Search Results (142)

Background: Poor adherence to home exercise programs is a persistent challenge in physical rehabilitation and beyond. Data suggest that follow-up telehealth visits featuring behavior change techniques can improve adherence. However, the optimal frequency of behavioral support for effective self-management of technology-enabled home exercise programs remains unclear. This paper investigates how adherence to home exercise varies with the number of follow-up visits holding the type of exercise constant and measuring adherence objectively. Methods: A secondary analysis of adherence was conducted on participants from the VIGOROUS five-site, single-blind, and randomized controlled trial. Chronic (>6 months) community-resident stroke survivors with mild-to-moderate upper extremity hemiparesis (n = 111) were assigned 15 h of asynchronous video game-based home exercise over 3 weeks. Participants received behavioral support during (a) one single in-person session, (b) four in-person sessions, or (c) four in-person sessions plus six remote teleconsultations. Each consultation incorporated standardized behavior change techniques—contracting, feedback, self-monitoring, action planning, and guided problem solving—to promote increased paretic arm use during daily activities. The primary outcome was adherence (minutes exercising), objectively captured by the gaming system for 87 participants. Results: Six telehealth visits with remote therapeutic monitoring (RTM) increased home exercise completion by 3.3 h [95% CI: 0.008, 6.60]; each remote or in-person consultation was associated with an estimated 34 min of additional asynchronous home exercise. Conclusions: RTM, which does not require travel to a healthcare facility, is a time-efficient modality to enhance therapeutic engagement. Behaviorally focused telehealth visits boost stroke survivors’ adherence to a structured home exercise program. Full article

Background: Lower gastrointestinal endoscopy is a critical diagnostic and therapeutic procedure that is inherently resource-intensive. Following the COVID-19 pandemic, backlogs grew significantly, necessitating innovative management solutions. This study evaluates a multidisciplinary strategy integrating organizational interventions supported by a machine-learning-based semantic appropriateness assessment system to reduce pre-appointment waiting lists within the ULSS (Unità Locale Socio Sanitaria) 3 Serenissima health authority in the Venice metropolitan area. Methods: We retrospectively analyzed administrative and prescription data for adult patients undergoing lower gastrointestinal endoscopy from 2021 to 2024 across five hospitals. Evaluation metrics included the size and composition of the pre-appointment list (first vs. follow-up), service volumes, and prescription trends. Clinical appropriateness was assessed pre-procedure by adherence to RAO (Raggruppamenti di Attesa Omogenea, i.e., Homogeneous Waiting Groups) priority protocols and post-procedure by specialist reviews against guideline-based criteria in two samples from 2023 and 2024. Results: The pre-appointment list decreased significantly from 1, 542 in 2021 to only 14 in 2024. Procedural volume increased (+8% in 2023 vs. 2022), while overall prescriptions decreased, reflecting improved demand management. The provided-to-prescribed ratio rose from 64% in 2021 to 80% in 2024. Furthermore, RAO priority discordance declined, and inappropriate priority-class lower gastrointestinal endoscopy dropped from 26% in 2023 to 21% in 2024—a 5% absolute reduction. Conclusions: A combined strategy targeting both supply and demand—utilizing multidisciplinary governance, computerized decision-support management based on semantic analysis and RAO appropriateness assessment, structured pathways, and continuous audit—was associated with a marked reduction in waiting lists and improved appropriateness while simultaneously increasing service delivery. Expanding specialist–primary care consultation pathways, including teleconsultation, may further consolidate these improvements. Full article

Background/Objectives: Nutritional impairment is common across the cancer care continuum and may negatively affect treatment tolerance, functional status, quality of life, and caregiver burden. Digital tools may offer new opportunities to extend nutritional care beyond conventional clinical encounters, but their application in oncology remains heterogeneous and poorly defined. This narrative review aims to describe the current landscape of digital nutritional care in oncology, focusing on quality of life and patient perspectives while also considering the emerging role of caregivers. Methods: We conducted a narrative review of the available evidence on digital nutritional and lifestyle interventions in cancer care, including mobile applications, web-based platforms, teleconsultations, SMS- or email-based communication, remote monitoring systems, and hybrid models. Results: Digital nutritional and lifestyle interventions have been evaluated across active treatment, postoperative recovery, and survivorship. Available studies indicate that these interventions are generally feasible and may improve nutritional status, dietary behaviors, and physical activity levels. However, quality-of-life outcomes remain heterogeneous and have not been consistently assessed across studies. Some interventions combining digital tools with personalization, professional feedback, behavioral support, or clinically actionable monitoring reported favorable patient-centered outcomes. However, heterogeneity across studies limits the interpretation of these findings and the identification of specific intervention features associated with effectiveness. Patient and caregiver perspectives further highlight the importance of usability, trust, access to reliable information, communication with healthcare professionals, and practical support in the home setting. Conclusions: Digital nutritional care has the potential to extend and strengthen the delivery of nutritional care. Rather than replacing conventional interventions, it should be implemented through hybrid, supervised, equitable, and clinically integrated models. Future studies should consistently assess quality of life and other patient-reported outcomes while also addressing caregiver needs, digital burden, psychological safety, and inequalities in access. Full article

The COVID-19 pandemic accelerated the use of telemedicine and revealed persistent barriers in rural primary healthcare, especially among older adults and caregivers. This study proposes an LLM-mediated smart tele-primary-care framework to support respiratory infection monitoring in underserved communities of Córdoba, Colombia. The framework is based on caregiver-centered teleconsultation, remote monitoring, preventive education, structured symptom reporting, risk-based teletriage, and clinician-supervised digital support. The LLM functions as a controlled conversational interface to collect symptoms, organize patient information, reinforce health education, generate follow-up reminders, and identify predefined warning signs, without replacing clinical judgment or making autonomous diagnostic or treatment decisions. A preliminary scenario-based assessment examined whether the proposed workflow supports coherent triage and appropriate escalation of high-risk cases. Importantly, the described architecture—a telematic system for intelligent-engine access in assisted medicine support (ATIMAMS)—has been implemented and is currently operational at the Systems Engineering Program, Universidad del Sinú (Montería, Colombia), providing intelligent decision support for telemedicine consultations and remote assistance appointments in the study region. Overall, the study presents a context-sensitive, low-barrier, and safety-aware model for strengthening rural primary care, improving continuity of care, and supporting caregiver-mediated respiratory infection monitoring. Full article

Background and Objectives: Long-term real-world data regarding smoking cessation after myocardial infarction (MI) remain scarce in Southeastern Europe. Our objective was to estimate the prevalence of smoking status categories and to assess their association with long-term all-cause mortality in percutaneous coronary intervention (PCI) treated MI patients. Materials and Methods: We retrospectively collected data from electronic medical records of hospitalized MI patients who underwent PCI from 1 January 2016 to 1 January 2019. Smoking status and primary outcome (all-cause mortality) were assessed at baseline, during follow-up visits, and during teleconsultation until January 2024, and patients were categorized accordingly. Results: Never-smokers were older than persistent smokers (67.6 ± 11.4 vs. 57.3 ± 9.6 years; p < 0.01) and had a higher burden of hypertension and diabetes (both p < 0.01). At baseline, 47.9% were active smokers, 32.3% of them quit after an MI (with 77.7% being men). Over a median follow-up of 6.7 years, 220 deaths (17.3%) occurred. In a Cox regression model adjusted for age, persistent post-MI smoking significantly increased mortality risk (aHR 2.18; 95% CI 1.52–3.12; p < 0.001), former smokers had an aHR was 1.07 (p = 0.694), while quitters had 30% reduction in death risk (aHR 0.69; p = 0.217). Additionally, in the fully adjusted model, besides persistent smoking (aHR 2.18; p = 0.001), diabetes (aHR 1.69; p = 0.001) and age (aHR 1.09; p < 0.001) were independent predictors of all-cause mortality. Conclusions: Post-MI smoking more than doubles mortality risk, while sustained cessation reduces risk to near never-smoker levels, underscoring the need for aggressive, tailored cessation strategies in low-quit-rate regions such as Southeastern Europe. Full article

Background: Anxiety and depression are major contributors to mental-health burden and frequently co-occur in clinical practice. In tele–mental health, routinely captured operational variables such as consultation duration, visit frequency, and follow-up cadence may provide clinical digital phenotypes that complement conventional symptom scales. This study aimed to characterize anxiety–depression comorbidity in a large real-world tele–mental health cohort and to determine whether symptom severity was associated with distinct patterns of healthcare utilization. Methods: We conducted a retrospective real-world study of 3467 patients followed in psychiatry and psychology teleconsultations. Patients were classified as anxiety only, depression only, comorbid anxiety–depression, or neither. Symptom severity was categorized as mild, moderate, or severe using validated questionnaire-based measures; to improve comparability across instruments, scores were additionally harmonized using z-score normalization. Associations between anxiety and depression severity within the comorbid subgroup were examined using a chi-square framework. Telehealth utilization endpoints included consultation duration, number of consultations, and inter-visit interval, analysed overall and stratified by sex, age group, and symptom severity. Results: Anxiety and/or depression were present in 61.7% of the cohort (2140/3467), and anxiety–depression comorbidity accounted for 43.8% of all patients (1520/3467), indicating substantial real-world overlap. Within comorbid cases, anxiety and depression severity were strongly coupled, with depression severity varying systematically across anxiety severity strata (chi-square p = 9.88 × 10⁻¹⁰²). Compared with isolated anxiety or depression, comorbidity was associated with a more intensive healthcare-utilization profile, characterized by a higher mean number of consultations and shorter inter-visit intervals. Among comorbid patients, females showed greater longitudinal service use than males, with more visits and closer follow-up. Resource use also varied according to symptom burden, mainly in depression, supporting a graded relationship between clinical severity and operational care demand. Conclusions: In this large real-world tele–mental health cohort, anxiety–depression comorbidity was highly prevalent, clinically structured, and associated with distinct and measurable resource-use signatures. These findings highlight the novelty and practical value of integrating symptom severity with operational telehealth data to derive pragmatic digital phenotypes of care intensity. Such phenotypes may support risk stratification, triage, follow-up scheduling, and capacity planning in tele–mental health, with potential translational relevance for broader mental healthcare systems. However, these findings should be considered descriptive and hypothesis-generating and warrant further longitudinal validation in other clinical settings. Full article

Background/Objectives: Nursing home (NH) residents who become acutely unwell may frequently be conveyed to emergency departments (EDs). However, at least half of such low-acuity visits could be avoided. Telehealth-supported acute care programmes may potentially reduce unnecessary ED attendances and subsequent hospital utilization. This study aimed to describe a telehealth-based acute care programme for NH residents and to explore a pragmatic method for estimating potential inpatient bed-day savings using publicly available diagnosis-related group (DRG)-based average-length-of-stay (ALOS) data. Methods: A telehealth-based programme was implemented at Sengkang General Hospital (SKH) to support NH staff in the management of acutely unwell residents. NH residents were prospectively tracked for ED non-attendance within 14 days following teleconsultation. Potential inpatient bed-day savings were estimated by mapping teleconsultation diagnoses to relevant DRGs and referencing Singapore Ministry of Health Hospital Bill Size and Fee Benchmarks. Institution-specific and nationally derived ALOS estimates were compared using exploratory Bland–Altman agreement analysis. Results: Over two financial year periods, seven NHs participated in the programme. A total of 726 teleconsultations were conducted, of which 424 encounters were successfully managed within NHs without ED attendance within 14 days (ED non-attendance rate being 58.4%). Using DRG-based estimation, the projected inpatient bed-day savings for FY2023 were 694.31 days using institution-specific ALOS and 805.42 days using nationally derived ALOS estimates. Exploratory Bland–Altman analysis across 34 mapped diagnostic categories demonstrated a mean bias of 0.098 days (approximately 2.4 h), with 95% limits of agreement ranging from −1.31 to +1.51 days. Conclusions: The acute care programme may reduce ED attendances and hospitalizations among NH residents. Publicly available national DRG-based ALOS data may provide a pragmatic approach for estimating the potential inpatient hospital bed-day savings when institution-specific data are unavailable. Full article

Telemedicine is increasingly relevant in undergraduate medical education; however, most educational studies emphasize short-term interventions, learner satisfaction, or tele-Objective Structured Clinical Examination performance rather than evidence derived from sustained platform implementation. This multi-cohort longitudinal implementation study evaluated a multiplatform asynchronous telemedicine system integrated into simulation-based gynecology training across three consecutive academic periods at a medical simulation center in Ecuador. Platform-generated teleconsultation records were analyzed at the record level, with repeated records nested within student identifiers when students submitted more than one case. Because the expected number of submissions differed across cohorts as part of planned curricular refinements, cohort-level differences were interpreted descriptively as implementation and process indicators rather than as comparative evidence of learner performance. A total of 205 teleconsultation records from 95 student users were analyzed. Documentation quality was high for current illness documentation (98.5%), physical examination documentation (87.3%), and physiologically plausible vital signs (74.1%). Specialist responses were linked to 196/205 records (95.6%), with complete structured feedback among linked responses. Faculty expert review and learner-reported perceptions provided complementary educational evidence, including perceived usefulness of specialist feedback for gynecology learning. These findings support the feasibility of asynchronous telemedicine-supported simulation workflows and the value of platform-generated data for educational process evaluation, documentation monitoring, and feedback tracking, while not demonstrating individual competence improvement. Full article

Persons with Disabilities (PWDs) face persistent barriers to healthcare access, welfare services, and timely medical assistance, particularly where hospital information is fragmented across institutions. In Thailand, these challenges are exacerbated by heterogeneous Hospital Information Systems (HISs) across provincial, district, and sub-district hospitals. This study presents the design, implementation, and evaluation of an integrated mobile application and a hybrid Hospital Information Exchange (HIE) system to enhance healthcare accessibility and service coordination for PWDs. The platform integrates a user-centered mobile application (iOS and Android) with a hybrid data exchange architecture (MedEx Hybrid) combining an application programming interface (API) and Message Queuing Telemetry Transport (MQTT). This enables real-time and on-demand data exchange while accommodating hospitals with limited infrastructure. Key functionalities include disability registration, emergency medical service (1669) integration, appointment management, rights notification, service location mapping, teleconsultation, and peer communication. Deployment across 159 hospitals nationwide demonstrates system scalability and interoperability. The system supports secure access to electronic medical records and enables emergency responders to retrieve patient information during SOS events, improving continuity of care. Findings confirm the feasibility of the proposed system and its potential to support inclusive digital health and national healthcare interoperability. Full article

Background: Arterial hypertension is one of the most prevalent chronic non-communicable diseases and a leading cause of cardiovascular morbidity and mortality worldwide. Its burden remains particularly high in rural and resource-limited settings, where access to healthcare is often constrained by shortages of healthcare professionals, geographical barriers, and underdeveloped infrastructure. These factors may contribute to delayed diagnosis, suboptimal disease control, and increased risk of complications. In this context, telemedicine has emerged as a useful approach to supporting hypertension management and improving access to care in rural populations. Methods: This study presents a narrative review of the literature focusing on the application of telemedicine in the management of arterial hypertension in rural populations. A structured literature search of PubMed, Scopus, and Web of Science databases was conducted for studies published between 2015 and 2025. The review included randomized controlled trials, systematic reviews, meta-analyses, and observational studies evaluating telemedicine interventions, including remote blood pressure monitoring, mobile health applications, and teleconsultations. Study selection was guided by relevance to the research objective, with particular attention to rural and resource-limited contexts. Results: Telemedicine interventions have been associated with improvements in blood pressure control, treatment adherence, and access to healthcare services. Evidence from randomized controlled trials and meta-analyses suggests modest reductions in systolic and diastolic blood pressure compared with standard care. However, a substantial proportion of the available evidence originates from studies conducted in general or mixed populations rather than exclusively rural settings. Therefore, the applicability of these findings to rural contexts remains limited and should be interpreted with caution. The effectiveness of telemedicine may vary depending on differences in healthcare infrastructure, resource availability, digital accessibility, and organizational models across healthcare systems. Integrated care approaches involving primary healthcare providers and specialist support may contribute to improved continuity of care, although their impact appears to be context-dependent. Key barriers include limited telecommunication infrastructure, digital literacy challenges, and difficulties in integrating telemedicine into routine clinical practice. Conclusions: Telemedicine may represent a useful approach to supporting hypertension management in rural populations. However, its implementation requires careful consideration of local healthcare systems, patient characteristics, and organizational context. Telemedicine should be viewed as a context-dependent strategy rather than a uniform solution. Further context-specific research is needed to evaluate the long-term clinical, organizational, and economic impact of telemedicine interventions in rural hypertension management. Full article

Telemedicine has become a routine component of healthcare delivery, creating a need for dedicated undergraduate training in teleconsultation-specific competencies. Although artificial intelligence (AI)-assisted educational systems have been proposed as scalable tools to support teleconsultation training, the evidence remains fragmented, and their educational role is not yet clearly defined. Objective: To map and critically synthesize empirical evidence on AI-assisted teleconsultation training systems used in undergraduate medical education, with attention to skill domains, system capabilities, and implementation considerations. Methods: A structured narrative review with transparent search and study selection procedures was conducted. Literature published between January 2019 and December 2025 was identified through searches of major bibliographic databases and supplementary semantic and citation-based sources. Studies involving undergraduate medical students and evaluating AI-assisted interventions targeting teleconsultation-related skills were included. Results: Eight empirical full-text studies met the final eligibility criteria and were included in the structured narrative synthesis. Across the included studies, AI-assisted systems tended to show favorable patterns in structured domains such as verbal communication, history-taking, and selected aspects of early clinical reasoning during virtual consultations. Evidence regarding nonverbal communication and empathic or relational skills was more limited and methodologically heterogeneous, and human-based simulation remained important in these domains. Students generally reported favorable perceptions of usability, accessibility, and psychological safety, although satisfaction and perceived realism were not uniformly superior to human-based approaches. AI-assisted systems also appeared scalable and potentially cost-efficient, particularly as preparatory or supplementary training modalities. Conclusions: Current evidence suggests that AI-assisted teleconsultation training systems may be useful as preparatory and supportive tools in undergraduate medical education, particularly for structured and repeatable components of remote consultation practice. However, the evidence base remains limited and heterogeneous, and these systems do not replace human-led training for relational, nonverbal, and context-sensitive competencies. Their educational value appears greatest within blended training models that align platform capabilities with specific teleconsultation skills. Full article

Portable non-enzymatic electrochemical glucose sensors offer potential for decentralized healthcare and medical education; however, their integration into simulation-based teleconsultation training workflows remains limited. This study presents the functional integration of a portable copper-modified electrochemical glucose sensor into a web- and Android-based telemedicine platform within a simulation-based medical education framework. Screen-printed carbon electrodes were electrochemically activated and modified via copper electrodeposition. Surface and electrochemical characterization were performed using SEM-EDX and cyclic voltammetry, respectively, followed by chronoamperometry for quantitative detection. Glucose solutions in PBS (pH 10) were measured using 70 µL samples, and the resulting signals were converted into glucose values (mg/dL) through a calibration model and incorporated into simulated gynecological teleconsultation workflows. The sensor exhibited a stable amperometric response at +0.60 V, with a linear range of 3.125–50 mM (R² = 0.9822), an area-normalized sensitivity of 0.061 µA·mM⁻¹·cm⁻², and a limit of detection of 1.39 mM. Implementation within the simulation scenario (n = 26) demonstrated 69% high/very high perceived usability and 88% high/very high educational value. These results support the feasibility of functionally integrating portable electrochemical sensing into simulation-based teleconsultation training and provide a proof-of-concept framework for future technical refinement and broader educational validation. Full article

This systematic review analyzes how the introduction and progressive deployment of 5G networks have influenced the evolution of telemedicine between 2014 and 2024, focusing on their impact on performance, accessibility, and the feasibility of advanced clinical applications across the pre-COVID-19, COVID-19, and post-COVID-19 periods. The review was conducted in accordance with PRISMA guidelines and included publications retrieved from SCOPUS, PubMed, and Web of Science using a PICO-based search strategy. Studies were selected based on predefined inclusion and exclusion criteria, and extracted data included clinical parameters, network characteristics such as bandwidth and latency, geographic setting, and type of telemedicine service. A total of 45 studies met the inclusion criteria, with most published between 2020 and 2024. The most frequently reported applications were telediagnosis, particularly robotic ultrasound, followed by telesurgery and teleconsultation. The low latency enabled by 5G networks supported complex telesurgical procedures over distances exceeding 5000 km, while in ultra-remote areas, hybrid solutions combining 5G and fiber-optic networks were often adopted to ensure stable connections. The integration of robotic platforms and AI-based tools further enhanced the precision and reliability of remote procedures. Overall, 5G technology has significantly advanced telemedicine by enabling real-time, high-quality care over long distances, improving access to specialist services and supporting more equitable and efficient digital healthcare delivery, particularly in underserved regions. Full article

Background and Objectives: AI- and extended reality (XR)-enabled telemedicine is increasingly relevant to clinical training, yet evidence from Central and Eastern Europe is limited. We assessed Romanian medical students’ acceptance of AI/XR-enabled telemedicine and examined whether health literacy moderates the association between AI/XR knowledge and acceptance. Methods: We conducted an anonymous cross-sectional online survey of 212 medical students (years 1–6) at a single Romanian university (March 2024–June 2025). Acceptance was measured using a study-specific Acceptance Index (mean of three 4-point items: trust in AI-assisted recommendations, perceived improvement in telemedicine quality with AI/XR, and willingness to participate in AI/XR-enabled teleconsultations; internal consistency acceptable, Cronbach’s α ≈ 0.8). Health literacy was assessed with the validated Romanian version of the European Health Literacy Survey Questionnaire (HLS-EU-Q16). We performed group comparisons, Spearman correlations, multivariable and hierarchical regression with a Knowledge × Health Literacy interaction, and k-means clustering. Results: Participants had a mean age of 22.5 ± 1.9 years; 66.0% were female. Overall acceptance was high (2.9 ± 0.6). Acceptance was higher in clinical vs. preclinical years (3.1 ± 0.6 vs. 2.8 ± 0.5; p < 0.001; Cohen’s d ≈ 0.55) and in prior AI/XR users vs. non-users (3.2 ± 0.5 vs. 2.7 ± 0.6; p < 0.001; d ≈ 0.89). Knowledge correlated strongly with acceptance (ρ = 0.68; p < 0.001). In multivariable models (R² = 0.61), knowledge, perceived educational value, prior AI/XR use, and clinical stage independently predicted acceptance, whereas privacy concern and gender did not. Health literacy was sufficient in 64.2% and significantly moderated the knowledge–acceptance link (interaction p = 0.012). Conclusions: Romanian medical students report favorable acceptance of AI/XR-enabled telemedicine. Findings support curriculum integration that combines structured AI/XR teaching with literacy-sensitive scaffolding to ensure knowledge translates into informed, critical acceptance across student subgroups. Full article

Background: Digital transformation in healthcare has advanced rapidly in hospitals and primary care, while long-term care facilities have often lagged behind. In nursing homes, nurses play a central role in coordinating care and accessing medical expertise, yet digital tools to support these tasks remain inconsistently implemented. The CareConnect study, funded under the German Model Program for Telecare (§ 125a SGB XI), aimed to develop and implement a multiprofessional telecare system tailored to nursing home care. Objective: This implementation study examined the feasibility, acceptability, and early adoption of a multiprofessional telecare system in nursing homes, focusing on implementation processes, contextual influences, and facilitators and barriers to integration into routine nursing workflows. Methods: A participatory implementation design was employed over 15 months (June 2024–August 2025), involving a university hospital, two nursing homes (NHs), and four medical practices in an urban region in Germany. The telecare intervention consisted of scheduled video-based teleconsultations and interdisciplinary case discussions supported by diagnostic devices (e.g., otoscopes, dermatoscopes, ECGs). The implementation strategy followed the Standards for Reporting Implementation Studies (StaRI) and was informed by the Consolidated Framework for Implementation Research (CFIR). Data sources included telecare documentation, nurse surveys, researcher observations, and structured feedback discussions. Quantitative and qualitative data were analyzed descriptively and triangulated to assess implementation outcomes and mechanisms. Results: A total of 152 documented telecare contacts were conducted with 69 participating residents. Most interactions occurred with general practitioners (48.7%) and dermatologists (23%). Across all contacts, in 79% of cases, there was no need for an in-person visit or transportation. Physicians rated most cases as suitable for digital management, as indicated by a mean of 4.09 (SD = 1.00) on a 5-point Likert scale. Nurses reported improved communication, time savings, and enhanced technical and diagnostic skills. Key challenges included delayed technical integration, interoperability issues, and varying interpretations of data protection requirements across facilities. Conclusions: This pilot study suggests that telecare can be feasibly introduced and accepted in nursing home settings when implemented through context-sensitive, participatory strategies. Implementation science approaches are essential for understanding how telecare can be sustainably embedded into routine nursing home practice. Full article