You are currently on the new version of our website. Access the old version .
HealthcareHealthcare
  • Editorial
  • Open Access

3 April 2025

The Future of Healthcare Is Digital: Unlocking the Potential of Mobile Health and E-Health Solutions

Centro Tisp, Istituto Superiore di Sanità, 00161 Roma, Italy
This article belongs to the Special Issue Healthcare Goes Digital: Mobile Health and Electronic Health Technology in the 21st Century
In the era of rapid technological advancement, healthcare is undergoing a profound transformation driven by digital solutions. The integration of artificial intelligence (AI) and conversational agents, such as ChatGPT, is reshaping the way healthcare is delivered, offering innovative opportunities to enhance patient care, streamline workflows, and improve overall efficiency.
The Special Issue “Healthcare Goes Digital: Mobile Health and Electronic Health Technology in the 21st Century” [1] aimed to explore emerging themes, examining their innovative applications, challenges, and prospects. A crucial focus is on both telemedicine [2] and mobile health applications and their impact on healthcare delivery, patient monitoring, and disease management [3]. Another area of interest is wearable health technology [4] and its role in continuously monitoring health metrics, offering new possibilities for personalized medicine. The evolution and effectiveness of telemedicine, particularly with AI-driven diagnostic tools [5] and virtual consultations [6], also form a central part of the discussion today. Furthermore, the integration of AI-driven analytics in electronic health records (EHRs) [7] is crucial for clinical decision-making and interoperability.
Security and privacy concerns in digital healthcare [8], especially regarding AI-driven applications nowadays, are key considerations that must be faced to ensure the responsible deployment of these technologies. Patient engagement through digital platforms, including AI-driven chat interfaces and virtual health assistants, is another significant topic in rapid evolution [9]. Finally, the influence of AI, the Internet of Things (IoT) [10], and other emerging technologies in healthcare is a field in need of special attention, both for its potential and implications.
As digital healthcare continues to evolve, it is crucial to critically assess the potential benefits and challenges of the integration of all this emerging technology.
Thanks to the contribution of numerous international scholars, this Special Issue has collected, in addition to this editorial, 13 studies, including 7 scientific articles [11,12,13,14,15,16,17] and 6 reviews [18,19,20,21,22,23], 5 of which are systematic reviews [19,20,21,22,23].
Contributions of the Article studies
Table 1 provides a brief summary of the foci and contributions of the articles published in this Special Issue.
Table 1. Sketch of the articles published in the Special Issue.
Some studies have explored the intersection of healthcare technology, patient care, and innovative solutions aimed at enhancing both accessibility and outcomes. One notable study by Alzghaibi [11], investigates barriers to the adoption of the Sehaty mobile health application, particularly for patients suffering from chronic diseases. It reveals challenges in technical performance, user interface design, and privacy concerns. This research provides valuable insights for improving mobile health platforms by enhancing stability, user experience, and security to ensure higher user satisfaction and engagement.
Lu et al. [12], delve into how online healthcare platforms influence patient decision-making. Specifically, their study looks at how hospital ratings and patient reviews shape the choices of patients seeking care across regions. The findings emphasize the need to optimize these systems to promote healthcare equity, thereby improving informed decision-making for underserved populations.
Shafran-Tikva et al. [13] propose a study taking a data-driven approach to preventing pressure injuries in elderly patients by analyzing electronic medical records. It identifies key factors that can help detect and prevent community-acquired pressure injuries, offering practical data that can improve clinical practices and patient safety.
In the field of patient-centered care, the work proposed by Estadella et al. [14] investigates the role of virtual reality (VR) in reducing pain and stress during medical procedures like office hysteroscopy. The study demonstrates that VR can significantly enhance patient comfort and reduce the need for invasive interventions, highlighting the potential of VR to revolutionize procedural care.
For mental health, Han et al. [15] explore the effects of virtual music therapy, based on positive psychology, on the mental health of college students during the COVID-19 pandemic. The findings underscore the effectiveness of such interventions in reducing stress, anxiety, and depression, especially during challenging times.
Artificial Intelligence (AI) also plays a crucial role in patient care, as highlighted by Gomez-Cabello et al. [16]. Their study evaluates the potential of AI models like ChatGPT-3.5 and GPT-4 in providing postoperative care advice to plastic surgery patients. It emphasizes the potential of large language models to deliver accurate and accessible care information, presenting them as valuable adjuncts in patient education.
Lastly, Lepri et al. [17] examine the shift toward home-based radiology services, particularly after the COVID-19 pandemic. The study uncovers the challenges and opportunities faced by medical radiology technicians, highlighting the need for further research and collaboration to integrate AI and improve patient care in a home setting.
Together, these studies shed light on the growing role of technology in enhancing patient care, from mobile health apps and AI integration to innovative pain management and virtual therapy solutions. The insights gained provide a foundation for the continued evolution of healthcare services, ensuring that they remain accessible, patient-centered, and efficient.
Contribution of the review studies
Table 2 focuses on the published review studies with a sketch. An overview of the reviews published in this Special Issue highlights the diverse ways in which digital interventions are transforming healthcare across various domains.
Table 2. Sketch of the review studies published in the Special Issue.
One of the most significant advancements is in telerehabilitation for chronic neck pain as highlighted by Valenza-Peña et al. [18]. Their review confirmed the efficacy of virtual consultations and remote exercise programs in reducing pain and improving functional outcomes for patients suffering from chronic neck pain. This demonstrates the growing potential of telerehabilitation to provide effective pain management and rehabilitation, particularly in remote or underserved areas.
Another key area of digital health innovation is the use of voice assistants (VAs) in managing non-communicable diseases (NCDs) as reported by Bramanti et al. [19]. The systematic review examining the role of VAs in managing illnesses like diabetes, cardiovascular diseases, and mental health conditions found that these technologies enhance patient engagement, improve self-management, and encourage behavioral changes. However, challenges such as privacy concerns and adoption barriers remain, which must be addressed to maximize their potential in healthcare settings.
In maternal and perinatal care, chatbots for women and expectant parents based on Amil et al. [20] have proven to be an invaluable resource. A systematic review of studies on the use of chatbots in supporting women throughout the reproductive cycle showed that these interactive tools significantly improved health knowledge, behaviors, and attitudes. They also facilitated better access to healthcare information and services, offering an effective way to engage expectant parents and women during preconception, pregnancy, and postpartum periods.
The use of digital psychotherapy in addressing suicide ideation and depression has also gained considerable attention as reported in Oh et al. [21]. This systematic review found that digital interventions, particularly Cognitive Behavioral Therapy (CBT), significantly reduced both suicide ideation and depression, providing a promising alternative to traditional face-to-face therapy. This approach offers greater accessibility and convenience, making it an increasingly important option for mental healthcare.
Bogár et al. [22], focused on the field of cardiac care, highlighting that smartwatches for arrhythmia detection [22] have shown to play a crucial role in the early detection and continuous monitoring of cardiac conditions such as atrial fibrillation. The systematic review highlights the potential of these wearable devices to enable timely interventions and improve patient outcomes, particularly for individuals at high risk of heart-related complications.
Lastly Protano et al. [23] demonstrated that digital technologies have also proven effective in promoting weight loss and healthy behaviors [23]. The systematic review of studies on mobile apps, wearables, and online programs for weight management demonstrated their effectiveness in encouraging healthier lifestyles, particularly by increasing physical activity and improving dietary habits. The personalized feedback provided by these digital tools has been shown to enhance weight loss efforts, offering significant benefits for individuals with obesity or overweight conditions.
Together, these reviews underline the transformative role of digital health technologies in modern healthcare. They highlight how virtual interventions, whether through telerehabilitation, voice assistants, chatbots, digital psychotherapy, or wearables, can enhance patient care, improve clinical outcomes, and provide accessible, personalized healthcare solutions across various health conditions.
Conclusions and future routes
Based on the contributions presented in this Special Issue, it is evident that healthcare technologies, including mobile health applications, virtual interventions, and digital platforms, are playing a transformative role in improving patient care, access, and overall health outcomes. The articles and reviews provide valuable insights into the challenges, opportunities, and effectiveness of these technologies across various healthcare domains, such as chronic disease management, mental health support, rehabilitation, and the monitoring of cardiovascular conditions [11,12,13,14,15,16,17].
Looking ahead, several key areas have been detected for further exploration and development. First, improving the usability, accessibility, and technical stability of mHealth platforms is crucial for ensuring their broader adoption and sustained engagement among patients, particularly those with chronic conditions [11]. In addition, focusing on the challenges related to data privacy, security, and the integration of digital tools into existing healthcare systems will be essential for maximizing their impact on patient care [12].
Future research should continue to focus on optimizing the integration of AI-powered tools, such as voice assistants, chatbots, and large language models, to enhance patient–provider communication, support self-management, and provide personalized care [19,20,21,22,23]. Moreover, the growing role of digital psychotherapy, telerehabilitation, and wearables in mental health and physical rehabilitation underscores the potential for remote healthcare interventions to complement traditional care models and offer more flexible, patient-centered solutions [18,21,22].
Lastly, as the healthcare landscape continues to evolve, it will be essential to address the ethical considerations surrounding the use of AI and digital technologies, ensuring that these tools are used responsibly and in ways that enhance health equity, patient autonomy, and trust in digital healthcare systems [19,23].
In conclusion, the ongoing advancement of digital health technologies promises to revolutionize healthcare delivery and provide more efficient, accessible, and personalized care. However, reaching the full potential of these technologies will require continued innovation, interdisciplinary collaboration, and a commitment to addressing the challenges that accompany their integration into real-world healthcare practices.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Special Issue: Healthcare Goes Digital: Mobile Health and Electronic Health Technology in the 21st Century. Available online: https://www.mdpi.com/journal/healthcare/special_issues/0P14J89UOQ (accessed on 20 March 2025).
  2. Farias, F.A.C.; Dagostini, C.M.; Bicca, Y.A.; Falavigna, V.F.; Falavigna, A. Remote Patient Monitoring: A Systematic Review. Telemed. J. E Health 2020, 26, 576–583. [Google Scholar] [CrossRef] [PubMed]
  3. Han, M.; Lee, E. Effectiveness of Mobile Health Application Use to Improve Health Behavior Changes: A Systematic Review of Randomized Controlled Trials. Healthc. Inform. Res. 2018, 24, 207–226. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  4. Lu, L.; Zhang, J.; Xie, Y.; Gao, F.; Xu, S.; Wu, X.; Ye, Z. Wearable Health Devices in Health Care: Narrative Systematic Review. JMIR Mhealth Uhealth 2020, 8, e18907. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  5. Esteva, A.; Kuprel, B.; Novoa, R.A.; Ko, J.; Swetter, S.M.; Blau, H.M.; Thrun, S. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017, 542, 115–118. [Google Scholar] [CrossRef] [PubMed]
  6. Available online: https://www.nejm.org/doi/full/10.1056/NEJMp2003539 (accessed on 19 March 2025).
  7. Rajkomar, A.; Oren, E.; Chen, K.; Dai, A.M.; Hajaj, N.; Hardt, M.; Liu, P.J.; Liu, X.; Marcus, J.; Sun, M.; et al. Scalable and accurate deep learning with electronic health records. NPJ Digit. Med. 2018, 1, 18. [Google Scholar] [CrossRef] [PubMed]
  8. Available online: https://www.ncbi.nlm.nih.gov/books/NBK233428/ (accessed on 19 March 2025).
  9. Kurniawan, M.H.; Handiyani, H.; Nuraini, T.; Hariyati, R.T.S.; Sutrisno, S. A systematic review of artificial intelligence-powered (AI-powered) chatbot intervention for managing chronic illness. Ann. Med. 2024, 56, 2302980. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  10. Al-Rawashdeh, M.; Keikhosrokiani, P.; Belaton, B.; Alawida, M.; Zwiri, A. IoT Adoption and Application for Smart Healthcare: A Systematic Review. Sensors 2022, 22, 5377. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  11. Alzghaibi, H. Barriers to the Utilization of mHealth Applications in Saudi Arabia: Insights from Patients with Chronic Diseases. Healthcare 2025, 13, 665. [Google Scholar] [CrossRef] [PubMed]
  12. Lu, Y.; Shi, L.; Wang, Z. Patient Mobility in the Digital Era: How Online Service Information from Internet Hospitals Shapes Patients’ Cross-Regional Healthcare Choices. Healthcare 2025, 13, 484. [Google Scholar] [CrossRef] [PubMed]
  13. Shafran-Tikva, S.; Gabay, G.; Kagan, I. Transformative Insights into Community-Acquired Pressure Injuries Among the Elderly: A Big Data Analysis. Healthcare 2025, 13, 153. [Google Scholar] [CrossRef] [PubMed]
  14. Estadella Tarriel, J.; Perelló Capó, J.; Simó González, M.; Bailón Queiruga, M.; Real Gatius, J.; Gomis-Pastor, M.; Marre, D.; Llurba Olivé, E. Effectiveness of Virtual Reality in Reducing Pain and Stress During Office Hysteroscopy: A Randomized Controlled Trial. Healthcare 2025, 13, 131. [Google Scholar] [CrossRef] [PubMed]
  15. Han, J.; Lee, H.; Kim, T.; Lee, S. Exploring the Impact of Positive Psychology-Based Virtual Music Therapy on Mental Health in Stressed College Students during COVID-19: A Pilot Investigation. Healthcare 2024, 12, 1467. [Google Scholar] [CrossRef] [PubMed]
  16. Gomez-Cabello, C.A.; Borna, S.; Pressman, S.M.; Haider, S.A.; Sehgal, A.; Leibovich, B.C.; Forte, A.J. Artificial Intelligence in Postoperative Care: Assessing Large Language Models for Patient Recommendations in Plastic Surgery. Healthcare 2024, 12, 1083. [Google Scholar] [CrossRef] [PubMed]
  17. Lepri, G.; Oddi, F.; Gulino, R.A.; Giansanti, D. Beyond the Clinic Walls: Examining Radiology Technicians’ Experiences in Home-Based Radiography. Healthcare 2024, 12, 732. [Google Scholar] [CrossRef] [PubMed]
  18. Valenza-Peña, G.; Calvache-Mateo, A.; Valenza, M.C.; Granados-Santiago, M.; Raya-Benítez, J.; Cabrera-Martos, I.; Díaz-Mohedo, E. Effects of Telerehabilitation on Pain and Disability in Patients with Chronic Neck Pain: A Systematic Review and Meta-Analysis. Healthcare 2024, 12, 796. [Google Scholar] [CrossRef]
  19. Bramanti, A.; Corallo, A.; Clemente, G.; Greco, L.; Garofano, M.; Giordano, M.; Pascarelli, C.; Mitrano, G.; Di Palo, M.P.; Di Spirito, F.; et al. Exploring the Role of Voice Assistants in Managing Noncommunicable Diseases: A Systematic Review on Clinical, Behavioral Outcomes, Quality of Life, and User Experiences. Healthcare 2025, 13, 517. [Google Scholar] [CrossRef] [PubMed]
  20. Amil, S.; Da, S.-M.-A.-R.; Plaisimond, J.; Roch, G.; Sasseville, M.; Bergeron, F.; Gagnon, M.-P. Interactive Conversational Agents for Perinatal Health: A Mixed Methods Systematic Review. Healthcare 2025, 13, 363. [Google Scholar] [CrossRef] [PubMed]
  21. Oh, J.; Ho, J.; Lee, S.; Park, J.-H. Effects of Digital Psychotherapy on Suicide: A Systematic Review and Meta-Analysis. Healthcare 2024, 12, 1435. [Google Scholar] [CrossRef] [PubMed]
  22. Bogár, B.; Pető, D.; Sipos, D.; Füredi, G.; Keszthelyi, A.; Betlehem, J.; Pandur, A.A. Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review. Healthcare 2024, 12, 892. [Google Scholar] [CrossRef] [PubMed]
  23. Protano, C.; De Giorgi, A.; Valeriani, F.; Mazzeo, E.; Zanni, S.; Cofone, L.; D’Ancona, G.; Hasnaoui, A.; Pindinello, I.; Sabato, M.; et al. Can Digital Technologies Be Useful for Weight Loss in Individuals with Overweight or Obesity? A Systematic Review. Healthcare 2024, 12, 670. [Google Scholar] [CrossRef] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Multiple requests from the same IP address are counted as one view.