This scoping review followed JBI (Joanna Briggs Institute) methodology and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) reporting guidance. PubMed/MEDLINE and EBSCOHost databases were searched in August 2025 and supplemented by Google Scholar searches. Peer-reviewed studies published from 2015 onward were included if they addressed bias in medical AI and described patient-related consequences relevant to patient empowerment or digital inequality. Data charting focused on AI application types, bias dimensions, patient empowerment domains, digital divide-related factors, intersectionality, and debiasing strategies. Findings were synthesized descriptively and thematically. The search identified 497 records, of which 22 studies met the inclusion criteria. Bias was represented as a multidimensional sociotechnical phenomenon, with social bias identified most frequently (21/22 studies), followed by algorithmic bias (16/22 studies), structural bias (14/22 studies), and design-related bias (12/22 studies). Patient empowerment was most frequently addressed through involvement in care (n=13), followed by health literacy (n=9) and trust and assurance (n=7), whereas broader psychosocial and everyday-life domains were addressed less frequently. Digital divide-related factors were identified in 19 of the 22 studies, with digital literacy and usability barriers reported most frequently. Seven studies considered 2 or more social or structural dimensions of disadvantage. Although many studies discussed approaches that could mitigate bias-related barriers, explicit empirical evaluation of debiasing strategies in relation to patient empowerment or digital equity was largely absent. Patient-related consequences of bias in medical AI extend beyond algorithmic performance and are reflected in access, understanding, trust, and involvement in care. Broader empowerment dimensions, multidimensional disadvantage, and empirically evaluated mitigation strategies remain comparatively underexplored. ", "url": "http://doi.org/10.2196/94439", "title": "Bias in Medical AI in Relation to Patient Empowerment and Digital Equity: Scoping Review.", "summary": "Bias in Medical AI in Relation to Patient Empowerment and Digital Equity: Scoping Review. - Online journal of public health informatics", "date_modified": "2026-11-09T00:00:00.000Z", "author": { "name": "Norz, LM; Beeck, E; Ammenwerth, E", "url": "https://orcid.org/0000-0003-2711-3227" } } ] }