The Journal of Telemedicine (TJT), also referred to as #tjtmed, was launched in late 2023, and the first issue was published in February 2024. The tjtmed is a quarterly journal with ISSN 3060-5830, subjected to peer review, and follows an open-access policy. Our publication has been the result of a collaboration with Ahvaz Jundishapur University of Medical Sciences (AJUMS). more… The invitation to submit a manuscript You are invited to submit your valuable article for the upcoming issue. Please note that the Journal of Telemedicine intends to publish your research summary (abstract) and personal experiences that are aligned with the aim and scope of the journal under the types of 'short communication' and 'letter to the editor'.
Ahvaz Jundishapur University of Medical Sciences (AJUMS)
The Maturity of Telemedicine: A Conceptual and Terminological Reflection
Telemedicine is rapidly expanding, and related terms such as telehealth, eHealth, and mHealth further complicate the landscape. MeSH offers a standardized framework but doesn't fully include newer terms. Using both preferred MeSH terms and specific keywords together can enhance clarity and improve search results.
Copyright (c) 2026 The Journal of Telemedicine
Optimizing Health Information Management: Performance of a Dashboard for Teaching Hospitals of Ahvaz Jundishapur University of Medical Sciences
Health Information Management (HIM) is vital for hospitals, enabling data collection, storage, and retrieval. Its effectiveness is often hindered by fragmented records, info overload, and poor decision-making. This study aimed to design and evaluate a performance dashboard for HIM in the Teaching hospitals of Ahvaz. This practical study was executed in three stages: (1) identifying key performance indicators (KPIs) via a literature review and expert consultations, (2) designing and developing the dashboard with QlikView, and (3) assessing usability using heuristic checklists and think-aloud methods. The dashboard integrated 47 KPIs, identified through a structured conceptual model and developed using QlikView, featuring interactive visualizations for health information management. While the evaluation found the dashboard useful, it also highlighted usability issues in control, error prevention, and visibility, indicating a need for improved data presentation and readability. Dashboards have proven to be essential tools in healthcare. From the perspective of hospital managers, the designed Health Information Management dashboard provides a clear, real-time view of key operational data, like patient wait times, admission trends, and record completion rates. This allows managers to quickly spot problems, make smarter decisions about staff and resources, and ultimately improve the efficiency and quality of their department's services.
Development of a Cost Model for Telemedicine Based on Medical Image Processing
Telemedicine has become an essential platform for delivering remote clinical services, particularly in specialties that are dependent on medical imaging. While AI-driven image-processing technologies can enhance diagnostic accuracy and improve workflow efficiency, most current telemedicine evaluations overlook their economic implications. This paper seeks to fill this gap by developing a dedicated economic framework for the costs and benefits of medical image processing. A three-phase approach was adopted. In the first place, a structured search across the major academic databases evaluated whether already published economic models included image-processing costs. Then, technical and financial parameters were integrated into a quantitative break-even model. Finally, experts in telemedicine, medical imaging, and health technology assessment reviewed the model, and its components were evaluated using Content Validity Index scores. The literature review revealed no previous models focused on image-processing costs, whereas expert assessment confirmed strong clarity and relevance in all components of this model. This validated framework provides a comprehensive basis for detailed estimates of implementation expenses, quantified potential savings, and the required patient volume to achieve financial sustainability. Further research should apply and test this model within a variety of clinical contexts.
Comparative Evaluation of ChatGPT-4o, Claude3.5, Gemini1.5 Pro, and Copilot for Determining Oral Medication Dosages
Delivering the most effective treatment to patients in the shortest possible time remains one of the most pressing challenges in modern healthcare. Large language models (LLMs) are widely accessible and have shown remarkable potential across domains, including achieving passing scores on the USMLE (United States Medical Licensing Examination), reducing physician visits, and lowering healthcare costs. This study aims to assess the capabilities, limitations, and practical considerations of integrating LLMs alongside pharmacists, with a focus on oral medication dosage prescriptions across different age groups. Questions were organized into seven domains, each comprising three Questions accompanied by clinical case scenarios, and prompts were designed using a zero-shot approach. Responses were evaluated against UpToDate using five criteria: response rate, accuracy, completeness, clarity, and safety. While none of the models had direct access to UpToDate, GPT-4o achieved the highest performance, correctly answering 100% of case-based questions. Copilot achieved 71.43% overall accuracy and 85.71% on case-based questions, but ranked lowest in completeness and clarity. Gemini 1.5Pro demonstrated the lowest response rate, while Copilot and Claude3.5 SonnetV2 generated unsafe outputs. Overall, the findings underscore the importance of evaluating context-dependent effectiveness before the broader adoption of large language models in clinical practice.
Generative Artificial Intelligence, Artificial Intelligence, Large Language Models, Drug Information Services, Electronic Prescribing
Copyright (c) 2025 The Journal of Telemedicine
Educational Needs in Self-Care Apps for Mast Cell Activation Syndrome: Perspectives from Specialists
Mast Cell Activation Syndrome (MCAS) is a condition that requires careful lifelong self-care. Mobile health apps are promising tools, but their content must be tailored to patient needs. This study aimed to identify and prioritize educational needs for designing a self-care mobile app for MCAS patients from the perspective of specialists. An applied, cross-sectional study was conducted using a descriptive survey. A purposive sample of 18 clinical immunologists and allergists completed a validated, researcher-developed questionnaire. They rated the importance of 58 educational items across 10 domains on a 5-point Likert scale. Data were analyzed using descriptive statistics. Fifty-two out of 58 items were considered essential (mean score ≥3.0), with the highest priority given to practical knowledge, such as proper use of an epinephrine auto-injector and trigger identification. Six items, including detailed breathing techniques and specific exercise types, did not meet the essentiality threshold. Additionally, specialists approved additional application features, such as a patient medical history section and a user feedback mechanism. This study provided an expert-validated foundation of essential educational content for an MCAS self-care app. The results offer an important blueprint for creating a targeted mHealth tool to empower patients, improve self-care, and enhance quality of life.
Mast Cell Activation Syndrome, Mobile Applications, Self Care, Patient Education
Review of the Status of Telemedicine Subject Presence in Scopus Database Scientific Articles
This study systematically examines scholarly trends in telemedicine research from 2020 to 2024, focusing on scientific growth and international collaboration. Using bibliometric data mining and lexical content analysis of 18,445 Scopus-indexed articles, we identified patterns in publication output, influential journals, active institutions, collaboration rates, and frequently used keywords. Articles were retrieved using the keywords “telemedicine,” “telehealth,” and “digital health,” with inclusion limited to English-language publications. Duplicates, conference abstracts, and non-peer-reviewed items were excluded. Findings showed an annual publication growth rate of 3.52%, with 24.17% of papers involving international collaboration. The International Journal of Environmental Research and Public Health, BMJ Open, and BMC Health Services Research had the highest publication volume. The University of California, the University of Toronto, and Harvard University led institutional contributions. Frequently occurring keywords included COVID-19, telemedicine, digital health, and health services accessibility. Despite progress, challenges such as infrastructure limitations, data privacy concerns, and uneven adoption across countries remain. This analysis highlights telemedicine’s transition from a supplementary tool to a core element of modern healthcare and underscores the need for future research on standardization, equity, and cross-national implementation.
Telemedicine, Digital Health, Bibliometrics, Intersectoral Collaboration, Health Care Reform
The Evolving Landscape of Digital Health Terminology
Mobile-Based Virtual Reality and Augmented Reality Apps in Rehabilitation: A Systematic Review
This systematic review aimed to identify the features and therapeutic content of mobile-based Virtual Reality (VR) and Augmented Reality (AR) rehabilitation apps and to examine the extent to which these apps are supported by scientific studies. A comprehensive search of the Apple App Store and Google Play Store was conducted using common rehabilitation-related keywords, specifically targeting English-language apps. Two reviewers independently screened and extracted data from eligible apps. Additionally, relevant scientific literature was reviewed to match qualitative and/or quantitative scientific studies with the selected apps. Out of 521 screened apps, 48 were directly related to rehabilitation. The most frequent app categories were health and fitness, education, and medical. Of the selected apps (N = 48), 35% were specifically designed for rehabilitation purposes. Additionally, 83.3% were VR-based, 6.25% were AR-based, and 10.4% included both VR and AR components. Fifteen studies were identified as related to the selected apps, including 7 Randomized Controlled Trials (RCTs). The findings suggest that despite the increasing availability of VR and AR apps in rehabilitation, only a small portion are supported by scientific evidence. These results may help individuals with disabilities and their caregivers make more informed decisions in selecting digital health tools for rehabilitation.
Rehabilitation, Mobile Applications, Virtual Reality, Augmented Reality
Telenursing in Elderly Care: A Hidden Challenge in the Healthcare Systems
The Importance of Telenursing in Nursing: A Paradigm Shift in Chronic Patient Care
Determining Key Performance Indicators for the Operational Dashboard of the IT Unit at Educational Hospitals
The growing healthcare data highlights the need for tools like dashboards to convert data into insights and inform decisions. This study aimed to identify the key performance indicators for designing an operational dashboard for the IT unit of Ahvaz Educational Hospitals, with the goal of enhancing transparency and efficiency. This developmental-applied study used a mixed-methods approach (qualitative-quantitative). KPIs were identified and validated through expert panel surveys, utilizing the Content Validity Index and Content Validity Ratio. A minimum dataset of 124 KPIs was finalized across seven domains: general duties, hardware, software, network, HIS, internet, and reporting. The dashboard was developed using a layered architecture (Data-Core-View) and technologies including ASP.NET Core, C#, MVC pattern, and Chart.js. Experts confirmed the relevance, clarity, and necessity of the KPIs. The dashboard enabled real-time IT performance monitoring, analytical reporting, and access control. Technological choices enhanced visualization accuracy and system responsiveness. The dashboard effectively improved IT performance monitoring and decision-making in educational hospitals, despite challenges like data sensitivity, system interoperability, and user resistance. The findings support the use of business intelligence tools in healthcare IT management.
Telenutrition: Opportunities after the COVID-19 Era, and Developing Countries’ Limitations
Identifying the Characteristics of Technology-Based Educational Interventions and Their Impact on Mothers' Breastfeeding Self-Efficacy
This review aims to identify the features of technology-based educational interventions and their effects on breastfeeding self-efficacy among mothers. Peer-reviewed articles published in Persian and English between 2015 and 2024 were collected. Various types of studies, including clinical trials, descriptive studies, mixed-methods research, and quasi-experimental studies (with or without blinding), were included. Databases such as Google Scholar, ScienceDirect, PubMed, Scopus, and domestic (Iranian) databases were searched using keywords like "breastfeeding," "educational technology," and "nursing mother." Out of 2,233 initially retrieved articles, 20 met the inclusion criteria, involving a total of 2,719 participants. Key variables examined included the type of technology used, delivery methods, and measured outcomes. The primary outcome assessed was mothers' breastfeeding self-efficacy, with major variables being intervention duration and breastfeeding self-efficacy. The findings indicate that interventions combining education with ongoing maternal support are the most effective technology-based approaches. While such interventions were widely implemented through mobile applications, maternal support was more prominent in interventions delivered via social networks and telephone follow-ups.
Investigating the Use of Online Social Networks to Obtain Health Information among Pregnant Women
This study aimed to explore various aspects of accessing health information through online social networks among pregnant women in Bojnurd. This cross-sectional study was conducted among 243 women from seven healthcare centers in 2024. Data were collected using an online questionnaire. The inclusion criteria encompassed proficiency in Persian and residency in Bojnurd, while the exclusion criteria included incomplete questionnaires. Descriptive statistics and analytical statistics were used for analysis, with a significance level set at p < 0.05. The mean scores for online social networks usage among the mothers were as follows: attitude (2.72), perceived ease of use (3.38), intensity of internet use (3.05), access to infant care information (2.95), childbirth-related information (2.89), pregnancy-related information (2.48), and postpartum information (2.13). A mean score above 3 indicates a desirable level. The results indicated that online health information seeking among the participating mothers was below average. Given the significant role of internet resources in alleviating maternal anxiety, it is recommended that websites provide necessary information for mothers.
Online Pharmacies Have Not Yet Been Widely Accepted by the Public: A Survey Study
The growth and expansion of online pharmacies have significantly transformed the drug supply chain, driven by consumer convenience and new behaviors arising from the pandemic. This study aimed to examine community perspectives on online pharmacies through a survey. A questionnaire was distributed to gather the attitudes of residents in Ahvaz, a major city in southwestern Iran. A total of 384 participants took part in the study. The data were analyzed using descriptive statistics through SPSS. Results indicated that while most people were aware of online pharmacies, a significant number remained unaware of their existence. Furthermore, individuals often choose not to use online pharmacies for several reasons, including concerns about privacy, security, and lack of trust, as they prefer shopping in person at local pharmacies. Additionally, satisfaction with online pharmacies was lower than expected, with nearly one-third of buyers reporting unaffordable experiences with their online purchases.
Transforming Dental Education in the Digital Age: Launching the Digital Demonstration Dental Room
Telerehabilitation in Pelvic Floor Disorders: A Feasible and Effective Approach
The Impact of Telemedicine on Access to Healthcare Services in Remote Areas
Telemedicine: A Cost-Effective Approach to IVF and Infertility Care
Developing a Mobile-based Educational Game to Enhance Dietary Habits for Type 2 Diabetes Patients through Artificial Intelligence Algorithms
This study aimed to design a mobile digital game to assist individuals with type 2 diabetes in better understanding food calories and the glycemic index, ultimately enhancing their management of the condition. The game was developed using fuzzy logic and initially tested in MATLAB 2018 before being converted to C# in Visual Studio and implemented in Unity. To develop the game, food calorie and glycemic index values were integrated into a fuzzy input system, utilizing a triangular membership function. The fuzzy output was translated into a numerical value through the centroid defuzzifier, employing the Mamdani fuzzy inference engine for determination. The outcome of this study was the development of a mobile game named "Diabetic Amoo," specifically designed for diabetic patients. Players advance through the first episode by correctly selecting appropriate food items, while the second stage focuses on educating them about low-sugar and low-calorie foods. Players receive ratings for their choices that range from "very bad" to "very good," with the goal of achieving a "very good" rating. By emphasizing patient education, such games can enhance motivation for self-care and improve adherence to diabetes diets and other health conditions.
Physicians’ View on Telemedicine during the Corona Outbreak: A Cross-Sectional Study Conducted in Imam Reza Teaching Hospital of Mashhad
Telemedicine uses information and communication technology (ICT) to provide remote care to patients, especially during outbreaks. This study aimed to evaluate the attitudes toward and knowledge about the telemedicine system among healthcare professionals. This cross-sectional study was conducted among physicians working at Imam Reza Hospital, affiliated with Mashhad University of Medical Sciences, in 2021. Data were collected using a well-structured self-administered questionnaire. A total of 133 specialists and subspecialists participated in this study, including 25 internists, 14 anesthesiologists, 10 cardiologists, 9 emergency medicine specialists, 9 radiologists, and 9 dermatologists. The average age and years of experience were 49.9 ± 8.6 and 13.4 ± 7.6, respectively. Investigating their attitudes toward and knowledge about telemedicine revealed that 50% of them had a “high” attitude, and their knowledge was above medium. Based on the research and the positive views on the use of telemedicine, especially during the recent pandemic, it can be concluded that this technology may be suitable for only specific healthcare tasks. However, healthcare organizations may benefit from implementing telemedicine in various aspects, such as reducing treatment costs and increasing the speed, accuracy, and quality of care provided to patients and injured individuals.
The Role of Telemedicine in the Early Detection and Management of Cardiovascular Diseases: A Systematic Review
Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, necessitating early detection and effective management to reduce morbidity and mortality. Telemedicine has emerged as an innovative approach to address healthcare delivery challenges, particularly in underserved areas. This systematic review evaluates the role of telemedicine in the Early detection of cardiovascular diseases. A systematic search of PubMed, Cochrane Library, Embase, and Web of Science databases was conducted for studies published between 2014 and 2024. Eligible studies included randomized controlled trials, observational studies, and meta-analyses that evaluated telemedicine interventions in CVD detection or management. Study quality was assessed using the Cochrane Risk of Bias tool and the Newcastle-Ottawa Scale. Fifteen studies covered diverse telemedicine approaches such as remote monitoring, wearable devices, and mobile applications. Key findings included: Early Detection: Telemedicine improved diagnostic efficiency, with wearable devices identifying arrhythmias (sensitivity 95%) and telemonitoring accelerating hypertension diagnoses by 25%. Telemedicine is a valuable tool for the early detection and management of CVDs, significantly improving clinical outcomes. Despite its benefits, challenges such as the digital divide, privacy concerns, and provider training must be addressed. Future studies should explore the cost-effectiveness, scalability, and long-term outcomes of telemedicine in cardiovascular care.
Development of an Internet of Things-based Smart Health Monitoring System for COVID-19
The application of machine learning (ML) -based Internet of Things (IoT)- in healthcare during COVID-19 has proven effective in preventing disease spread. This paper proposed an IoT system to remotely detect and monitor suspected COVID-19 cases at home. To develop the system, IoT sensors, a mobile application, and ML algorithms were used for data analysis. The IoT node tracked health parameters, including body temperature, heart rate, blood oxygen saturation level, and blood pressure, as well as age and gender information, then used a user interface to display health status updates and sent them to a cloud server. The decision-making module based on ML algorithms was placed on the server side. The system's efficiency was evaluated using accuracy, precision, recall, and F1 score metrics. Doctors could view and track users' health status through an interface, and Pearson's correlation coefficient was used to determine the correlation between sensor measurements and vital sign devices. The proposed system achieved 99.05% accuracy, 98.66% precision, 99.32% recall, and 98.99% F-measure using the random forest algorithm. The Pearson correlation coefficient also showed a strong correlation in evaluating the sensors. The system could aid in diagnosing and monitoring suspected COVID-19 cases.
Quality Evaluation and Content Analysis of Mobile Applications in Tuberculosis: MARS Approach
Copyright (c) 2024 The Journal of Telemedicine
The Impact of Remote Consultation on Mortality Rate of Covid-19 Patients Admitted to Intensive Care Units
During critical situations like the COVID-19 pandemic, a shortage of medical staff not only impacts the mortality of coronavirus patients but also contributes to delayed diagnoses of other life-threatening disorders like cancer. This study aimed to compare death rates and outcomes in patients with COVID-19 admitted to Intensive Care Units through remote and in-person consultations, and Conducted at Razi Hospital in Ahvaz, the cross-sectional study analyzed patient records from ICU admissions in August and September 2020, dividing them into case and control groups. Internal medicine residents provided remote consultations based on requests from attending specialists in other hospitals. Of the 58 patients included, the Remote Consultation group had significantly shorter wait times for clinical consultation (2.6 vs. 4 hours, p=0.002). There were no differences in waiting times for writing orders or death rates between the groups (p=0.9 and p=0.7, respectively). Medication usage also showed no significant variance. Remote healthcare offers benefits like long-term cost-effectiveness, reduced healthcare facility strain, shorter outpatient clinic wait times, and minimized exposure risks during pandemics like COVID-19.
The Development of a National Telemedicine Service Maturity Model
Health Literacy and Preferred Sources of Health Information among Mothers Attending Comprehensive Health Service Centers in Semnan County
This descriptive-analytical study aimed to assess the health literacy status among mothers and their preferred sources of health information in 2023. Study carried out on 330 mothers attending comprehensive health service centers (CHC) in Semnan County to monitor the health of their two-year-old children. Data collection tools included demographic information, the Iranian Adults Health Literacy (HELIA) questionnaire, and a checklist regarding health information sources. The data were organized and analyzed using SPSS25 with appropriate statistical tests. The mean age of the mothers was 32.5 ± 5.5 years. Approximately 43% held a Bachelor's degree, 69% were housewives, and 31% were employed. The overall average health literacy score was 68.39%, with the highest score in the access sub-domain (75.36%) and the lowest in the evaluation sub-domain (38.69%). Healthcare providers (44.2%) and the internet and social media (32.7%) were the most utilized sources for obtaining health information. The health literacy status of mothers was relatively favorable. Mothers' reliance on healthcare providers to receive appropriate health information is logical and meanwhile internet and social media plays critical role in health information and can be account as e learning source. However, it needs to enhance access and use of accurate and reliable information.
Telemedicine's Role in Shaping the Future of Healthcare Delivery: A Systematic Review
Telemedicine, defined as the use of telecommunication technologies to provide healthcare services remotely, has significantly evolved over the past few decades. This review aims to provide a comprehensive analysis of telemedicine's development, current applications, benefits, challenges, and potential to shape the future of healthcare delivery. A systematic literature search was conducted across multiple databases, including PubMed, MEDLINE, Scopus, and Google Scholar. Keywords used in the search included "telemedicine," "telehealth," "remote healthcare," "digital health," and "virtual care." The search was limited to articles published between 2014 and 2024. Additionally, reference lists of relevant articles were reviewed to identify further sources. After applying inclusion and exclusion criteria, a total of 20 articles were selected for detailed analysis. The review found that telemedicine has significantly improved healthcare access, particularly in remote and underserved areas. It has enhanced patient engagement and convenience, leading to higher satisfaction rates. However, several challenges remain, including technological barriers, regulatory and licensing issues, inconsistent reimbursement policies, and resistance to adoption among patients and providers. Future trends indicate a growing integration of artificial intelligence, wearable technology, and personalized medicine in telemedicine practices. Telemedicine is transforming healthcare delivery by making it more accessible, efficient, and patient-centered.
Determining the Minimal Dataset for a Mobile-Based Self-Care Educational System for Corneal Transplant Patients
Self-care methods for patients with corneal transplants are very important. Currently, traditional self-care guidelines have limitations. Determining the minimal dataset for a self-care educational system is essential to improve the quality of content and services provided to corneal transplant patients. This study aimed to determine the necessary dataset for a corneal transplant educational system. This applied research study was conducted using a descriptive-developmental approach in 2022-2023. In the first stage, the researchers identified the clinical-educational content required, and the questionnaire's content validity and face validity were evaluated by six ophthalmologists and ten faculty members of the Department of Health Information Technology and Medical Informatics. The reliability of the questionnaire was calculated using Cronbach's alpha with SPSS software version 26. Among the elements surveyed, those with a mean score above 3.5 were selected as essential data elements, and those with a mean score between 2.5 and 3.5 were selected as desirable data elements. The minimal dataset for a self-care educational system was presented in four sections: demographic data elements, clinical data elements, educational data elements, and functional and technical requirements. A proposed model for an electronic educational system can be developed based on the results.
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Evaluating user satisfaction with the electronic prescription system in Ahvaz medical centers: A social insurance organization perspective
The electronic prescription system is a significant concern for medical staff today. In Iran, the social insurance organization, as a non-profit entity, is responsible for providing health insurance services. This research aims to evaluate the electronic prescription system of social insurance from the perspective of users in selected medical centers in Ahvaz. This descriptive and analytical research was conducted in 2022-2023. The study's statistical population comprised all users of the electronic prescription system in the pharmacies, laboratories, and clinics of medical centers affiliated with social insurance organization. The descriptive statistical methods used to analyze the checklist results were based on five Likert ranges. The results indicated a relative level of satisfaction among respondents in the medical centers of the Social Insurance Organization. Specifically, 58.6% of respondents rated the performance quality of the laboratory subsystem as high. In comparison, 37.3% and 30.7% of respondents rated the performance quality of the pharmacy and clinic subsystems as high, respectively. Despite the relative satisfaction with this system's features and its widespread use in social insurance-affiliated medical centers, some drawbacks hinder user interaction quality and can negatively impact the treatment process. Therefore, it is essential to identify and address these issues to improve the system.