Digital health technologies (DHTs) encompass a diverse range of innovations—including mobile health applications, telemedicine, digital therapeutics, remote monitoring systems, and artificial intelligence (AI) tools—that are transforming health care delivery, public health, and patient self-management across the globe.

Scope and Effectiveness

DHTs are increasingly recognized for their potential to improve remote care, patient engagement, and health outcomes, especially in low- and middle-income countries (LMICs). A systematic review focusing on pharmaceutical care in LMICs found that mHealth apps, mobile phone calls, video calls, telemonitoring, and internet-based drug information centers improved some health-related outcomes. However, the benefit was not universal across all interventions, and there were significant challenges related to patient, system, and technology factors that impact broad adoption and sustained effectiveness(Alfian, 2023).

In the realm of chronic disease management, digital health lifestyle interventions (DHLI) for prediabetes have demonstrated statistically significant weight loss as well as improvements in secondary health outcomes, especially when interventions have a longer duration and are comprehensive in scope(Holm, 2024). Similarly, DHTs for chronic diseases in home care settings—including for diabetes and cardiovascular diseases—demand specialized health technology assessment (HTA) frameworks addressing their unique risks and benefits, as standard evaluation models are often inadequate(Von Huben, 2021).

Implementation and Challenges

The evaluation and integration of DHTs pose unique methodological challenges. Traditional randomized controlled trial (RCT) frameworks are prevalent but come with issues such as recruitment limitations, confounding factors, and the short duration of studies. The fast-paced nature of digital innovation demands more agile, continuous, and iterative evaluation methods that align with the technology’s maturity and readiness for real-world deployment(Gityamwi, 2025), (Rrd, 2020). HTA processes are being adapted specifically for AI-driven DHTs to ensure rigorous safety, efficacy, and value assessments(Molt-Puigmart, 2024).

Additionally, digital adherence technologies like smart pillboxes and data-linked medication labels are being studied to support tuberculosis treatment adherence, indicating promising directions in differentiated digital care, though evidence is still emerging on their sustained efficacy(Tadesse, 2021).

Ethical issues—such as user consent, privacy, and exacerbation of health disparities due to variable digital literacy and access—remain major concerns. For instance, implementation studies highlight that while digital platforms can reach underserved groups and reduce barriers (e.g., loneliness or mental health issues among older adults), they require substantial ongoing human support and adaptation to users’ digital skills(Hernandez-Ramos, 2024), (Krisher, 2024).

Educational Interventions and Professional Training

Digital media platforms and gamified learning are increasingly used for training healthcare professionals, with evidence showing significant increases in clinical knowledge and preparedness, particularly regarding birth preparedness, complication readiness, and neonatal care(Mahmood, 2023), (Erdoan, 2022). These tools are especially effective in resource-constrained environments or when traditional training is unfeasible.

Mental Health and Behavior Change

DHTs play a significant role in mental health, using tools such as chatbots and digital cognitive behavioral therapy (dCBT) platforms. While digital interventions in mental health can reduce symptoms of anxiety, depression, and stress, engagement rates are crucial—higher engagement leads to better outcomes, and human support significantly enhances the effectiveness, especially among populations with lower digital literacy(Daley, 2020), (Hernandez-Ramos, 2024).

Health Economics and Policy

Health economic evaluation of digital nursing and health technologies is crucial for guiding implementation and reimbursement policy. The field still lacks sufficient high-quality evidence on cost-effectiveness, and there are unique methodological challenges—such as proving causality during early-stage technology rollouts—which require innovative, context-appropriate assessment strategies(Huter, 2022).

Future Perspective

The rapid emergence of novel DHTs, including AI software and digital therapeutics, calls for continual adaptation of evaluation methodologies and early horizon scanning to prepare systems for the influx of innovative tools(Ng, 2023). Furthermore, while digital health’s integration with big data and machine learning promises improvements in both monitoring and evaluation, challenges around data quality, bias, and model explainability must be systematically addressed(Mohan, 2019), (Mumtaz, 2023).

Summary Table: Applications and Challenges of Key Digital Health Technology Modalities

Would you like a deeper exploration into a specific DHT modality (e.g., AI in health, telemedicine for chronic disease, digital mental health tools), a particular health context/country, or more detail on assessment methodologies and policy implications? I can also gather further up-to-date examples or research evidence if needed.