Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 42 appraisals
Journal of robotic surgery
The need for a dedicated surgical consent framework for robotic telesurgery: a global call to action
Robotic telesurgery has progressed from experimental demonstrations to real-world clinical implementation across multiple continents. Landmark interconnected procedures, including intercontinental robotic prostatectomies, humanitarian implementations in underserved regions, and expansion of teleproctoring/tele-mentoring networks, showcase a rapidly maturing field. Despite this proliferation, no standardized, procedure-specific surgical consent for telesurgery exists in the medical literature. Current consent processes for robotic surgery, telemedicine, and surgical research fail to address critical elements unique to telesurgery, including latency thresholds, technical redundancies, network architecture, cybersecurity risks, remote surgeon responsibilities, and contingency planning. Our article aims to define the essential elements that should compose a dedicated telesurgery-specific informed consent and to highlight why current consent frameworks are insufficient for this rapidly expanding global practice. This expert-opinion paper synthesizes high-impact literature on consent ethics, digital surgery, telehealth governance, and robotic surgery; evaluates current consents used in pioneering telesurgery programs across North America, South America, Africa, Europe, and Asia; and incorporates multidisciplinary insights from surgery, anesthesiology, biomedical engineering, cybersecurity, telecommunications, ethics, and global health. We identify major gaps in contemporary consent frameworks, including (1) inadequate disclosure of connectivity-related risks; (2) insufficient explanation of data transmission, cybersecurity, and encryption; (3) absence of latency thresholds and safety-based interruption criteria; (4) lack of transparency regarding remote surgeon responsibility and handover protocols; and (5) limited patient education regarding contingency conversion and chain-of-care accountability. We thus propose a 9-component International Telesurgery Consent Framework, providing standardized language and structure for global implementation. The rapid expansion of telesurgery demands an equally rapid evolution in patient-centered informed consent. A dedicated telesurgery consent should become the ethical, medicolegal, and operational standard for any remote robotic clinical procedure. This paper serves as the basis for an international consensus effort involving global leaders in robotic surgery, telehealth, AI-enabled surgery, and digital health regulation.
14 June 2026
Read appraisal →Journal of medical Internet research
Telehealth Scale and Artificial Intelligence Adoption Tiers Across Clinical and Operational Domains in US Hospitals: Cross-Sectional Study
BACKGROUND: Telehealth expansion and artificial intelligence (AI) adoption are often described as parallel dimensions of health system digital transformation. However, whether telehealth scale is associated with hospital AI adoption and whether this relationship varies across hospital settings remain unclear. OBJECTIVE: This study examined the association of telehealth scale with clinical and operational AI adoption tiers in US hospitals and assessed whether these patterns differed by telehealth reporting behavior and geography. METHODS: This cross-sectional study included 6173 US acute care hospitals using linked 2024 American Hospital Association Annual Survey and Information Technology Supplement data and 2023 Healthcare Cost Report Information System data. Telehealth scale was parameterized using log-transformed telehealth volume, a telehealth nonreporting indicator, and a reported-zero telehealth indicator. Clinical and operational AI adoption tiers were derived from hospital-reported AI capability items and classified into 3 tiers. Both outcomes were modeled using multioutput gradient-boosted tree classifiers, and model behavior was interpreted using Shapley additive explanations, partial dependence plots, and stratified analyses by the Core-Based Statistical Area category. RESULTS: Telehealth volume was the strongest predictor of both clinical and operational AI adoption tiers and had a larger contribution to the clinical AI model. Telehealth nonreporting was common, occurring in 57% (3521/6173) of hospitals, and was concentrated among hospitals in the lowest clinical AI adoption tier, accounting for 91.4% (3145/3441) of hospitals with no reported clinical AI adoption. Higher telehealth volume was associated with a steep increase in predicted clinical AI adoption tiers at lower telehealth volumes, followed by a plateau at higher volumes. At similar telehealth volumes, rural hospitals showed weaker telehealth-attributed contributions to predicted clinical AI adoption tiers than metropolitan hospitals. Supplementary analyses suggested that telehealth reporting status and telehealth intensity reflected related but distinct structural processes. CONCLUSIONS: Telehealth scale was strongly associated with hospital AI adoption tiers, especially clinical AI adoption tiers. These findings suggest that telehealth capacity may serve as a practical hospital-level marker of broader digital readiness for AI adoption, but the cross-sectional design does not establish whether telehealth expansion precedes or causes AI adoption. Hospitals with telehealth nonreporting and rural hospitals may face additional structural barriers that limit the translation of digital capacity into AI maturity. Policies to reduce inequities in hospital AI adoption may therefore need to pair telehealth expansion with implementation support, interoperability capacity, and organizational resources.
14 June 2026
Read appraisal →BMJ open
Protocol for evaluating the effects of the intelligent multimodal symptom assessment and response system in patients with pemphigus vulgaris: a randomised controlled trial
INTRODUCTION: Pemphigus vulgaris is a rare autoimmune blistering disease characterised by recurrent mucocutaneous erosions, high symptom burden and unpredictable relapse. Current management relies mainly on pharmacological therapy and hospital-based follow-up, with limited real-time monitoring and individualised support in home-based disease management. To address these challenges, this trial aims to evaluate the effectiveness of an Intelligent Multimodal Symptom Assessment and Response System, integrating patient-reported outcomes, wearable physiological data and image-based lesion assessments, to improve symptom management and quality of life in pemphigus vulgaris patients. Primary objective is to evaluate the effectiveness of the Intelligent Multimodal Symptom Assessment and Response System in improving symptom alerting and symptom management outcomes in patients with pemphigus vulgaris. Secondary objectives are to enhance patients' self-management ability in symptom monitoring and control, to improve treatment adherence throughout the follow-up period, to promote health-related quality of life among pemphigus vulgaris patients, to assess the usability and acceptability of the system from the patients' perspective. METHODS AND ANALYSIS: This is a multicentre, parallel-group, randomised controlled trial. 160 participants will be randomly assigned to either the intervention group (receiving the Intelligent Multimodal Symptom Assessment and Response System) or the control group (receiving standard care). Eligible participants will be adults aged 18 years or older with a confirmed diagnosis of pemphigus vulgaris and active skin or mucosal lesions, who are able to use digital devices and provide written informed consent. Individuals with severe comorbidities, concurrent participation in other clinical trials or cognitive impairments that may interfere with study adherence will be excluded. The intervention will be delivered via a digital platform, integrating electronic patient-reported outcomes, wearable physiological data and lesion images over a 12-week follow-up period. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Institutional Review Board of the School of Nursing, Fudan University (IRB 2025-07-13), the Medical Ethics Committee of the Institute of Dermatology, Chinese Academy of Medical Sciences (2025-KY-034) and the Ethics Committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (2025-452). Approvals were granted on 10 September, 18 July and 23 July 2025, respectively. This protocol is based on V1.0, 13 July 2025 of the protocol. The results of this study will be disseminated through peer-reviewed publications and academic conferences. TRIAL REGISTRATION NUMBER: ChiCTR2500109711.
29 May 2026
Read appraisal →Journal of medical Internet research
Rerouting Eye Care: How AI and Telemedicine Are Reshaping Ophthalmology Patient Journeys in the United Kingdom and Germany
Artificial intelligence (AI) as a medical device is now progressively entering routine ophthalmic care, yet its impact is still mostly evaluated in terms of diagnostic performance rather than how it reshapes patient care pathways. This viewpoint argues that careful pathway design is crucial to implementing AI in ophthalmology so that it translates into real, practical benefits for patients and services. We propose a framework that classifies AI- and telemedicine-enabled eye care pathways by the initial point of contact and the role of AI: from direct human assessment to grader- or telemedicine-based use to AI-first contact and fully autonomous AI gatekeeping. We apply this framework to 2 contrasting health systems, the United Kingdom and Germany, focusing on common retinal diseases and cardiovascular risk assessment from retinal images. In the United Kingdom, AI is being introduced mainly as a modular upgrade to standardized programs layered onto a gatekeeper model centered on community optometrists and general practitioners. In Germany, direct access to office-based ophthalmologists, opportunistic screening, and commercial retail offerings are producing more fragmented clinician- and market-driven AI adoption. Our comparison shows that the same AI technologies can generate very different patient journeys across health systems. Therefore, their value depends not only on diagnostic performance but also on intentional pathway design, including clear escalation rules and structured information transfer. This includes appropriate task shifting from ophthalmologists to trained staff or new roles, such as image grading, tele-ophthalmology triage, or pathway management. Without such design, AI risks duplicate testing, incomplete or poorly coordinated referrals, and further fragmentation of care.
29 May 2026
Read appraisal →Medicine
Applying digital technologies for remote care in the real life context: A 3-year experimentation with postoperative lung cancer patients
Surgery remains the main curative treatment for lung cancer patients. However, operation has resulted in some-degree reduction in postoperative pulmonary function. The decreased pulmonary function could be rehabilitated to the preoperative level through restoring exercise, which is related to the ways and exercise time of rehabilitating. The Dignio platform is 1 digital telemedicine system and has been used maturely in Norway, however, it has not yet been widely promoted in China. In the present study, we adopted the telemedicine system, according to the formulated rehabilitation exercise program, to design a good way to recover pulmonary function for postoperative lung cancer patients, promoting early and quick recovery, and reducing the long-term postoperative complications and outpatient visits. This retrospective controlled study enrolled 250 postoperative lung cancer patients using a remote digital care platform and 250 matched controls receiving standard instructions. In the postoperative 1-week follow-up, we found that the forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), forced expiratory volume in 6 seconds, FVC25-75, peak expiratory flow had an obvious upward trend, although there were no significant differences in the measurements on postoperative day 7 compared with day 1. From the long-term data at 1 month/3 months/6 months post-operation, we found that the recovery was better to varying degrees in the experiment group using the remote care digital platform, compared with that of the control, especially the FEV1 at 3 (P = .065) and 6 months post-operation (P = .037), and forced Expiratory Flow between 25% and 75% of forced vital capacity at 3 months post-operation (P = .084). However, most pulmonary values, such as the FEV1/FVC, FVC and peak expiratory flow have no significant difference (all P > .05) in the recovery at 1 month post-operation between the experimental group and control, the second time at 3 months and the third time at 6 months after surgery. Especially in the experimental group, 2 patients with sudden pneumothorax were timely detected after discharge through the Digino platform, the patient returned to the hospital in time, and both patients were out of danger ultimately. The Digino remote care indeed has some benefit in the pulmonary function recovery in the long-term follow up, and reduces postoperative complications obviously.
24 May 2026
Read appraisal →BMC research notes
Survey to evaluate clinical benefits and acceptance in international tele-intensive care unit collaboration
OBJECTIVES: Tele-intensive care unit (TICU) networks have evolved quickly in recent years and have proved their value in providing care for the critically ill. Objective measures to assess performance and quantify success e.g. clinical and economic outcome parameters are desirable but not easily accessible in international collaboration with very diverse clinical settings and legal prerequisites. Therefore, we initiated a study to evaluate the performance in our tele-intensive care unit network. METHODS: We conducted an online survey addressing clinical staff at ten spoke sites in four countries connected to one TICU hub to assess subjective clinical benefit, acceptance and potential for improvement. RESULTS: The majority of the 30 participants felt well supported clinically and personally, with a high acceptance and trust as well as a positive working relationship in tele-medical collaboration. Ethical principles and data protection were discovered to be persistently of utmost significance in tele-intensive care unit networks. CONCLUSION: International telemedicine in critical care is perceived positively without major differences between diverse health care systems when crossing borders, showing potential for improvement to guide future clinical and research approaches. Clinical trial registiry: The study was registered on August 11th, 2023 with the German Clinical Trials Register (DRKS-IDDRKS00032246; https://www.drks.de/search/de/trial/DRKS00032246/details ).
24 May 2026
Read appraisal →Studies in health technology and informatics
Logic Models on Health Information Technology: First Insights from a Cross-Disciplinary Scoping Review
BACKGROUND: Health information technology (HIT) interventions are complex, yet theory-based approaches such as logic models or Theory of Change (ToC) remain rarely applied in medical informatics, although they could clarify assumptions, link activities to outcomes, and support design and evaluation. OBJECTIVES: This scoping review examined how logic models and ToC have been used in HIT research across disciplines. METHODS: Following the PRISMA-ScR guidelines, databases were searched up to August 2025. Eligible studies explicitly applied logic models or ToC to HIT. Data were extracted on HIT type, purpose of using logic models, and reported benefits and challenges. RESULTS: Sixty-nine studies met inclusion criteria, most published after 2020. A majority of studies developed logic models for patient-facing HIT such as mHealth or telehealth. Logic models were mainly used to support HIT design or evaluation and were mostly newly developed. Reported benefits of using logic models included conceptual clarity and better stakeholder communication; challenges involved resource demands and limited generalisability. CONCLUSIONS: Logic models and ToC are increasingly used for HIT but remain inconsistently applied and seldom reused. Standardised reporting and repositories could strengthen theory-informed evaluation in medical informatics.
24 May 2026
Read appraisal →Journal of medical Internet research
Reporting of Telehealth Implementation in Cystic Fibrosis: Scoping Review Using a Novel Theory-Based Evaluation Lens
BACKGROUND: Many inductive reviews exploring telehealth and its application in health care have identified missing or inconsistently reported implementation data, calling for a standardized approach to telehealth research. OBJECTIVE: Using cystic fibrosis (CF) as a case exemplar, this study evaluated the adherence of telehealth research to standardized reporting frameworks through a theory-based evaluation lens to assess implementation reporting quality and identify knowledge gaps and strengths across the literature. METHODS: We conducted an updated systematic review of the PubMed, Scopus, and Web of Science databases using a novel deductive approach to identify relevant scientific papers available in English and focusing on the delivery of telehealth interventions to CF populations as part of or alongside routine CF care. Two relevant reporting checklists were identified in the Equator Network database (Guidelines and Checklist for the Reporting on Digital Health Implementations [iCHECK-DH] and Template for Intervention Description and Replication for Telehealth [TIDiER-telehealth]) to extract data from the papers. Each checklist category was described as being "fully reported" (score=2), "partially reported" (score=1), and "did not report" (score=0) for each paper. An overall score was calculated for adherence to the checklists. RESULTS: In total, 98 studies published between 2006 and May 2025 were included in this review, with the majority appearing during the COVID-19 pandemic (2021-2022). Most studies were conducted in a single country, predominantly the United States, Australia, and the United Kingdom, and were published in medical journals. Telehealth was variably described, with video call-based models in combination with remote monitoring being most common. The median score was 22/40 (range 11-29, 55.0% adherent) for iCHECK and 15/24 (range 6-23, 62.5% adherent) for TIDiER, demonstrating moderate overall reporting quality. For iCHECK, ≥50% of studies fully reported 6/20 categories, partially reported 9/20 categories, and did not report 3/20 categories. For TIDiER, ≥50% of studies fully reported 4/12 categories, partially reported 6/12 categories, and did not report 1/12 categories, indicating persistent gaps in intervention description despite improved partial reporting. CONCLUSIONS: Key areas, such as justification for telehealth, target populations, and outcomes, are well documented, offering valuable insights into the rationale for and outcomes associated with telehealth. However, implementation processes remain underreported, partly due to the more recent adoption of frameworks like iCHECK and TIDiER. The clinical implications of the current evidence limit the implementation of telehealth in terms of the ability to assess feasibility and readiness for adoption; understand financial implications and plan sustainably; ensure patient safety, data protection, and equity; interpret outcome data in context; and share, replicate, or scale evidence-based models of care. Strengthening the commitment to standardized telehealth reporting will ultimately support clinical decision-making and improve the effective and equitable integration of telehealth into care.
23 May 2026
Read appraisal →The British journal of dermatology
Artificial intelligence-based smartphone application for skin cancer detection: a prospective diagnostic accuracy study
BACKGROUND: Smartphone applications ('apps') that use artificial intelligence (AI) for skin cancer diagnosis may help with early detection. However, prospective studies assessing real-world performance are scarce. OBJECTIVES: To evaluate in an independent prospective study the diagnostic accuracy of a widely used skin cancer detection app and the effect of photographic conditions in a user-representative cohort of patients consulting for lesions of concern. METHODS: Between 1 February 2021 and 30 June 2023, participants presenting at an early-access consultation with a lesion of concern were consecutively enrolled. Following dermatological assessment, each lesion was photographed using the app. The app's convolutional neural network (CNN) generates a binary risk output and advice. A teledermatology review was performed in a subset of cases. The diagnostic accuracy of the CNN combined with teledermatology review was compared with final clinical or histopathological diagnosis. Performance was tested under different photographic conditions (angle, lighting, user) and with different smartphone models. The trial was registered with ClinicalTrials.gov (NCT05246163). RESULTS: A total of 1458 participants with 1904 lesions of concern were included. Of these, 185 (9.7%) were skin cancers, with 32 melanomas. Image capture was unsuccessful in 16.6% of lesions (n = 317/1904), despite optimal conditions. For successfully captured lesions, the CNN achieved a sensitivity of 82.5% and specificity of 76.8% for skin cancer detection. In-app teledermatology review was available for 65.7% (n = 1042/1587) of images. Combined CNN and teledermatology review resulted in increased specificity (86.8%; P < 0.001), with a sensitivity of 75.3%. Overall sensitivity in melanocytic lesions was lower than in nonmelanocytic lesions (71.0% vs. 76.3%; P < 0.001), whereas specificity was higher (90.0% vs. 84.9%; P < 0.001). A substudy demonstrated low image-capture success in user hands (28.9%) and variation in diagnostic performance between smartphone models. CONCLUSIONS: This independent, prospective study evaluated diagnostic performance of a widely used skin cancer detection app in a user-representative cohort. The findings highlight the importance of independent clinical validation of AI-based healthcare tools in real-world settings. Skin cancer is one of the most common cancers that affects people worldwide. Finding cancer early is important, especially for melanoma, a serious form of skin cancer. There is potential for smartphone apps to use AI to help people identify skin spots that may need medical attention. In this study, we evaluated a widely used app called SkinVision. People presenting with a worrisome spot at a dermatology appointment were invited to take part in this study. Altogether, 1458 people were included. The skin area of concern was assessed with the app. Using AI, the app produced a risk score. It also gave a final score. The final score was the AI risk score that may be combined with dermatology advice delivered remotely (‘teledermatology’). We compared the app scores with the doctor’s final diagnosis. We also studied the impact of things such as photo angle, lighting, type of smartphone and the person who took the photo. We found that over 16% of worrisome skin areas could not be captured by the app under ideal conditions. If participants were asked to take the photo themselves, this increased to over 70%. The app correctly identified skin cancers in 83% of cases but gave false alarms in 23%. The in-app teledermatology review reduced the number of false alarms, but this increased the number of missed skin cancers. Finally, we found important differences between different smartphones. Our findings highlight the importance of trialling apps like this with real patients in real-life setting before they are fully introduced to the public.
20 May 2026
Read appraisal →JMIR medical informatics
The Impact of Electronic Health Records on Family Physicians During Simulated Virtual Encounters: Exploratory Mixed Methods Study
BACKGROUND: This exploratory study investigated the impact of computer use on physician performance during clinical simulations. Standardized patient (SP) scenarios used in family practice certification examinations were adapted to include the use of the electronic health record (EHR). OBJECTIVE: The goal was to compare the impact of EHR use during simulated virtual patient encounters on resident physicians' and staff physicians' patient-centeredness (PC) and overall clinical performance, as well as to measure the cognitive load (CL) imposed by EHR use. METHODS: Sixteen participants each completed 2 video telemedicine simulations with SPs. One simulation case included limited past medical history for the SP in the EHR, while the other did not. Participants were instructed to completely document the encounter using the EHR. Participants' self-perceived CL was measured using the raw National Aeronautics and Space Administration Task Load Index (NASA-TLX). Video recordings were analyzed for participant PC and overall clinical performance. In addition to interacting with the EHR, multiple participants also conducted internet searches. The proportion of time that participants spent interacting with the computer, either using the EHR or searching the internet, was calculated. Inductive qualitative coding of a subset of video recordings (18 of 32 encounters) was performed, with a focus on signs of stress/CL. All videos were assessed for usability problems. RESULTS: Staff physicians (n=6) scored higher on PC compared to resident physicians (n=10) for both cases, though differences were not statistically significant after correction for multiple comparisons (family-wise error rate). Physicians' overall CL, as measured by the raw NASA-TLX, was not significantly correlated with computer use. Exploratory qualitative data analysis found both verbal and nonverbal signs of stress/CL due to computer use while interacting with the SPs. The proportion of time displaying nonverbal signs of stress/CL was calculated for a subset of participants (6 resident physicians and 3 staff physicians). Participant interpretations of instructions to completely document the encounter using the EHR varied widely. It is likely that participants' usual style of documenting, either primarily during or after patient encounters, impacted their use of the EHR while SPs were present. CONCLUSIONS: Use of the computer during video telemedicine appointments may negatively impact physician PC and overall clinical performance. Exploratory qualitative coding identified both verbal and nonverbal signs of stress/CL when participants interacted with the computer and the patient simultaneously. Increased clinical experience helped to mitigate the negative impact of computer use. If the use of the EHR is included in physician certification examinations, clear instructions regarding which tasks must be completed in the EHR during interactions with SPs should be provided.
20 May 2026
Read appraisal →Physiological measurement
EdgeECG: a lightweight edge-oriented network with dual criterion pruning for real-time ECG arrhythmia classification
Objective.Miniature electrocardiogram (ECG) devices can rapidly and accurately acquire real-time cardiac signals, enabling timely warnings for patients with heart disease. To achieve accurate arrhythmia classification on resource-constrained ECG edge devices, we propose EdgeECG, an ultra-lightweight neural network designed for deployment on low-power microcontrollers.Approach.EdgeECG is first designed with a compact convolutional architecture to ensure compatibility with resource-limited embedded platforms. A dual criterion pruning (DCP) strategy is then introduced to evaluate weight importance using both magnitude and median deviation for more precise model compression. In addition, quantization is applied to reduce storage cost and improve deployment efficiency on an STM32F103 microcontroller.Main results.Experimental results on the benchmark MIT-BIH arrhythmia dataset show that EdgeECG achieves an overall classification accuracy of 98.07%, outperforming several representative methods. In patient-independent record-level evaluation, the accuracy reaches 80.73%. The model contains only 2680 parameters and is successfully deployed on an STM32F103 microcontroller with 64 KB SRAM, achieving an inference latency of 0.025 s and an energy consumption of 0.156 mJ per inference. In addition, DCP reduces the number of non-zero parameters by nearly 50% while maintaining promising classification performance.Significance.EdgeECG provides an effective solution for five-class ECG arrhythmia classification on severely resource-constrained edge devices. Its compact architecture, effective pruning strategy, and successful deployment on an STM32F103 demonstrate its potential for low-power edge-based ECG analysis and wearable cardiac monitoring applications. The source code of EdgeECG is publicly available at:https://github.com/jyanhuang/EdgeECG-code.
19 May 2026
Read appraisal →JMIR mHealth and uHealth
WhatsApp-Supported Teledentistry to Reinforce Oral Health Promotion Among Older Adults Residing in Rural and Urban Areas: Randomized Controlled Trial
BACKGROUND: Access to oral health promotion for older adults is globally limited, especially in rural, low- and middle-income settings. Digital research often lacks theoretical foundation and focuses primarily on younger cohorts, yielding few randomized trials evaluating accessible tools for oral health education in older adults. OBJECTIVE: This study aimed to develop a telehealth reinforcement strategy for oral health promotion to improve knowledge, attitudes, and self-efficacy in community-dwelling older adults. METHODS: A single-center, parallel-group randomized controlled trial was conducted in 4 municipalities (2 urban and 2 rural) in La Araucanía, Chile. Eligible participants were functionally independent adults aged ≥60 years with smartphone and internet access; those with cognitive impairment, complete edentulism, or inability to use WhatsApp were excluded. Participants were recruited from regional databases and assessed using the Geriatric Dental Specialties Tele-platform, a teledentistry tool for older adults. Participants were randomized (1:1) to face-to-face instruction (comparator) or the same instruction plus 2 weeks of social cognitive theory-informed telehealth reinforcement (4 validated videos via WhatsApp). Clinicians and statistical advisors were blinded. Primary outcomes (oral health knowledge, attitudes, and self-efficacy) were measured via telephone-administered questionnaires at baseline and 6 weeks post intervention. Secondary outcomes included acceptability and self-reported behaviors. Analyses included hypothesis testing, multiple correspondence analysis, and k-means clustering. RESULTS: A total of 120 older adults were randomized (comparator: n=59; telehealth: n=61), with 103 analyzed (comparator: n=51; telehealth: n=52). Both groups showed substantial within-group improvements in oral health knowledge (comparator: Cohen d=0.93, 95% CI 0.52-1.34; P<.001; telehealth: Cohen d=1.07, 95% CI 0.66-1.48; P<.001) and self-efficacy (comparator: r=0.59, 95% CI 0.38-0.74; P<.001; telehealth: r=0.62, 95% CI 0.43-0.77; P<.001). In per-protocol analysis, telehealth improved dental caries knowledge (P=.03) and attitudes (P=.004), with no between-group differences in other domains (P>.05). In intention-to-treat analysis, telehealth showed a significant between-group difference for attitudes only (adjusted mean difference=0.91, 95% CI 0.34-1.48; P=.002), with no differences for overall oral health knowledge (P=.11) or self-efficacy (P=.59). Exploratory analyses indicated only the rural telehealth subgroup showed significant gains in attitudes (P=.003) and flossing (P<.001). Clustering suggested greater improvements among participants with higher baseline needs, predominantly rural, with fewer teeth. Telehealth demonstrated acceptability across multiple indicators (>80% for most measures) with no clinical adverse events; minor video-access issues occurred. CONCLUSIONS: Telehealth reinforcement provided significant advantages in oral health attitudes compared with face-to-face instruction. The intervention was acceptable and showed benefits among older adults with higher preventive needs, commonly seen in rural settings. By integrating theory-informed strategies into a familiar digital platform, this study adds evidence from rural and urban contexts, extending prior work on mobile oral health. It offers insights to address service gaps in underserved areas and highlights potential for feasible, context-aligned implementation. Future research should evaluate long-term effects, adaptability, and cost-effectiveness. TRIAL REGISTRATION: ClinicalTrials.gov NCT05917548; https://clinicaltrials.gov/study/NCT05917548.
17 May 2026
Read appraisal →European heart journal
Wearable devices and cardiovascular health: revolutionizing remote monitoring and disease prevention
Wearable devices are transforming cardiovascular medicine by enabling continuous monitoring of physiologic and behavioural measures outside of traditional clinical settings. Smartwatches and activity trackers, the most widely used wearables, employ motion and biometric sensors to measure physical activity, sleep quality, heart rate, and rhythm. By converting health goals into objective, quantifiable measures, wearable devices empower patients to assume a more active role in their health while providing clinicians with novel opportunities for longitudinal, real-world assessment. Clinical applications span the cardiovascular continuum from lifestyle interventions targeting physical activity and sleep to the remote management of chronic conditions such as heart failure. Widespread clinical adoption of wearables remains limited by challenges, such as variability in device methodology, data outputs, validation, and intended use; incompatibility with existing electronic health records; and the lack of standardized, evidence-based workflows for clinicians to efficiently interpret and act upon wearable data. This review summarizes the current landscape of wearable technologies in cardiovascular medicine by highlighting key clinical applications, evidence gaps in the existing literature, the role of artificial intelligence, and barriers to implementation. We discuss strategies to enhance clinical integration and strengthen the current evidence base while also providing practical guidance to help clinicians navigate commonly encountered clinical scenarios.
16 May 2026
Read appraisal →Current pain and headache reports
Addressing the Treatment Gap for Pediatric Headache in Underserved Regions
PURPOSE OF REVIEW: This review explores innovative strategies to address the treatment gap for pediatric headache disorders in underserved regions worldwide. RECENT FINDINGS: Global Burden of Disease studies indicate that the fastest growth in pediatric headache burden occurs in low- and middle-income countries, where reported prevalence likely underestimates true disease burden due to healthcare access barriers. Telemedicine demonstrates comparable efficacy, safety, and satisfaction to in person care. Artificial intelligence based diagnostic models achieve high accuracy for pediatric migraine identification. School-based interventions leveraging existing educational infrastructure improve headache knowledge and coping behaviors. Task shifting and integrated care delivery models are increasingly recognized as essential components of sustainable care. Telemedicine, artificial intelligence, school-based interventions, task shifting, and integrated care networks represent scalable solutions for extending headache care to underserved pediatric populations. Realizing their potential requires integrating technological innovation with workforce capacity building, community engagement, and policy advocacy.
14 May 2026
Read appraisal →JMIR mHealth and uHealth
Contribution of Longitudinal Mobile Health Measures in the Dynamic Track of Patients With Major Depressive Disorder: Multiple Centers, Prospective Cohort Study Using Functional Data Analysis and Machine Learning
BACKGROUND: Continuous follow-up for patients with major depressive disorder (MDD) is essential for treatment decisions and a better prognosis. There remains limited evidence regarding the critical issue of depression variation trajectory prediction using mobile health (mHealth) measures. Moreover, the temporal dynamics of mHealth measures have not been fully modeled in previous studies, and the poor patient adherence to mHealth records poses great challenges to the dynamic feature modeling. OBJECTIVE: This study aimed to examine the contribution of mHealth measures in predicting depression variation trajectory for patients with MDD, with full consideration of the temporal dynamics of mHealth measures. METHODS: A total of 229 patients with MDD from a multiple-center, prospective cohort were included. A 12-week follow-up was conducted involving the collection of the Hamilton Depression Rating Scale (HAMD-17), along with patient-reported outcomes (Immediate Mood Scaler and Altman Self-Rating Mania Scale) via mobile devices and sleep duration through wearable wristbands. We used functional data analysis to extract dynamic features from the sparse mHealth records, rather than aggregating the data to a single scalar summary measure through collapsing over time. Subsequently, 3 machine learning models were applied to predict the depression variation trajectory classes based on the baseline characteristics and these extracted dynamic features. RESULTS: Based on the variation of HAMD-17 scores within 12 weeks, the participants were labeled into 4 classes through the k-means algorithm. The classes included stable decline (n=93), fluctuate decline (n=44), fast decline (n=60), and delayed and fluctuate (n=32), in light of the shape of depression trajectories. With both baseline features and dynamic features of the mHealth measures, accuracy rates for the overall data were 54.35%, 60.87%, and 56.52%, for the stable decline patients were 78.95%, 84.21%, and 73.68%, for the nonstable decline patients were 59.26%, 62.96%, and 70.37% based on the 3 machine learning models, respectively. The results were significantly superior to the prediction obtained without mHealth measures (with an overall accuracy below 50%) and only showed a marginal reduction in accuracy relative to the ideal prediction with assessment obtained from clinical visits. Moreover, in the construction of the most accurate prediction model, dynamic features of the Immediate Mood Scaler, the Altman Self-Rating Mania Scale, and sleep duration emerged as the most influential predictors, ranking first, third, and fourth, respectively, in terms of their relative importance. CONCLUSIONS: Longitudinal mHealth measures show potential in depression variation trajectory monitoring for patients with MDD even under poor patient adherence. Our work provides practical help in alleviating the follow-up burden for patients with MDD and validates the effectiveness of mHealth measures in clinical applications.
13 May 2026
Read appraisal →Journal of medical Internet research
Governing Patient-Facing AI-Generated Video in Digital Health: A Risk-and-Ethics Matrix for Deployment, Monitoring, and Change Control
In this Viewpoint, we argue that patient-facing high-fidelity artificial intelligence (AI)-generated video requires governance that is operational, life cycle based, and embedded in existing institutional review pathways rather than limited to predeployment checks alone. Patient-facing high-fidelity AI-generated video-synthetic or substantially AI-mediated video that presents realistic human likeness, voices, or clinical communication cues-is rapidly entering patient education and clinical communication. We propose a risk-and-ethics matrix that combines residual clinical risk (likelihood × severity after mitigations) with an ethical alignment score that operationalizes autonomy, beneficence, nonmaleficence, and justice to yield actionable dispositions (encourage, permit with oversight, restrict or redesign, or prohibit). The framework links each disposition to dossier-based review, minimum controls, and postdeployment monitoring triggers-focused on measurable outcomes (eg, comprehension, content-attributable follow-up burden, incidents and complaints, and equity gaps) as well as provenance and change control-to support auditable, revisitable decisions over the system life cycle.
13 May 2026
Read appraisal →Current pain and headache reports
Telemedicine in Pediatric Headache in a Post-COVID-19 World: A Narrative Review and Practical Implementation
PURPOSE OF REVIEW: Pediatric migraine is a leading cause of disability worldwide, yet access to pediatric headache specialists remains limited due to workforce scarcities and geographic disparities. This review examines the evolution of telemedicine in headache care, evaluates current evidence for safety and efficacy, and explores its role in improving access and multidisciplinary management. RECENT FINDINGS: Randomized trials and observational studies demonstrate that telemedicine provides clinical outcomes comparable to in-person visits with high patient satisfaction and reduced logistical burden. Emerging data support its safety in non-acute headache evaluation as well as benefit of supporting multidisciplinary care. Professional societies, including the American Headache Society and the American Academy of Pediatrics, endorse telemedicine as an appropriate modality for headache management. Telemedicine has matured into a sustainable, evidence-based approach for pediatric headache care. When implemented thoughtfully, it expands access, supports multidisciplinary treatment, and maintains safety, positioning it as an essential component of future headache care delivery models.
12 May 2026
Read appraisal →Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Telemedicine adoption, pandemic-related fear, and treatment adherence in cancer care during COVID-19: a prospective cohort study
PURPOSE: To evaluate the impact of telemedicine adoption and pandemic-related fear on treatment adherence, healthcare utilization, and supportive care processes among patients undergoing cancer therapy during the COVID-19 pandemic. METHODS: In this prospective cohort study, we followed 149 cancer patients over two years to evaluate telemedicine utilization, treatment modifications, and COVID-19-related fear. We employed validated psychometric tools, including the COVID-19 Fear Scale. RESULTS: Telemedicine adoption (24.8% of patients) was associated with fewer hospital visits (7.3 ± 3.2 vs 9.4 ± 4.1, p = 0.004) and reduced emergency room utilization (16.2% vs 46.4%, p < 0.001). Treatment modifications occurred in 55.9% of patients, predicted by COVID-19 infection (OR = 2.8, 95% CI:1.7-4.6) and neutropenia (OR = 2.1, 95% CI:1.3-3.4). High fear scores were linked to increased mortality (8.1% vs 2.7%, p = 0.032), disease progression (37.8% vs 21.4%, p = 0.018), lower treatment adherence (75.7% vs 87.5%, p = 0.041), and higher hospitalization rates (51.3% vs 24.1%, p < 0.001). CONCLUSION: This study demonstrates that telemedicine can reduce acute care utilization while treatment modifications and high pandemic-related fear significantly worsen cancer outcomes. These findings highlight the need for oncology teams to proactively integrate remote care strategies and targeted psychological support to maintain treatment adherence and mitigate adverse outcomes during health crises.
10 May 2026
Read appraisal →Journal of advanced research
Flexible wearable medical devices: from material innovations and data processing to intelligent healthcare applications
BACKGROUND: Flexible wearable medical devices drive healthcare transformation via non-invasive, real-time physiological monitoring and personalized management. Traditional rigid devices lack long-term comfort, while chronic disease care and telemedicine demand reliable, patient-centered solutions. Advances in materials (carbon nanomaterials, liquid metals, hydrogels) enable stretchable, biocompatible substrates adapting to bodily movements. Innovative sensing (PPG, EEG, sweat-based detection) tracks blood pressure, glucose, and neural signals accurately. Key challenges include insufficient sensor flexibility, lagging supervision, data security issues, and large-scale production difficulties, requiring interdisciplinary collaboration. AIM OF REVIEW: This review integrates cutting-edge advances in flexible wearable medical devices, covering material innovations, sensing breakthroughs, power management, and AI-driven data analysis. It evaluates strategies to enhance biocompatibility of carbon composites, liquid metals, and hydrogels, analyzing improvements in device sensitivity, biocompatibility, and real-world applicability. It critically discusses machine learning's role and limitations in chronic disease management, telemedicine, and sports optimization. Key unresolved challenges include lagging regulations, privacy risks in multi-source data fusion, mismatched sensing development, and large-scale production difficulties. The aim is to provide a scalable, secure, and clinically translatable roadmap for future research. KEY SCIENTIFIC CONCEPTS OF REVIEW: Core technologies involve carbon nanomaterials (e.g., graphene), liquid metals (structurally optimized for balanced conductivity and flexibility), and hydrogels (preferred as flexible substrates for mimicking natural soft tissues' mechanics and biocompatibility). Sensing technologies (PPG, EEG, sweat-based detection) enable non-invasive, real-time monitoring of vital parameters like blood pressure, glucose, and neural signals. AI decodes complex physiological data for predictive diagnosis, while IoT/5G integration advances telemedicine. Current limitations include poor sensor flexibility, lagging regulations, and large-scale production hurdles, contrasting with trends like advanced sensing, new materials, and hybrid diagnostic-therapeutic systems-highlighting flexible wearables' potential in intelligent healthcare.
5 May 2026
Read appraisal →Journal of medical Internet research
Digital Health Interventions for Family Members of ICU Patients: Current Evidence and Future Directions
A recent systematic review and meta-analysis of randomized trials evaluating digital health interventions for family members of intensive care unit (ICU) patients found no significant improvements in anxiety, depression, posttraumatic stress, quality of life, or communication quality. Rather than concluding that digital approaches are inherently ineffective, we argue that these null findings reflect identifiable and remediable limitations in intervention design, outcome measurement, and trial methodology. In this commentary, we examine four structural barriers that currently constrain the evidence base and outline the conditions that next-generation trials must meet to adequately address the questions raised by this review.
4 May 2026
Read appraisal →PloS one
Enhanced graph attention network by integrating Long Short-Term Memory for artificial emotion representation in multi-modality datasets
Emotion representation is a critical aspect of artificial intelligence, particularly in human-computer interaction and affective computing. Emotion recognition from multi-modal data remains challenging due to the complex semantic relationships between textual, audio, and visual features. This study proposes a hybrid model combining Enhanced Graph Attention Networks and Bidirectional Long Short-Term Memory to address this challenge. First, E-GAT captures structural dependencies between emotional features by constructing a semantic graph from text embeddings. Second, Bi-LSTM models temporal dynamics of sequential data, enabling effective integration of contextual information. We evaluated the model on three benchmark datasets: SemEval-2018 (text-only), RAVDESS (audio-visual), and CMU-MOSEI (multi-modal). Experimental results show that the proposed model achieves state-of-the-art performance: 58.5% accuracy and 68.7% F1-score on SemEval-2018, outperforming baseline models. On multi-modal datasets, it achieves 78.9% accuracy (RAVDESS) and 82.3% accuracy (CMU-MOSEI), demonstrating robust cross-modal generalization. This work advances emotion recognition by providing a unified framework for both text-only and multi-modal scenarios, with applications in human-computer interaction and mental health monitoring.
3 May 2026
Read appraisal →Journal of medical Internet research
Rapid Deployment of Telemedicine in HIV Care: Mixed Methods Study of Providers' Attitudes and Perceptions
BACKGROUND: The COVID-19 pandemic prompted an abrupt transition to telemedicine for HIV care, necessitating the exploration of provider attitudes and experiences to understand its ongoing viability and impact. OBJECTIVE: This study aimed to assess providers' attitudes toward and experiences with telemedicine at HIV clinics in the Chicago area during the COVID-19 pandemic at 2 time points and at 2 clinical sites. METHODS: We conducted a convergent mixed methods study to evaluate and explore providers' attitudes toward and experiences with telemedicine at HIV clinics in the Chicago area during the COVID-19 pandemic, applying the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework and the updated Consolidated Framework for Implementation Research. This study assessed HIV providers via surveys at 2 time points, capturing responses on the acceptability, appropriateness, feasibility, and maintenance of telemedicine. Semistructured key informant interviews were conducted on a random selection of 10 participants to explore perceived experiences with telemedicine. RESULTS: Among emailed providers, 43 of 83 (51.8%) and 27 of 82 (32.9%) responded to survey 1 and survey 2, respectively. The first survey recorded telemedicine usage at 75%, which decreased to 58% by the second survey. Overall, the majority of respondents agreed with statements that assessed telemedicine as appropriate, acceptable, and feasible. There were overall few statistical differences in responses between sites, although more providers at the community site indicated at least some potential value in telemedicine when compared to providers at the university hospital (100% agree or strongly agree vs 82.3%; P=.04) in survey 1. In survey 1, providers with more than 10 years of experience were less likely to report telemedicine helped them see more patients (31.6% agree or strongly agree vs 70.6% for providers with ≤10 y of experience; P=.008). Fewer experienced providers felt they could talk about private issues with their patients during telemedicine (57.9% of more experienced vs 88.3% of less experienced providers; P=.03). Key informant interviews provided qualitative insights into telemedicine integration, revealing mixed sentiments; providers appreciated the flexibility and accessibility that telemedicine offered but preferred in-person visits for their thoroughness, especially for physical examinations and laboratory tests. Despite initial barriers such as technical challenges and patient preferences for in-person visits, telemedicine was deemed feasible for maintaining communication and care quality. Providers highlighted the need for better technological support and ongoing training to optimize telemedicine usage. CONCLUSIONS: Our study underscores telemedicine as a sustainable adjunct to traditional HIV care, emphasizing the importance of addressing technological and training barriers to enhance its efficacy.
3 May 2026
Read appraisal →American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Tech That Scales: A Practical Framework for Artificial Intelligence-Enabled Cancer Care in Low- and Middle-Income Countries and Underserved US Counties
Cancer outcomes remain starkly unequal: 5-year survival rates for common malignancies in low- and middle-income countries (LMICs) often lag 20-40 percentage points behind high-income benchmarks, and similar disparities persist between well-resourced metropolitan centers and rural or safety-net settings within high-income countries. The gap is driven less by the absence of effective interventions than by workforce shortages, fragmented referral pathways, limited infrastructure, and loss to follow-up after abnormal screens. Technologies that scale must therefore function as deployable workflows integrating staffing, logistics, quality assurance (QA), governance, and monitoring not merely as stand-alone algorithms or devices.1 This review synthesizes evidence across four complementary technology families that address these constraints across the continuum of care: artificial intelligence (AI)-supported screening and triage as the population entry-point layer; Project ECHO telementoring as the workforce-capacity layer; electronic patient-reported outcomes and remote symptom monitoring as the longitudinal continuity layer; and AI-powered clinical trial prescreening hubs as the access-to-innovation layer. The technologies do not carry equal evidentiary weight, and they should not be deployed identically in every setting. Our aim is to show how oncology leaders can sequence them pragmatically inside a common operating logic while adapting to local infrastructure and governance. We organize the framework in patient journey order entry into care through screening, workforce support through telementoring, continuity through remote monitoring, and access to innovation through trial prescreening, and draw examples from both LMIC programs and underserved US settings. We therefore present a practical implementation playbook, including a 90-day launch checklist, staffing models, QA frameworks, equity and bias monitoring metrics, and a program outcomes dashboard designed for oncology leaders seeking to move beyond pilots toward durable, monitored deployment.
27 Apr 2026
Read appraisal →JMIR mental health
Effectiveness of a Fully Automated Mobile Therapeutic Versus a General Chatbot in Reducing Depression and Anxiety and Improving Well-Being: Feasibility Randomized Controlled Trial
BACKGROUND: Given the increasing prevalence of depression and anxiety disorders and enduring barriers to care, there is a critical need for alternative treatment options. Generative artificial intelligence (AI) chatbots show promise for increasing access to mental health care, though more direct research is needed to establish their efficacy. OBJECTIVE: This pilot study aimed to test the efficacy of a generative mental health chatbot rooted in solution-focused therapy compared to the general-purpose ChatGPT and an assessment-only control (AOC) group on depression, anxiety, and well-being. METHODS: A total of 185 English-speaking adults were recruited online and randomly assigned to one of three groups: AI therapy, ChatGPT, or AOC. Of these, 147 eligible participants filled out a pretreatment assessment. Over a 3-week period, the AI therapy group (n=44) was instructed to complete 3 structured, fully automated app-based sessions per week (9 total), while the ChatGPT group (n=60) was instructed to engage in 9 unstructured conversations with ChatGPT (GPT-4o-based models). The control group (n=43) received no intervention. In the AI therapy group, 39% (n=17) completed all sessions, as did 62% (n=38) of those in the ChatGPT group. Primary outcome measures, self-assessed online at baseline and postintervention, included the Patient Health Questionnaire-9 (PHQ-9), Overall Depression Severity and Impairment Scale (ODSIS) (depression), 7-item Generalized Anxiety Disorder Scale (anxiety), and World Health Organization Well-Being Index (5-item version) (well-being). Linear mixed effects models were used for data analysis. RESULTS: Compared to AOC, both the AI therapy group (d=-0.47; P=.01) and the ChatGPT group (d=-0.44; P=.02) demonstrated significant reductions in depression scores measured by PHQ-9. The AI therapy group showed nonsignificant reductions in anxiety (d=-0.37; P=.11) and ODSIS depression scores (d=-0.25; P=.22) and an increase in well-being (d=0.12; P=.53) compared to AOC. Similarly, a nonsignificant reduction in anxiety (d=-0.27; P=.22) and ODSIS depression scores (d=-0.12; P=.53) and an increase in well-being (d=0.20; P=.29) were observed in the ChatGPT group compared to AOC. The AI therapy group did not significantly outperform the ChatGPT group on any outcomes (PHQ-9: b=-0.19; d=0.03; P=.87; 7-item Generalized Anxiety Disorder Scale: b=-0.57; d=-0.11; P=.62; ODSIS: b=-0.59; d=-0.13; P=.50; and WHO: b=-0.38; d=-0.07; P=.69). CONCLUSIONS: Both the structured generative AI chatbot and ChatGPT showed a significant reduction in depression scores compared to the control group. No significant effects were observed across other outcomes, although descriptive trends indicated improvements in anxiety. While the AI therapy group showed descriptively better outcomes for depression and anxiety, differences between groups were not significant. A larger sample and longer intervention may be needed for the emerging trends to yield clinically meaningful effect sizes.
26 Apr 2026
Read appraisal →JMIR mHealth and uHealth
Effectiveness of Mobile Health Interventions in Pediatric Cancer: Systematic Review and Meta-Analysis of Randomized Controlled Trials
BACKGROUND: Cancer poses a significant threat to children's health, and mobile health (mHealth) is emerging as a key tool for remote disease management, health education, and follow-up. However, evidence of its effectiveness remains limited. OBJECTIVE: This study aimed to summarize the effects of mHealth interventions for pediatric cancer compared with usual care, providing evidence-based support for optimizing intervention models and improving patient outcomes. METHODS: A systematic search of 14 databases identified randomized controlled trials (RCTs) on mHealth apps for pediatric patients with cancer from inception to August 1, 2025. Two reviewers independently screened studies, extracted data, assessed bias risk, and graded evidence quality. The meta-analysis was conducted using RevMan 5.4 and Stata 15. RESULTS: A total of 24 RCTs involving 2645 patients were included. This review found that mHealth interventions significantly reduced infection rates (odds ratio [OR] 0.25, 95% CI 0.10-0.60; P=.002) and the overall incidence of peripherally inserted central catheter (PICC) complications (OR 0.16, 95% CI 0.10-0.24; P<.001), while improving quality of life (standardized mean difference [SMD] 1.34, 95% CI 0.13-2.55; P=.03), self-management ability (SMD 6.39, 95% CI 1.26-11.53; P=.01), and treatment adherence (OR 2.83, 95% CI 1.41-5.66; P=.003). However, mHealth interventions had no significant effect on PICC catheter displacement (OR 0.44, 95% CI 0.15-1.29; P=.13) or health knowledge (SMD 4.44, 95% CI -2.40 to 11.29; P=.20). Further high-quality studies are needed to verify their impact in these areas. The intervention components covered 9 behavior change techniques: goals and planning, feedback and monitoring, social support, shaping knowledge, repetition and substitution, reward and threat, comparison of outcomes, natural consequences, and regulation. CONCLUSIONS: This systematic review and meta-analysis synthesized evidence from RCTs. The findings support the use of mHealth to reduce infections and PICC-related complications among pediatric patients with cancer while improving quality of life, self-management capabilities, and treatment adherence. These results underscore the importance of incorporating mHealth strategies into pediatric cancer care and guide the development and enhancement of future mHealth interventions.
26 Apr 2026
Read appraisal →European journal of hospital pharmacy : science and practice
A collaborative telepharmacy model for dispensing and informed delivery from hospital to community pharmacies
BACKGROUND: This study examines the implementation of a collaborative telepharmacy programme in an outpatient pharmaceutical care unit (OPCU) at a tertiary hospital. The programme coordinates between the hospital pharmacy, community pharmacies, a pharmaceutical distributor, and the regional official college of pharmacists to optimise medication dispensing and delivery to outpatients. METHODS: The programme addressed challenges in operations, logistics, technology, legality, training and information. A protocol was developed defining the collaborative dispensing circuit, including criteria for patient selection and prioritisation. RESULTS: Over 39 months, 13 310 shipments were made to 1039 patients, averaging 17 daily. Each patient received about 13 deliveries. A total of 14 283 medications from 258 specialties were dispensed. The programme saved 512 534 km and 542 164 min (356 days) in travel. Each patient saved approximately 493 km and 522 min, reducing CO2 emissions by 58-116 kg per patient, or 72-145 tonnes overall. A survey of 130 patients revealed a 93% preference for this model over home or healthcare facility delivery. DISCUSSION: The implementation of telepharmacy programmes for dispensing hospital medication to community pharmacies marks a significant advancement in patient care. Initially rare, telepharmacy is now widespread, overcoming previous barriers. Programmes show similar effectiveness to home delivery, improving workflow and safety. Future improvements may include remote monitoring tools and video calls. Despite some limitations, such as economic analysis and tracking, telepharmacy has proven beneficial for patients, offering cost savings and enhanced confidentiality. CONCLUSION: The collaborative telepharmacy circuit was efficiently and safely implemented, offering an innovative approach that meets the needs and expectations of patients in the OPCU.
26 Apr 2026
Read appraisal →Neurology
Virtual vs In-Person Neurologic Ambulatory Care: A Case-Control Study of Subsequent Health Care Utilization
BACKGROUND AND OBJECTIVES: Implementation of telemedicine expanded options for outpatient neurology care. It remains uncertain which new neurology patients can be appropriately evaluated virtually. We compared subsequent health care utilization after virtual vs in-person new patient neurology visits across 3 academic medical centers. METHODS: We conducted a retrospective multicenter cohort study of adults with a new outpatient neurology visit from September 2020 through December 2021 using the Vizient Clinical Data Base and Clinical Practice Solutions Center databases. Virtual and in-person patients were matched 1:1 using propensity scores incorporating demographics, clinical characteristics, time period, and previous health care utilization. Outcomes were analyzed overall and stratified by neurologic chief complaint category and institution. We compared rates of subsequent neurologic clinic follow-up, emergency department (ED) visits, and hospitalizations after virtual and in-person encounters. Testing and all-cause ED visits/hospitalizations were also assessed. RESULTS: We identified 10,428 virtual and 36,767 in-person neurology new outpatient visits. After propensity score matching, 8,202 virtual visits were matched to 8,202 in-person visits. Neurology follow-up within 90 days did not differ between virtual and in-person visits (24.6% vs 23.7%, p = 0.18). Thirty-day neurology clinic follow-up was slightly lower after virtual visits, whereas follow-up at 6 months and 1 year was similar between groups. Neurologic ED visits and hospitalizations within 90 days were similar (0.9% vs 0.8%, p = 0.23 and 1.8% vs 1.7%, p = 0.47, respectively). All-cause ED visits and hospitalizations within 90 days were also comparable (1.8% vs 1.7%, p = 0.59 and 2.2% vs 1.8%, p = 0.13, respectively). Analyses by chief complaint found that 90-day follow-up was higher after in-person visits for dementia, whereas 30- and 90-day follow-up was higher after virtual visits for Parkinson disease and multiple sclerosis, and 90-day follow-up was higher after virtual visits for headache. Testing was more frequent after in-person visits for certain chief complaints. DISCUSSION: In this propensity score-matched multicenter cohort, new neurology patients seen virtually had similar downstream utilization as those seen in-person, including comparable 90-day follow-up and similar neurologic and all-cause ED visits and hospitalizations. Although follow-up varied modestly by chief complaint and testing was more frequent after some in-person visits, no major differences emerged overall.
25 Apr 2026
Read appraisal →JMIR formative research
Global Mapping of Telemedicine Regulation and Ethical Safeguards: Mixed Methods Exploratory Document Analysis
BACKGROUND: Telemedicine has become central to digital health strategies, yet the regulatory environment that shapes ethical safeguards and equitable access remains uneven and incompletely assessed across countries. Legal and normative instruments matter because they define requirements for privacy, consent, accountability, professional readiness, and barrier reduction. OBJECTIVE: This study aimed to map the current global landscape of normative instruments related to telemedicine and identify which ethical and social safeguards are explicitly addressed, with particular attention to equity. METHODS: We conducted a document analysis guided by the READ (ready the materials, extract data, analyze data, and distill findings) framework. From February 2024 to February 2026, we conducted a structured web-based search across all World Health Organization (WHO) member states with no language restrictions, using official government sources, statutory professional regulators, and institutional publication channels. Retrieval combined internal site searches, direct navigation, external search engine queries, and targeted snowball sampling to identify currently in-force instruments. Two researchers independently extracted and coded data using a predefined codebook. We operationalized 10 binary items covering regulatory presence and scope (questions 1 and 2), safeguards for data protection (question 3), consent and disclosure (questions 4 and 5), prior in-person prerequisites (question 6), monitoring (question 7), training requirements (question 8), and equity (questions 9 and 10). We summarized frequencies overall and stratified by WHO region and World Bank income group and conducted a qualitative thematic analysis of included normative instruments. RESULTS: Of the 194 WHO member states, 81 (41.8%) had at least one current normative instrument related to telemedicine in force. Among these, 72.8% (59/81) defined telemedicine or telehealth. Data protection provisions were most common (73/81, 90.1%), followed by mandatory informed consent (n=71, 87.7%) and monitoring mechanisms (n=65, 80.2%). Fewer countries required disclosure of telemedicine limitations (n=36, 44.4%) or mandated telemedicine-specific training (n=26, 32.1%). Prior in-person consultation requirements were uncommon (n=8, 9.9%). Equity-related safeguards were uneven: 51.9% (n=42) referenced justice, equity, or nondiscrimination, whereas 30.9% (n=25) included concrete barrier reduction provisions (eg, digital inclusion or accommodations for people with disabilities and minors). CONCLUSIONS: Telemedicine regulation is becoming more common, but both coverage and safeguarding content remain uneven. While privacy, consent, and monitoring are frequently addressed where regulation exists, disclosure, physician competency, and operational equity measures are less consistently specified. Strengthening telemedicine governance will require translating ethical commitments into enforceable standards that address digital determinants of access and protect groups at risk of exclusion.
25 Apr 2026
Read appraisal →American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists
Feasibility and acceptability of incorporating telemedicine into pharmacy services in the rheumatology clinics of the School of Medicine of the University of Puerto Rico
PURPOSE: Incorporating telemedicine into pharmacist services can promote medication adherence, reduce polypharmacy, and prevent adverse drug events as part of identification of drug-related problems. Our primary aim was to measure the acceptability to patients of telemedicine services using a standardized patient satisfaction survey and compare it to that for face-to-face services. Our secondary aim was to assess the feasibility of the telemedicine modality for pharmaceutical care interventions by measuring, quantifying, and categorizing drug-related problems identified during the service. METHODS: The study followed a prospective crossover design from October 2021 to September 2022. Adult patients (21 years or older) with rheumatic diseases evaluated at a university-based outpatient clinic were eligible to be enrolled. After the intervention, patients completed a survey regarding satisfaction and perception of their appointment. Descriptive statistics were used for patient demographic characteristics. Patient satisfaction with the modalities was compared using a t test. RESULTS: In this study, 296 patients were enrolled with a mean (SD) age of 50.4 (12.5) years. Participating patients were utilizing a mean (SD) of 10.2 (4.7) medications. No significant differences (P < 0.05) were observed for any of the survey questions when comparing responses for the face-to-face and telemedicine encounters. In general, patients strongly agreed that they were satisfied with the services they received and perceived the services as unique and valuable in both types of encounters. CONCLUSION: Overall satisfaction was very high, and no differences were found in the perception of or satisfaction with services between the telemedicine and face-to-face modalities.
24 Apr 2026
Read appraisal →JMIR research protocols
Evaluating the Role of Surgical Telementoring in the Acquisition of Surgical Skills in Laparoscopic Cholecystectomy: Protocol for a Pilot Randomized Controlled Trial
BACKGROUND: Developing surgical skills among residents requires time and resources, often in conflict with the goals of efficiency and hospital economics in surgical practice. Optimizing resident training may prevent a decline in quality. Skilled surgeons are vital to effective and safe surgical performance, yet the training trajectory for surgical residents is often inefficient, particularly in the era of minimally invasive surgery. A framework that efficiently disseminates surgical skills is essential to cultivate skilled future surgeons within an acceptable time frame. Surgical telementoring (ST) aligns well with minimally invasive surgery because the mentee operating in the field shares the telementor's perspective. Despite growing experience with telemedicine, data on educational outcomes remain limited. OBJECTIVE: We aim to conduct a pilot randomized controlled trial (RCT). Data collection will inform a future full-scale RCT evaluating whether real-time ST, combined with structured postoperative coaching, is superior to traditional on-site mentoring in developing laparoscopic cholecystectomy skills among surgical residents. METHODS: Eligible residents will be randomly assigned in a 1:1 ratio to either the intervention group (real-time ST and postoperative coaching) or the control group (traditional intraoperative hands-on teaching). This research adheres to the extended SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) statements for pilot RCTs and follows the intention-to-treat principle. Residents in both groups will perform 5 consecutive procedures under standardized intraoperative conditions. The primary outcomes are the Global Operative Assessment of Laparoscopic Skills (GOALS) score and the Non-Technical Skills for Surgeons (NOTSS). We hypothesize that the intervention group will show a 3- to 5-point improvement in the GOALS score compared with the control group. To achieve 0.8 statistical power, a P value <.05, and a 20% dropout rate in a definitive RCT, 12 residents per group are required. We present a pilot RCT with 5 residents per group. Challenges encountered during the trial will be reported, and amendments will be proposed to assess the need for a future definitive RCT. RESULTS: The primary outcomes will be technical and nontechnical surgical skills, measured by the GOALS and NOTSS scores, respectively. Patient-reported experience measures and satisfaction scores of eligible mentees and mentors will be analyzed as secondary outcomes. The ST system configuration at the 2 inclusion centers was completed in December 2023. Ethics approval and the most recent update report to ClinicalTrials.gov were obtained on October 23, 2023, and December 8, 2024, respectively. Recruitment of residents to the study commenced in spring 2024. Recruitment is expected to be completed in May 2026, with data analysis in November 2026 and manuscript submission of results in January 2027. CONCLUSIONS: The SURGTEACH (Surgical Telementoring in Acquisition of Surgical Skills of Laparoscopic Cholecystectomy) trial is the first pilot RCT evaluating ST for educational outcomes. This research may provide high-quality evidence to improve surgical education, particularly in rural hospitals.
18 Apr 2026
Read appraisal →Journal of neurointerventional surgery
Feasibility and non-inferiority of mobile telementoring for digital subtraction angiography: a single-center observational study
BACKGROUND: Telementoring is an emerging approach in surgical education that offers remote supervision and guidance through digital platforms. This study aimed to evaluate the feasibility and non-inferiority of a mobile-based telementoring system for digital subtraction angiography (DSA) and compare it with traditional face-to-face mentoring. METHODS: This prospective, single-center observational study included 71 patients who underwent DSA between April 2021 and May 2024. Patients were categorized into control (n=48, face-to-face mentoring) and telementoring (n=23) groups. A mobile telementoring system (JOIN, Allm Inc., Tokyo, Japan), which enabled real-time image sharing and voice communication between the examiner and the remote supervisor, was employed. The primary endpoints were contrast volume, procedural time, and radiation dose, with a non-inferiority margin of 20% applied. RESULTS: No significant differences were observed between the two groups in contrast volume (88.3±39.6 mL vs 97.1±36.4 mL, p=0.499), procedural time (44.1±17.7 min vs 50.7±19.0 min, p=0.308), or radiation dose (427.9±262.2 mGy vs 506.6±307.1 mGy, p=0.346). Non-inferiority was confirmed across all primary endpoints. No procedural complications occurred. Qualitative feedback indicated high user satisfaction, with the system facilitating effective remote supervision and decision-making. CONCLUSIONS: This study demonstrates the feasibility and non-inferiority of a mobile telementoring system for DSA, effectively supporting real-time remote guidance and reducing the need for on-site supervision. Its implementation may enhance access to expert mentoring, particularly in regions with limited specialist availability, contributing to equitable and efficient cerebrovascular care.
18 Apr 2026
Read appraisal →JMIR formative research
Development of a Contextualized, Research-Based Flemish Assessment Framework for Digital Care, Assistance, and Support: Delphi Study
BACKGROUND: The rapid evolution of digital technologies has transformed health, mental health, and social care, offering new modalities of digital care, assistance, and support through web-based platforms, mobile apps, extended reality, wearables, and artificial intelligence systems. Despite this proliferation, there is little consensus on what constitutes "high-quality" digital care. Challenges persist regarding data security, interoperability, accessibility, sustainability, and professional competence, whereas existing standards and regulations provide fragmented guidance. OBJECTIVE: This study aimed to develop a contextualized, consensus-based quality assessment framework for digital care, assistance, and support in Flanders, Belgium. For this purpose, perspectives across technology, organizational processes, and professional competencies were integrated. METHODS: The study used a multiphase design comprising (1) 10 expert interviews with Flemish government officials; (2) a narrative literature review of 303 peer-reviewed and gray literature sources; (3) a 3-round Delphi study with 50 experts across 5 domains (end users, facilitators, technology developers, deontology and ethics experts, and digital inclusion and media literacy experts); and (4) 4 complementary focus groups and 3 interviews with specialists in artificial intelligence, regulation, social work, mental health, and IT. The Delphi rounds gathered iterative feedback through open-ended elicitation, structured rating, and classification of quality criteria. Quantitative data were analyzed using descriptive statistics, whereas qualitative feedback was subjected to thematic analysis. RESULTS: A total of 50 experts participated in round 1, a total of 40 (80%) participated in round 2, and 27 (54%) participated in round 3. Round 1 generated 577 unique quality criteria, consolidated into 26 clusters organized under 3 pillars: technology, organization, and professional competencies. The relative importance across pillars was balanced (mean score 37.29, SD 12.38 for technology; 33.33, SD 10.39 for professional competencies; and 29.80, SD 10.45 for organizations). Accessibility, reliability, and safety ranked highest for the technology; vision, quality monitoring, and infrastructure ranked highest for organization; and support, digital competencies, and ethics ranked highest for professional competencies. The finalized framework included 112 criteria, of which 35 (31.3%) were designated as optional and 77 (68.8%) were designated as minimum requirements. Focus groups and interviews validated the framework's comprehensiveness and usability, emphasizing proportional implementation, user centrality, and alignment with European Union regulations. Stakeholders highlighted the need for tools, training, and governance mechanisms to ensure adoption and sustainability. CONCLUSIONS: This study produced a codeveloped, context-sensitive quality assessment framework that balances technological robustness, organizational readiness, and professional competence in digital care, assistance, and support. The framework can serve both as a quality safeguard and a developmental road map. Accompanying self-assessment and governance tools enhance practical applicability. Implementation success will depend on governmental support, resource allocation, and structured feedback loops. Future research should pilot the framework in real-world settings, assess its impact, and establish mechanisms for continuous updates to maintain relevance in a rapidly evolving digital landscape.
17 Apr 2026
Read appraisal →Blood advances
HCT Pre-App program: a telemedicine-based prehabilitation for allogeneic hematopoietic cell transplant candidates
Frailty has emerged as a key component of allo-HCT candidate assessment and is closely associated with transplant outcomes. Exercise-based prehabilitation may improve transplant candidacy, yet real-world implementation is limited. Our institution implemented a structured Frailty Program (FP) to assess frailty and introduce prehabilitation interventions. This study describes the program's evolution and evaluates the impact of prehabilitation. Between April 2021 and April 2025, 185 consecutive allo-HCT candidates were included in 3 sequential FP phases. In the first phase (No-Prehab, n = 76), patients underwent frailty assessment only. In the second phase (Pilot-Prehab, n = 59), patients received a home-based, nonsupervised prehabilitation program. In the third phase (Tele-Prehab, n = 50), patients participated in the HCT Pre-App Program, a structured digital telemedicine intervention supervised by rehabilitation physicians. Frailty was assessed at first consultation and HCT admission using the HCT Frailty Scale. Median prehabilitation duration was 6 weeks. Adherence was high across frailty groups (76%-88%), with no adverse events. Prehabilitation improved frailty status: fit patients increased from 22% to 42% in the Pilot-Prehab cohort (P = .009) and from 34% to 56% in the Tele-Prehab cohort (P = .001). Tele-Prehab independently increased the odds of being fit at admission (odds ratio [OR], 3.86; P = .001) and reduced frailty incidence (OR, 0.17; P = .031). One-year OS and NRM were comparable across cohorts (OS, 74.5%, 84.5%, and 78.1%; P = .367) with a trend toward lower NRM among prehabilitated patients (NRM, 14.6%, 5.1%, and 5.6%; P = .075). Frailty is dynamic in allo-HCT candidates, and results support how home-based digital prehabilitation improves fitness before transplantation.
15 Apr 2026
Read appraisal →JMIR aging
Personalized Digital Care Program Allocation for Older Adults: Reinforcement Learning-Based Simulation Study
BACKGROUND: As the demand for innovative older adult care grows alongside a shortage of care workers, personalization is key to optimizing services and enhancing long-term sustainability. This study proposes an adaptive reinforcement learning (RL)-based framework to promote precision digital care by dynamically assigning care programs based on individuals' unique characteristics and evolving needs. Its effectiveness was evaluated through simulation-based experiments comparing multiple allocation methods within an artificial intelligence (AI)-powered care call service for older adults. OBJECTIVE: This study aimed to develop and evaluate an RL-based model for personalizing digital care program allocation to optimize care engagement and health outcomes among low-income older adults living alone. METHODS: We developed the framework by using contextual bandits, specifically Thompson Sampling, to maximize user outcomes. Four program allocation strategies were tested using a synthetic dataset of user features and program attributes. Simulations were conducted over multiple iterations to evaluate how the model adapts over time and optimizes program assignments compared with static methods. RESULTS: Four program allocation methods were compared across 100 simulation runs (n=3000 assignments per run) using 2 datasets (AI Call: n=1196; Community Health Survey [CHS]: n=72,812): (1) systematic allocation (baseline), (2) single best program based on population average, (3) idealized personalized delivery (theoretical upper bound), and (4) precision digital care using Thompson Sampling. Precision digital care outperformed baseline and population-average approaches, achieving outcomes comparable to the theoretical upper bound. Compared to systematic allocation, call success rates increased by 84.2% (AI Call) and 54.4% (CHS), Patient Health Questionnaire-2 depression scores decreased by 32.1% (AI Call) and 41.4% (CHS), and self-reported health scores improved by 19% (AI Call) and 22% (CHS). It also showed improved learning efficiency, refining assignments dynamically as it learned from user responses. CONCLUSIONS: Our findings emphasize the importance of personalization in digital care. We plan to refine and validate the model through a publicly funded AI care program for community-dwelling, low-income older adults living alone in the Republic of Korea. RL offers a scalable and effective approach to advance precision digital care delivery and support future innovations in aging services.
14 Apr 2026
Read appraisal →BMJ open respiratory research
What is the evidence for virtual wards or hospital-at-home care pathways for exacerbations of chronic obstructive pulmonary disease? A systematic review and meta-analysis.
OBJECTIVES: Given increasing interest in admission avoidance, we evaluated the evidence to support virtual wards (VW) and hospital at home (HaH) models of care during exacerbations of chronic obstructive pulmonary disease (ECOPD). DESIGN: A systematic review and meta-analysis. A comprehensive search of MEDLINE (1946 to March 2024), Embase (1974 to March 2024) and CENTRAL (searched 22 March 2024) was conducted. Risk of bias and a random effects meta-analysis were performed. POPULATION: Adults with an ECOPD presenting to the hospital or who require hospital-led care. INTERVENTIONS: VW: defined as assessments and interventions delivered remotely or HaH (defined as assessments and interventions delivered by healthcare professionals in patient's homes) care pathways, compared with hospital admission. PRIMARY AND SECONDARY OBJECTIVES: Safety (mortality rate of all causes, in-patient, 7 days and 30 days) and readmission rate in 7 and 30 days. Length of stay in hospital and changes in pulmonary function tests. RESULTS: One study assessed VWs (reported in two publications) and 10 assessed HaH. There were no changes in survival or short-term readmission rates attributable to the interventions and no evidence that VW or HaH care pathways reduced the total time a patient spent under hospital-led care, whether at home or in the hospital. CONCLUSIONS: More evidence is needed to support the widespread roll-out of HaH and especially VW pathways for ECOPD. PROSPERO REGISTRATION NUMBER: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024517565.
12 Apr 2026
Read appraisal →Open heart
Effect of a mobile health intervention optimised with artificial intelligence on blood pressure and other cardiovascular risk factors in adults with high blood pressure: rationale and design of My Intelligent Cardiac Assistant (MICArdiac) randomised controlled trial
INTRODUCTION: Control of blood pressure (BP) continues to be a challenge globally. Clinical trials have shown home BP monitoring and text-message interventions to lower BP. Integrating these to personalise supportive messaging in response to changing BP and activity through leveraging artificial intelligence (AI) could improve BP control. The aim of this trial is to examine the impact on BP, compared with a text-message only programme, of the My Intelligent Cardiac Assistant (MICArdiac) programme. MICArdiac is a 6-month programme comprising tracking of BP, physical activity and heart rate informing a content stream of AI-driven personalised messages to encourage BP self-management, as-necessary medical review to up-titrate medicines and cardiovascular preventative behavioural change. METHODS AND ANALYSIS: MICArdiac is a prospective randomised open-blinded endpoint randomised controlled trial with 1:1 (intervention:control) allocation and active control. Individuals aged 35 years old or above with high BP are randomised to the MICArdiac programme or to a text-message cardiovascular education programme. Recruitment started in primary care and hospital clinics in Western Sydney and moved to decentralised direct-to-community recruitment in the Australian Capital Territory, New South Wales and Victoria. Randomisation and allocation concealment occur via a secure web-based system. The primary outcome is mean daytime systolic BP measured by 24-hour Ambulatory Blood Pressure Monitoring at 6 months. Primary analysis will follow intention-to-treat principles; data analysts will be blinded. Process evaluation will be conducted. ETHICS AND DISSEMINATION: Ethics approval was obtained from Western Sydney Local Health District Human Ethics Research Committee (2021/ETH11379). TRIAL REGISTRATION NUMBER: ACTRN12622000091707.
11 Apr 2026
Read appraisal →BMJ open quality
Feasibility and early outcomes of a multi-site TeleHospitalist admissions programme: staff and patient perspectives from a large health system
BACKGROUND: Staffing shortages contribute to admission delays, fragmented care and hospitalist burnout. Although telemedicine has been widely adopted in critical care and subspecialties, its use in general inpatient admissions remains understudied. This study evaluated the feasibility, operational performance and early perceptions of a TeleHospitalist admissions programme designed to address nocturnal staffing shortages in a large academic health system. METHODS: In October 2024, Houston Methodist launched a nocturnal TeleHospitalist programme. The programme provided centralised coverage via audio-video technology, operating from 18:00 to 02:00 initially and expanding to 18:00-06:00. Adult patients admitted from the emergency department (ED) between October 2024 and August 2025 and clinical staff involved in admission workflows, were surveyed. Operational data on admission timeliness were extracted from the Epic electronic medical record, and patient and staff experiences were evaluated through structured surveys and qualitative feedback. RESULTS: Over 10 months, 1575 TeleHospitalist encounters were completed (median age 65 years (IQR 49 to 75); 56% were ≥65 years). Median hospital length of stay was 38.5 hours (IQR 17.3 to 66.3), and median ED arrival-to-admission time was 7.3 hours (IQR 4.7 to 12.8). Among 311 patient respondents (19.7%; median age 66.5 years (IQR 52.3 to 75.6); 5% were ≥65 years), satisfaction scores were high (median 4 (IQR 3 to 5). Staff responses (n=29) demonstrated strong endorsement: 86% favoured continuation, 79% reported comfort with the technology and 75% rated admission processes as better than traditional workflows. CONCLUSIONS: A system-wide TeleHospitalist admissions programme was feasible and well accepted by patients and staff. Older adults reported positive experiences, suggesting age is not a barrier to virtual inpatient care. Early findings indicate improved timeliness, communication and workflow efficiency while mitigating overnight staffing gaps. Future studies will evaluate long-term outcomes, cost-effectiveness and strategies to enhance privacy and patient engagement.
8 Apr 2026
Read appraisal →JMIR research protocols
Remote Management of Patients With Diabetic Macular Edema Receiving Long-Term Intravitreal Anti-Vascular Endothelial Growth Factor Therapy (RE-SHINE Study): Protocol for a Real-World Study
BACKGROUND: Long-term intravitreal anti-vascular endothelial growth factor therapy is the gold standard for treating diabetic macular edema (DME). However, poor treatment adherence in real-world settings often leads to suboptimal visual outcomes. Evidence-based remote management strategies are required to bridge the gap between clinical protocols and patient self-management. OBJECTIVE: This study aims to describe a remote management program based on the Behavior Change Wheel model designed to increase treatment adherence and improve disease outcomes for patients with DME receiving long-term anti-vascular endothelial growth factor therapy, and to report the study protocol. METHODS: The RE-SHINE study was structured into three phases: theoretical modeling, digital platform development, and a validation cohort study. The intervention included a smartphone-based app providing personalized health education, self-monitoring of vision (Amsler grid), injection reminders, and direct communication with health care providers. The efficacy of the remote management model was tested in a real-world cohort study. Participants were assessed at baseline and at each follow-up visit over 12 months. The primary outcome measure was best-corrected visual acuity, and secondary outcome measures included central retinal thickness and treatment adherence (injection rate and follow-up frequency). RESULTS: A total of 1006 patients with DME underwent initial screening, and 958 (95.2%) patients met the inclusion criteria, with only 7 patients declining follow-up. We anticipate that the remote management system will be both feasible and acceptable for patients with DME. It is hypothesized that the intervention group would demonstrate significantly higher levels of treatment adherence and better visual preservation compared to the retrospective control group. In addition, we intend to assess the impact of the digital intervention on patient-reported outcomes, encompassing quality of life and self-efficacy. Participant recruitment began in September 2023 and was completed by the time of submission. The data analysis is yet to begin. The results are expected to be published in 2026. CONCLUSIONS: A Behavior Change Wheel-based remote management approach could be a scalable and sustainable method to enhance adherence in patients requiring long-term intravitreal therapy. If proven effective, this model could be integrated into routine ophthalmic care to mitigate the risk of vision loss due to undertreatment in DME.
7 Apr 2026
Read appraisal →European journal of cardiovascular nursing
A review and promise of digital health technologies to promote global cardiovascular health
Digital health technologies include an array of mobile or digital devices and apps that may be used by patients to support lifestyle modification or medical apps that monitor vital parameters and provide data that may influence treatment decisions. The use of digital health technologies is a growing opportunity for disease prevention and management of cardiovascular disease (CVD) for both patients to engage in self-management as well as nurses to monitor patients remotely and facilitate clinical decision support. The aims of this review article are to provide an overview of pertinent digital health technologies in CVD care, address social determinants of health and other enablers/barriers to digital health implementation, and provide perspectives on novel models of care incorporating digital technologies. Based on the latest evidence, recommendations for special considerations and implementation of digital health technologies in low- and middle- vs high-income countries are presented. In addition, tables reviewing functionality of the digital tools and global examples of their use are provided. Extensive empirical evidence from diverse populations suggests adoption of these innovative tools has been low in clinical settings. We provide a table summarizing these barriers and include the facilitators that can improve the adoption of digital health tools to improve behavioral lifestyle modification. For learning purpose, implementation of an innovative model of care is illustrated graphically and in text. We include a call to action to achieve the maximum impact of digital technology to support nurses who work in almost all settings improving CVD prevention and management globally. The multiple roles of nurses using digital health for global CVD prevention and management are discussed in the settings of clinical practice, research, education, public health, health policy/leadership, and informatics.
5 Apr 2026
Read appraisal →Critical care clinics
Innovation, Technology, and Telemedicine in Critical Care
Critical care medicine is undergoing a major transformation driven by rapid technological innovation, digital integration, and telemedicine. This article examines how modern intensive care units (ICUs) are evolving into data-rich, precision environments equipped with advanced monitoring, organ support, and predictive analytics. Innovations such as artificial intelligence-enhanced decision support, portable ultrasound, and tele-ICU platforms are expanding diagnostic accuracy, remote access, and timely interventions. By tracing historical milestones to emerging technologies like smart ICUs and wearable biosensors, this article highlights the shift toward anticipatory, personalized care. It underscores the importance of evidence-based adoption to ensure these tools improve outcomes.
4 Apr 2026
Read appraisal →Journal of telemedicine and telecare
Telemedicine and digital health for chronic conditions in pediatrics: A systematic review
BackgroundThe prevalence of chronic diseases in children and adolescents has significantly increased. The COVID-19 pandemic accelerated telemedicine adoption, leading to improved healthcare access and outcomes. Despite its benefits, telemedicine is still not fully integrated into standard care. Previous reviews have been limited in scope. This systematic review aims to provide a comprehensive overview of recent trials on web or app-based telemedicine for chronically ill children and adolescents, identifying interventions and outcomes for future healthcare strategies.MethodsA comprehensive search was conducted on PubMed on November 21, 2023, and updated on January 9, 2025. Results were filtered to include prospective intervention studies involving children and adolescents with chronic conditions and limited to publications from 2017 onwards. A total of 8699 results were retrieved, and 1506 titles were screened for eligibility, resulting in 116 studies included in the review.ResultsThese studies covered 45 different conditions, with the highest numbers for diabetes, asthma, and obesity. Telemedicine interventions varied, including gamification, video meetings, integrated devices, psychological components, symptom tracking, and educational content. Most studies reported high feasibility and patient satisfaction. Clinical outcomes improved in some cases, and none were worse than standard care. The heterogeneity limited direct comparisons and meta-analysis, and small sample sizes in many studies affected the generalizability and statistical significance of the findings.ConclusionsOur study highlights the potential of telemedicine in managing chronic illnesses among children, emphasizing the need for standardized methodologies, larger sample sizes, and continued investment in infrastructure and equitable policies to fully realize its benefits in improving accessibility, convenience, cost savings, and overall health outcomes.
4 Apr 2026
Read appraisal →Curr Opin Neurol
Neuro-vestibular rehab: new developments.
PURPOSE OF REVIEW: This review highlights recent advances in neuro-vestibular rehabilitation, with emphasis on vestibular adaptation and emerging mobile technologies. It summarizes developments in promoting vestibular plasticity and discusses novel tools such as virtual reality, wearable sensors, and telehealth platforms that enhance access, engagement, and outcomes. The scope is broad, focusing on general principles rather than specific populations. RECENT FINDINGS: New methods to enhance vestibulo-ocular reflex (VOR) adaptation include incremental adaptation devices and gamified exercises. Inducing VOR gain-down adaptation temporarily increases postural sway, which normalizes via sensory reweighting, demonstrating central compensation. Portable tools like StableEyes show promise in boosting VOR gain with brief sessions. Concurrently, technology-driven approaches are gaining traction. Gamified mobile applications and wearable sensors allow home-based rehabilitation with remote supervision and monitoring, showing promising results in conditions like multiple sclerosis. Virtual reality interventions and telehealth models accelerated during the COVID-19 era, expanding therapy delivery to underserved populations. Adjunctive methods such as vibrotactile feedback and galvanic vestibular stimulation are emerging as complementary therapies. SUMMARY: Recent developments are advancing vestibular rehabilitation by refining adaptive training techniques and leveraging digital tools to overcome barriers in access and adherence. These innovations point to a more personalized, technology-enabled approach to optimizing neuro-vestibular recovery.
1 Feb 2026
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