Displaying publications 1 - 20 of 204 in total

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  1. Bradley P, Deane J, O'Hara J, Kennedy M, Carrard VC, Cheong SC, et al.
    BMJ, 2024 Mar 01;384:q512.
    PMID: 38428988 DOI: 10.1136/bmj.q512
    Matched MeSH terms: Telemedicine*
  2. Pathmanathan R, Anuar Zaini MZ
    JUMMEC, 1996;1:3-4.
    Matched MeSH terms: Telemedicine
  3. Hui CY, Condon K, Kolekar S, Roberts N, Sreter KB, Simons SO, et al.
    PLoS One, 2024;19(12):e0314914.
    PMID: 39729438 DOI: 10.1371/journal.pone.0314914
    The value of 'data-enabled', digital healthcare is evolving rapidly, as demonstrated in the COVID-19 pandemic, and its successful implementation remains complex and challenging. Harmonisation (within/between healthcare systems) of infrastructure and implementation strategies has the potential to promote safe, equitable and accessible digital healthcare, but guidance for implementation is lacking. Using respiratory technologies as an example, our scoping review process will capture and review the published research between 12th December 2013 to 12th December 2023. Following standard methodology (Arksey and O'Malley), we will search for studies published in ten databases: MEDLINE, EMBASE, CINAHL, PsycINFO, Cochrane Library, Web of Science, Scopus, IEEE Xplore, CABI Global Health, and WHO Medicus. Our search strategy will use the terms: digital health, respiratory conditions, and implementation. Using Covidence, screening of abstracts and full texts will be undertaken by two independent reviewers, with conflicts resolved by a third reviewer. Data will be extracted into a pilot-tested data extraction table for charting, summarising and reporting the results. We will conduct stakeholder meetings throughout to discuss the themes emerging from implementation studies and support interpretation of findings in the light of their experience within their own networks and organisations. The findings will inform the future work within the ERS CONNECT clinical research collaboration and contribute to policy statements to promote a harmonised framework for digital transformation of respiratory healthcare.
    Matched MeSH terms: Telemedicine
  4. Lee SWH, Ooi L, Lai YK
    Front Pharmacol, 2017;8:330.
    PMID: 28611672 DOI: 10.3389/fphar.2017.00330
    Importance: Telemedicine has been shown to be an efficient and effective means of providing care to patients with chronic disease especially in remote and undeserved regions, by improving access to care and reduce healthcare cost. However, the evidence surrounding its applicability in type 1 diabetes remains scarce and conflicting. Objective: To synthesize evidence and quantify the effectiveness of telemedicine interventions for the management of glycemic and clinical outcomes in type 1 diabetes patients, relative to comparator conditions. Data Sources: MEDLINE, EMBASE, Cochrane Library, Web of Science, PsycINFO, and CINAHL were searched for published articles since inception until December 2016. Study Selection: Original articles reporting the results of randomized controlled studies on the effectiveness of telemedicine in people with type 1 diabetes were included. Data Extraction and Synthesis: Two reviewers independently extracted data, assessed quality, and strength of evidence. Interventions were categorized based upon the telemedicine focus (monitoring, education, consultation, case-management, and peer mentoring). Main Outcome and Measure: Absolute change in glycosylated hemoglobin A1c (HbA1c) from baseline to follow-up assessment. Results: A total of 38 studies described in 41 articles were identified. Positive effects on glycemic control were noted with studies examining telemedicine, with a mean reduction of 0.18% at the end of intervention. Studies with longer duration (>6 months) who had recruited patients with a higher baseline HbA1c (≥9%) were associated with larger effects. Telemedicine interventions that involve individualized assessments, audit with feedback and skill building were also more effective in improving glycemic control. However, no benefits were observed on blood pressure, lipids, weight, quality of life, and adverse events. Conclusions and Relevance: There is insufficient evidence to support telemedicine use for glycemic control and other clinically relevant outcome among patients with type 1 diabetes.
    Matched MeSH terms: Telemedicine*
  5. Tsoi K, Yiu K, Lee H, Cheng HM, Wang TD, Tay JC, et al.
    J Clin Hypertens (Greenwich), 2021 03;23(3):568-574.
    PMID: 33533536 DOI: 10.1111/jch.14180
    The prevalence of hypertension is increasing along with an aging population, causing millions of premature deaths annually worldwide. Low awareness of blood pressure (BP) elevation and suboptimal hypertension diagnosis serve as the major hurdles in effective hypertension management. The advent of artificial intelligence (AI), however, sheds the light of new strategies for hypertension management, such as remote supports from telemedicine and big data-derived prediction. There is considerable evidence demonstrating the feasibility of AI applications in hypertension management. A foreseeable trend was observed in integrating BP measurements with various wearable sensors and smartphones, so as to permit continuous and convenient monitoring. In the meantime, further investigations are advised to validate the novel prediction and prognostic tools. These revolutionary developments have made a stride toward the future model for digital management of chronic diseases.
    Matched MeSH terms: Telemedicine*
  6. Anisha SA, Sen A, Bain C
    J Med Internet Res, 2024 Jul 16;26:e56114.
    PMID: 39012688 DOI: 10.2196/56114
    BACKGROUND: The rising prevalence of noncommunicable diseases (NCDs) worldwide and the high recent mortality rates (74.4%) associated with them, especially in low- and middle-income countries, is causing a substantial global burden of disease, necessitating innovative and sustainable long-term care solutions.

    OBJECTIVE: This scoping review aims to investigate the impact of artificial intelligence (AI)-based conversational agents (CAs)-including chatbots, voicebots, and anthropomorphic digital avatars-as human-like health caregivers in the remote management of NCDs as well as identify critical areas for future research and provide insights into how these technologies might be used effectively in health care to personalize NCD management strategies.

    METHODS: A broad literature search was conducted in July 2023 in 6 electronic databases-Ovid MEDLINE, Embase, PsycINFO, PubMed, CINAHL, and Web of Science-using the search terms "conversational agents," "artificial intelligence," and "noncommunicable diseases," including their associated synonyms. We also manually searched gray literature using sources such as ProQuest Central, ResearchGate, ACM Digital Library, and Google Scholar. We included empirical studies published in English from January 2010 to July 2023 focusing solely on health care-oriented applications of CAs used for remote management of NCDs. The narrative synthesis approach was used to collate and summarize the relevant information extracted from the included studies.

    RESULTS: The literature search yielded a total of 43 studies that matched the inclusion criteria. Our review unveiled four significant findings: (1) higher user acceptance and compliance with anthropomorphic and avatar-based CAs for remote care; (2) an existing gap in the development of personalized, empathetic, and contextually aware CAs for effective emotional and social interaction with users, along with limited consideration of ethical concerns such as data privacy and patient safety; (3) inadequate evidence of the efficacy of CAs in NCD self-management despite a moderate to high level of optimism among health care professionals regarding CAs' potential in remote health care; and (4) CAs primarily being used for supporting nonpharmacological interventions such as behavioral or lifestyle modifications and patient education for the self-management of NCDs.

    CONCLUSIONS: This review makes a unique contribution to the field by not only providing a quantifiable impact analysis but also identifying the areas requiring imminent scholarly attention for the ethical, empathetic, and efficacious implementation of AI in NCD care. This serves as an academic cornerstone for future research in AI-assisted health care for NCD management.

    TRIAL REGISTRATION: Open Science Framework; https://doi.org/10.17605/OSF.IO/GU5PX.

    Matched MeSH terms: Telemedicine*
  7. Mohamed H, Ismail A, Sutan R, Rahman RA, Juval K
    BMC Pregnancy Childbirth, 2025 Feb 13;25(1):153.
    PMID: 39948493 DOI: 10.1186/s12884-025-07209-8
    INTRODUCTION: Digital health technologies have vastly improved monitoring, diagnosis, and care during pregnancy. As expectant mothers increasingly engage with social media, online platforms, and mobile applications, these innovations present valuable opportunities to enhance the quality of maternal healthcare services.

    OBJECTIVE: This review aims to assess the applicability, outcomes, and recent advancement of digital health modalities in antenatal care.

    METHOD: We conducted a scoping review by searching four electronic databases (Scopus, Web of Science, PubMed, EBSCOhost), performing manual searches of Google Scholar, and examining the references of relevant studies. Eligible studies included original research published in English between 2010 and 2024 involving the use of digital health technologies for antenatal care, complying with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping review guidelines.

    RESULTS: One hundred twenty-six eligible articles were identified, with the majority (61.11%) conducted in high-income countries, including the United States, United Kingdom, and Australia. Digital health studies have increased over time, driven by telehealth adoption in affluent nations. Interventions predominantly focused on patient-provider consultations, remote monitoring, and health education, complementing in-person visits or as a substitute when necessary. High levels of acceptance and satisfaction were reported among users. These interventions primarily targeted general maternal care (28.57%), gestational diabetes mellitus (15.07%), and mental health (13.49%) while also addressing gestational weight management, hypertensive disorders, high-risk pregnancies and maternal education. The findings demonstrated positive outcomes in managing clinical conditions, enhancing knowledge, promoting birth preparedness, and improving antenatal care access and utilisation. Additionally, the findings revealed the cost-effectiveness of these approaches in alleviating financial burdens for patients and healthcare systems.

    CONCLUSION: Digital health is emerging as a pivotal tool in maternal and child care, fostering positive outcomes and high acceptance among patients and healthcare providers. Its integration into antenatal care ensures the maintenance of standard care quality, with no adverse effects reported despite limited discussions on safety and privacy concerns. As these technologies continue to evolve, they are set to redefine antenatal care by offering more accessible, efficient, and patient-centred solutions, ultimately shaping the future of maternal healthcare delivery.

    Matched MeSH terms: Telemedicine*
  8. Qi Y, Mohamad E, Azlan AA, Zhang C, Ma Y, Wu A
    J Med Internet Res, 2025 Jan 23;27:e64981.
    PMID: 39847411 DOI: 10.2196/64981
    BACKGROUND: Cardiovascular disease (CVD) is a major global health issue, with approximately 70% of cases linked to modifiable risk factors. Digital health solutions offer potential for CVD prevention; yet, their effectiveness in covering the full range of prevention strategies is uncertain.

    OBJECTIVE: This study aimed to synthesize current literature on digital solutions for CVD prevention, identify the key components of effective digital interventions, and highlight critical research gaps to inform the development of sustainable strategies for CVD prevention.

    METHODS: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a comprehensive search in Web of Science, Scopus, and PubMed to identify original English-language studies published between January 2000 and May 2024 that examined primary or secondary CVD prevention through digital solutions. The exclusion criteria included: telephone-only interventions, abstract-only publications, methodology-focused studies without primary data, studies without participants or specific groups, and studies with no follow-up period. The literature search used the string with terms like "digital health," "mHealth," "mobile health," "text message," "short message service," "SMS," "prevention," "prevent," "cardiovascular disease," "CVD," etc. Study bias was assessed using the RoB 2 (Cochrane Collaboration) and the ROBINS-I tool (Cochrane Collaboration). Data on prevention components, prevention types, study design, population, intervention, follow-up duration, personnel, and delivery settings were extracted.

    RESULTS: A total of 2871 studies were identified through the search. After excluding ineligible studies, 30 studies remained, including 24 randomized controlled trials. The reviewed digital solutions for CVD prevention focused on baseline assessment (29/30, 97%), physical activity counseling (18/30, 60%), tobacco cessation (14/30, 47%), blood pressure management (13/30, 43%), and medication adherence (10/30, 33%). The technologies used were categorized into 3 types, smartphones and wearables (16/30, 53%), email and SMS communications (12/30, 40%), and websites or web portals (3/30, 10%). The majority of the study outcomes addressed blood pressure (14/30, 47%), exercise capacity (12/30, 40%), weight (12/30, 40%), and lipid profile (11/30, 37%), while fewer focused on nicotine dependence (9/30, 30%), medication use (8/30, 27%), quality of life (7/30, 23%), dietary habits (5/30, 17%), intervention adherence (4/30, 13%), waist circumference (4/30, 13%), and blood glucose levels (2/30, 7%).

    CONCLUSIONS: Digital solutions can address challenges in traditional CVD prevention by improving preventive behaviors and monitoring health indicators. However, most evaluated interventions have focused on medication use, quality of life, dietary habits, adherence, and waist circumference. Further studies are needed to assess the long-term impact of more comprehensive interventions on key cardiovascular outcomes.

    Matched MeSH terms: Telemedicine*
  9. Judson JP
    JUMMEC, 1996;1:17-21.
    Matched MeSH terms: Telemedicine
  10. Judson JP
    JUMMEC, 1996;1:5-8.
    Matched MeSH terms: Telemedicine
  11. Suleiman AB, Mohan J
    Telemed Today, 1998 Dec;6(6):16.
    PMID: 10339345
    Matched MeSH terms: Telemedicine*
  12. Al-Samarraie H, Ghazal S, Alzahrani AI, Moody L
    Int J Med Inform, 2020 09;141:104232.
    PMID: 32707430 DOI: 10.1016/j.ijmedinf.2020.104232
    BACKGROUND: Despite attempts to reform the healthcare delivery system in the Middle East, expectations for its progress have been-and for some still are-somewhat slow.

    OBJECTIVE: This study reviewed progress in the use and adoption of telemedicine in Middle Eastern countries. The key dimensions affecting the progress of telemedicine in these countries were identified.

    METHOD: A systematic review of the literature was conducted on 43 peer reviewed articles from 2010 to 2020. The review followed the scientific process of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of identification, selection, assessment, synthesis, and interpretation of findings.

    RESULTS: The results showed that progress made in the utilization of telemedicine was insufficient and varies across Middle Eastern countries. Certain cultural, financial, organizational, individual, technological, legal, and regulatory challenges were found to prevent telemedicine from being fully used to the point where the full range of medical services can be provided. For example, doctor and patient resistance, poor infrastructure, lack of funding, poor system quality, and lack of information technology training were associated with the low adoption of telemedicine in the region.

    CONCLUSION: This review provides a number of recommendations that will help policymakers to move toward the integration of innovative technologies in order to facilitate access to health information, health services, and training. It also recommends that health initiatives should focus on health education and health promotion in order to increase public awareness of the benefits of telemedicine services in the region.

    Matched MeSH terms: Telemedicine*
  13. Khoo S, Mohbin N, Ansari P, Al-Kitani M, Müller AM
    PMID: 34071342 DOI: 10.3390/ijerph18115798
    This review aimed to identify, evaluate, and synthesize the scientific literature on mobile health (mHealth) interventions to promote physical activity (PA) or reduce sedentary behavior (SB) in cancer survivors. We searched six databases from 2000 to 13 April 2020 for controlled and non-controlled trials published in any language. We conducted best evidence syntheses on controlled trials to assess the strength of the evidence. All 31 interventions included in this review measured PA outcomes, with 10 of them also evaluating SB outcomes. Most study participants were adults/older adults with various cancer types. The majority (n = 25) of studies implemented multicomponent interventions, with activity trackers being the most commonly used mHealth technology. There is strong evidence for mHealth interventions, including personal contact components, in increasing moderate-to-vigorous intensity PA among cancer survivors. However, there is inconclusive evidence to support mHealth interventions in increasing total activity and step counts. There is inconclusive evidence on SB potentially due to the limited number of studies. mHealth interventions that include personal contact components are likely more effective in increasing PA than mHealth interventions without such components. Future research should address social factors in mHealth interventions for PA and SB in cancer survivors.
    Matched MeSH terms: Telemedicine*
  14. Kohl SE, Van Tilburg C, Flaherty GT
    J Travel Med, 2019 Jan 01;26(1).
    PMID: 30535106 DOI: 10.1093/jtm/tay145
    Matched MeSH terms: Telemedicine*
  15. D'Souza B, Suresh Rao S, Hisham S, Shetty A, Sekaran VC, Pallagatte MC, et al.
    Hosp Top, 2021 02 02;99(4):151-160.
    PMID: 33528313 DOI: 10.1080/00185868.2021.1875277
    The Coronavirus disease 2019 (COVID-19) pandemic has necessitated medical centers across the world to deliver healthcare through telemedicine. We discuss the adoption, delivery of telemedicine services at a tertiary care center and patient satisfaction involving 456 patients in south India. Most respondents had sought telemedicine care at the department of Medicine (16.23%). The maximum satisfaction was reported by patients in OBG (100%). The responses were generally positive across all the age groups. The paper offers insights on best practices adopted at the center, lessons learnt, and provides recommendations for health care systems offering telemedicine during COVID-19 times.
    Matched MeSH terms: Telemedicine*
  16. Haque R, Ho SB, Chai I, Abdullah A
    F1000Res, 2021;10:911.
    PMID: 34745565 DOI: 10.12688/f1000research.73026.1
    Background - Recently, there have been attempts to develop mHealth applications for asthma self-management. However, there is a lack of applications that can offer accurate predictions of asthma exacerbation using the weather triggers and demographic characteristics to give tailored response to users. This paper proposes an optimised Deep Neural Network Regression (DNNR) model to predict asthma exacerbation based on personalised weather triggers. Methods - With the aim of integrating weather, demography, and asthma tracking, an mHealth application was developed where users conduct the Asthma Control Test (ACT) to identify the chances of their asthma exacerbation. The asthma dataset consists of panel data from 10 users that includes 1010 ACT scores as the target output. Moreover, the dataset contains 10 input features which include five weather features (temperature, humidity, air-pressure, UV-index, wind-speed) and five demography features (age, gender, outdoor-job, outdoor-activities, location). Results - Using the DNNR model on the asthma dataset, a score of 0.83 was achieved with Mean Absolute Error (MAE)=1.44 and Mean Squared Error (MSE)=3.62. It was recognised that, for effective asthma self-management, the prediction errors must be in the acceptable loss range (error<0.5). Therefore, an optimisation process was proposed to reduce the error rates and increase the accuracy by applying standardisation and fragmented-grid-search. Consequently, the optimised-DNNR model (with 2 hidden-layers and 50 hidden-nodes) using the Adam optimiser achieved a 94% accuracy with MAE=0.20 and MSE=0.09. Conclusions - This study is the first of its kind that recognises the potentials of DNNR to identify the correlation patterns among asthma, weather, and demographic variables. The optimised-DNNR model provides predictions with a significantly higher accuracy rate than the existing predictive models and using less computing time. Thus, the optimisation process is useful to build an enhanced model that can be integrated into the asthma self-management for mHealth application.
    Matched MeSH terms: Telemedicine*
  17. Rafiq MT, Abdul Hamid MS, Hafiz E
    Adv Rheumatol, 2021 10 24;61(1):63.
    PMID: 34689837 DOI: 10.1186/s42358-021-00221-4
    OBJECTIVE: The objective of this randomized controlled trial (RCT) was to investigate the effectiveness of the lower limb rehabilitation protocol (LLRP) combined with mobile health (mHealth) applications on knee pain, mobility, functional activity and activities of daily living (ADL) among knee osteoarthritis (OA) patients who were overweight and obese.

    METHODS: This study was a single-blind, RCT conducted at Teaching Bay of Rehmatul-Lil-Alameen Post Graduate Institute of Cardiology between February and November 2020. 114 knee OA patients who were overweight and obese were randomly divided by a computer-generated number into the rehabilitation group with mHealth (RGw-mHealth) to receive LLRP + instructions of daily care (IDC) combined with mHealth intervention, rehabilitation group without mHealth (RGwo-mHealth) to receive LLRP + IDC intervention and control group (CG) to receive IDC intervention. All three groups were also provided leaflets explaining about their intervention. The primary outcome measure was knee pain measured by the Western Ontario and McMaster Universities Osteoarthritis Index score. The secondary outcome measures were mobility measured by the Timed up and go (TUG) test, functional activity measured by the patient-specific functional scale (PSFS), and ADL measured by the Katz Index of independence in ADL scores.

    RESULTS: Among the 114 patients who were randomized (mean age, 53 years), 96 (84%) completed the trial. After 3-months of intervention, patients in all three groups had statistically significant knee pain reduction (RGw-mHealth: 2.54; RGwo-mHealth: 1.47; and CG: 0.37) within groups (P  0.05). As indicated in the overall analysis of covariance, there were statistically significant differences in the mean knee pain, mobility, functional activity, and ADL changes between groups after 3-months (p 

    Matched MeSH terms: Telemedicine*
  18. Che Johan NAS, Rasani AAM, Keng SL
    Br J Nurs, 2023 Jan 26;32(2):74-80.
    PMID: 36715528 DOI: 10.12968/bjon.2023.32.2.74
    BACKGROUND: The use of mobile health (mHealth) applications, which provide opportunities to improve health and lessen health inequalities, is increasing. Studies assessing the readiness and ability of patients in Malaysia with chronic kidney disease (CKD) to use mobile phone apps to manage their health are limited.

    AIMS: This study aimed to assess the readiness and ability to use mHealth apps among patients with CKD in north-east Peninsular Malaysia.

    METHODS: A cross-sectional study was undertaken, using a convenience sample of 100 CKD medical inpatients in a tertiary teaching hospital. A structured, self-administered questionnaire on readiness and ability to use mHealth apps was adopted.

    FINDINGS: Nearly one in five patients (18%) actively used health applications. More than three-quarters (77%) were aged >40 years and a similar proportion were ready to use mHealth apps (78%), and nearly half (46%) were confident about connecting their device to wifi. There was a correlation between ability and readiness to use mHealth apps (r=0.4; P<0.05).

    CONCLUSIONS: Fewer than half of participants had a good command of mHealth applications. Therefore, support on the use of these apps is needed, and healthcare managers need to consider this.

    Matched MeSH terms: Telemedicine*
  19. Abdullah B, Snidvongs K, Poerbonegoro NL, Sutikno B
    Int J Environ Res Public Health, 2022 Oct 20;19(20).
    PMID: 36294211 DOI: 10.3390/ijerph192013632
    The COVID-19 pandemic presented unique challenges to the delivery of healthcare for patients with allergic rhinitis (AR) following its disruption and impact on the healthcare system with profound implications. Reliance on self-care for AR symptom management was substantial during the pandemic with many patients encouraged to only seek in-person medical care when necessary. The advantage of digital technology becomes apparent when patients and healthcare providers had to change and adapt their method of interaction from the regular physical face-to-face consultation to telehealth and mobile health in the provision of care. Despite the pandemic and the ever-evolving post pandemic situation, optimal management of AR remains paramount for both patients and healthcare professionals. A reshaping of the delivery of care is essential to accomplish this goal. In this paper, we present what we have learned about AR management during the COVID-19 pandemic, the role of digital technology in revolutionizing AR healthcare, screening assessment in the identification and differentiation of common upper respiratory conditions, and a framework to facilitate the management of AR in primary care.
    Matched MeSH terms: Telemedicine*
  20. Garfan S, Alamoodi AH, Zaidan BB, Al-Zobbi M, Hamid RA, Alwan JK, et al.
    Comput Biol Med, 2021 Nov;138:104878.
    PMID: 34592585 DOI: 10.1016/j.compbiomed.2021.104878
    During the coronavirus disease (COVID-19) pandemic, different technologies, including telehealth, are maximised to mitigate the risks and consequences of the disease. Telehealth has been widely utilised because of its usability and safety in providing healthcare services during the COVID-19 pandemic. However, a systematic literature review which provides extensive evidence on the impact of COVID-19 through telehealth and which covers multiple directions in a large-scale research remains lacking. This study aims to review telehealth literature comprehensively since the pandemic started. It also aims to map the research landscape into a coherent taxonomy and characterise this emerging field in terms of motivations, open challenges and recommendations. Articles related to telehealth during the COVID-19 pandemic were systematically searched in the WOS, IEEE, Science Direct, Springer and Scopus databases. The final set included (n = 86) articles discussing telehealth applications with respect to (i) control (n = 25), (ii) technology (n = 14) and (iii) medical procedure (n = 47). Since the beginning of the pandemic, telehealth has been presented in diverse cases. However, it still warrants further attention. Regardless of category, the articles focused on the challenges which hinder the maximisation of telehealth in such times and how to address them. With the rapid increase in the utilization of telehealth in different specialised hospitals and clinics, a potential framework which reflects the authors' implications of the future application and opportunities of telehealth has been established. This article improves our understanding and reveals the full potential of telehealth during these difficult times and beyond.
    Matched MeSH terms: Telemedicine*
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