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Healthcare
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Applications of Digital Technology in Comprehensive Healthcare
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Applications of Digital Technology in Comprehensive Healthcare

A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "TeleHealth and Digital Healthcare".

Deadline for manuscript submissions: 29 September 2025 | Viewed by 3371

Special Issue Editors

Dr. Maria Haritou

E-Mail Website
Guest Editor
Biomedical Eng. Lab, Institute of Communication and Computer Systems, National Technical University of Athens, Heroon Polytechniou 9, GR-15773 Athens, Greece
Interests: e/m health; digital health systems and services; computational analysis in healthcare; clinical decision support systems; health management
Dr. Ioannis Kakkos

E-Mail Website
Guest Editor
Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9, Iroon Polytechniou Street, Zografos, 15780 Athens, Greece
Interests: transmission of nerve stimuli; study of cognitive systems and processes; medical image and signal processing; AI for diagnosis and therapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The integration of digital technology into patient care and health management is revolutionizing the healthcare landscape. In this regard, the adoption of digital technologies in healthcare holds significant promise for improving health and care services, enhancing efficiency, and reducing costs, ultimately leading to a more integrated and responsive healthcare system. This journal explores various applications of digital health tools, including telemedicine, wearable devices, electronic health records (EHRs), and mobile health apps. Telemedicine and remote consultations have expanded access to medical services, especially in underserved areas, while wearable devices provide continuous monitoring of patient vitals and activity levels, enabling proactive health management. EHRs streamline patient information and facilitating better coordination and continuity of care. Mobile health apps empower patients to manage their health through medication reminders, appointment scheduling, and health education. Additionally, artificial intelligence (AI) is being utilized for early disease detection, personalized treatment plans, and predictive analytics, enhancing diagnostic accuracy and patient outcomes. Moreover, digital therapeutics offer software-based interventions for chronic disease management and mental health support. The journal also addresses the importance of cybersecurity in protecting sensitive patient data and the role of interoperability standards in ensuring seamless data exchange between different health systems.

In this context, we are pleased to invite you submitting your work to this Special Issue, which aims to shed light on the future of healthcare, by addressing a wide range of subjects and topics in an effort to reveal how digital health advances are changing the field.

We are seeking original research papers, reviews, and case studies, spanning (but not limited to) a range of digital health fields:

  • Telemedicine and Remote Consultations: enhancing access to healthcare through virtual doctor visits, providing instant support and information to patients, and expanding access to mental health services through digital platforms.
  • Remote Patient Monitoring and Wearable Health Devices: continuous monitoring of patients with chronic conditions using connected devices including vitals and activity levels with smartwatches and fitness trackers.
  • Health Information Exchange and Electronic Health Records (EHRs): improving patient care through streamlined and accessible medical records, while enhancing coordination of care through the electronic exchange of health information.
  • AI-Enabled Healthcare: State-of-the-art uses of machine learning and artificial intelligence for disease detection, prognostication, therapy planning, diagnosis, and personalized treatment plans.
  • Digital Health Literacy: Educating patients and healthcare providers on using digital tools effectively. Improved patient empowerment, education, and engagement in healthcare decision-making are as achieve via patient-centric technologies.
  • Mobile Health Apps and Digital Therapeutics: Empowering patients with apps for medication management, appointment scheduling, and health education. Integrating software-based interventions for chronic disease management and health support.
  • Health Data Analytics, Cybersecurity, and Interoperability Standards: Protecting sensitive patient information in a digital landscape. Facilitating seamless data exchange between different health systems and devices.
  • Big Data and Population Health Management: Leveraging data to predict health trends and improve patient outcomes. Using digital tools and predictive analytics to manage and improve the health of specific populations. Improving patient engagement and self-management through online patient portals and engagement platforms.
  • Digital Therapeutics and Precision Medicine: Applying digital tools for personalized treatment. Investigating digital channels for therapy, support, and improvement of medical conditions through behavioral changes.

We look forward to receiving valuable contributions.

Dr. Maria Haritou
Dr. Ioannis Kakkos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • health management
  • telemedicine
  • remote monitoring
  • electronic health records (EHR)
  • digital therapeutics
  • mobile health apps
  • artificial intelligence in healthcare
  • predictive analytics
  • patient engagement
  • precision medicine
  • cybersecurity in healthcare
  • digital health literacy

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

23 pages, 521 KiB  
Article
The Digital Transformation of Healthcare Through Intelligent Technologies: A Path Dependence-Augmented–Unified Theory of Acceptance and Use of Technology Model for Clinical Decision Support Systems
by Șerban Andrei Marinescu, Ionica Oncioiu and Adrian-Ionuț Ghibanu
Healthcare 2025, 13(11), 1222; https://doi.org/10.3390/healthcare13111222 - 22 May 2025
Viewed by 397
Abstract
Background/Objectives: Integrating Artificial Intelligence Clinical Decision Support Systems (AI-CDSSs) into healthcare can improve diagnostic accuracy, optimize clinical workflows, and support evidence-based medical decision-making. However, the adoption of AI-CDSSs remains uneven, influenced by technological, organizational, and perceptual factors. This study, conducted between November 2024 [...] Read more.
Background/Objectives: Integrating Artificial Intelligence Clinical Decision Support Systems (AI-CDSSs) into healthcare can improve diagnostic accuracy, optimize clinical workflows, and support evidence-based medical decision-making. However, the adoption of AI-CDSSs remains uneven, influenced by technological, organizational, and perceptual factors. This study, conducted between November 2024 and February 2025, analyzes the determinants of AI-CDSS adoption among healthcare professionals through investigating the impacts of perceived benefits, technological costs, and social and institutional influence, as well as the transparency and control of algorithms, using an adapted Path Dependence-Augmented–Unified Theory of Acceptance and Use of Technology model. Methods: This research was conducted through a cross-sectional study, employing a structured questionnaire administered to a sample of 440 healthcare professionals selected using a stratified sampling methodology. Data were collected via specialized platforms and analyzed using structural equation modeling (PLS-SEM) to examine the relationships between variables and the impacts of key factors on the intention to adopt AI-CDSSs. Results: The findings highlight that the perceived benefits of AI-CDSSs are the strongest predictor of intention to adopt AI-CDSSs, while technology effort cost negatively impacts attitudes toward AI-CDSSs. Additionally, social and institutional influence fosters acceptance, whereas perceived control and transparency over AI enhance trust, reinforcing the necessity for explainable and clinician-supervised AI systems. Conclusions: This study confirms that the intention to adopt AI-CDSSs in healthcare depends on the perception of utility, technological accessibility, and system transparency. The creation of interpretable and adaptive AI architectures, along with training programs dedicated to healthcare professionals, represents measures enhancing the degree of acceptance. Full article
(This article belongs to the Special Issue Applications of Digital Technology in Comprehensive Healthcare)
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13 pages, 778 KiB  
Article
User Experiences and Attitudes Toward Sharing Wearable Activity Tracker Data with Healthcare Providers: A Cross-Sectional Study
by Kimberley Szeto, Carol Maher, Rachel G. Curtis, Ben Singh, Tara Cain, Darcy Beckett and Ty Ferguson
Healthcare 2025, 13(11), 1215; https://doi.org/10.3390/healthcare13111215 - 22 May 2025
Viewed by 458
Abstract
Background/Objectives: Wearable activity trackers (WATs) are increasingly used by individuals to monitor physical activity, sleep, and other health behaviors. Integrating WAT data into clinical care may offer a cost-effective strategy to support health behavior change. However, little is known about users’ willingness [...] Read more.
Background/Objectives: Wearable activity trackers (WATs) are increasingly used by individuals to monitor physical activity, sleep, and other health behaviors. Integrating WAT data into clinical care may offer a cost-effective strategy to support health behavior change. However, little is known about users’ willingness to share their WAT data with healthcare providers. This study aimed to explore attitudes and experiences of WAT users regarding the sharing of WAT data with healthcare providers and to examine how these vary according to user characteristics. Methods: An international online cross-sectional survey was conducted on adults who had used a WAT within the past three years. The survey assessed user demographics, usage patterns, experiences of sharing data with healthcare providers, and willingness or concerns regarding data sharing. Multivariate logistic regression was used to examine associations between user characteristics and data-sharing experiences or attitudes. Results: 447 participants completed the survey (60.0% female; 83.9% < 45 years; 60.0% from the United States). Most (94%) participants expressed willingness to share WAT data with healthcare providers, 47% had discussed it, and 43% had shared WAT data in clinical settings. Privacy was the most commonly reported concern, cited by 10% of participants. Participants with chronic health conditions were more likely to have shared or discussed WAT data, but also more likely to report concerns. Geographic differences were also observed, with Australian participants less likely to have shared or discussed their WAT data with providers, and US participants reporting fewer privacy concerns. Conclusions: The high willingness to share WAT data suggests that there is a possibility for integrating patient-owned WATs into clinical care. Addressing privacy concerns and equipping healthcare professionals with the skills to use WAT data will be essential to fully realize this opportunity. These findings highlight the need for further development of secure WAT systems, clinician training, and expanded evidence on WATs’ clinical utility. Full article
(This article belongs to the Special Issue Applications of Digital Technology in Comprehensive Healthcare)
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18 pages, 6840 KiB  
Article
Exploring New Tools in Upper Limb Rehabilitation After Stroke Using an Exoskeletal Aid: A Pilot Randomized Control Study
by Pantelis Syringas, Vassiliki Potsika, Nikolaos Tachos, Athanasios Pardalis, Christoforos Papaioannou, Alexandros Mitsis, Emilios E. Pakos, Orestis N. Zestas, Georgios Papagiannis, Athanasios Triantafyllou, Nikolaos D. Tselikas, Konstantina G. Yiannopoulou, George Papathanasiou, George Georgoudis, Daphne Bakalidou, Maria Kyriakidou, Panagiotis Gkrilias, Ioannis Kakkos, George K. Matsopoulos and Dimitrios I. Fotiadis
Healthcare 2025, 13(1), 91; https://doi.org/10.3390/healthcare13010091 - 6 Jan 2025
Cited by 2 | Viewed by 1629
Abstract
Background/Objectives: Spasticity commonly occurs in individuals after experiencing a stroke, impairing their hand function and limiting activities of daily living (ADLs). In this paper, we introduce an exoskeletal aid, combined with a set of augmented reality (AR) games consisting of the Rehabotics rehabilitation [...] Read more.
Background/Objectives: Spasticity commonly occurs in individuals after experiencing a stroke, impairing their hand function and limiting activities of daily living (ADLs). In this paper, we introduce an exoskeletal aid, combined with a set of augmented reality (AR) games consisting of the Rehabotics rehabilitation solution, designed for individuals with upper limb spasticity following stroke. Methods: Our study, involving 60 post-stroke patients (mean ± SD age: 70.97  ±  4.89 years), demonstrates significant improvements in Ashworth Scale (AS) scores and Box and Block test (BBT) scores when the Rehabotics solution is employed. Results: The intervention group showed slightly greater improvement compared to the control group in terms of the AS (−0.23, with a confidence interval of −0.53 to 0.07) and BBT (1.67, with a confidence interval of 1.18 to 2.16). Additionally, the Rehabotics solution was particularly effective for patients with more severe deficits. Patients with an AS score of 3 showed more substantial improvements, with their AS scores increasing by −1.17 ± 0.39 and BBT scores increasing by −4.83 ± 0.72. Conclusions: These findings underscore the potential of wearable hand robotics in enhancing stroke survivors’ hand rehabilitation, emphasizing the need for further investigations into its broader applications. Full article
(This article belongs to the Special Issue Applications of Digital Technology in Comprehensive Healthcare)
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