Angela Ahrendt
To balance digital investment with limited resources, healthcare organizations must view digital transformation as a strategic commitment rather than a financial burden. As emphasized in our article, technological adoption must go hand in hand with workforce upskilling—without it, digital tools risk being underused and ultimately costly. Adoption strategies should focus on phased implementation, prioritizing high-impact technologies while simultaneously building digital competencies across the workforce. This dual investment in tools and people is essential for advancing digital maturity in the hospital and healthcare settings. Finally, as advisors, we advocate for inclusive collaboration. Engaging healthcare professionals, citizens, and digital experts alike will ensure solutions that are not only practical and user-friendly but also, in the long term, scalable and sustainable.
Georgi Chaltikyan
Academic training in digital health must transition from traditional, siloed education to a dynamic, competency-based model that reflects the realities of digital healthcare ecosystems. It should focus on developing interdisciplinary fluency, integrating clinical knowledge with data science, health informatics, AI, ethics, cyber security, and system design. Future professionals need not only (even, not so much) technical skills but leadership capabilities, critical thinking, and adaptability. Programs like the Master of Digital Health (MDH) at DIT-ECRI are designed precisely with this vision—blending theory with hands-on experience, industry engagement, and exposure to global best practices to cultivate leaders who can drive digital transformation. Furthermore, in order to streamline and harmonize master-degree digital health education, we have started a movement we call “MDH Alliance”, calling all interested parties and major players to work collaboratively towards establishing a globally recognized and accredited own degree “MDH” – in the same manner as MPH transformed public health education and training.
3. Your research touches on workforce capacity building - what are some evidence-based strategies that can simultaneously address digital skill gaps and organizational resistance to change?
Fara Aninha Fernandes
Workforce capacity building depends on several interconnected factors. Addressing both digital skill gaps and organizational resistance to change requires a combination of leadership, supportive organizational and digital infrastructure and particularly well-designed digital learning ecosystems. These digital learning ecosystems bring together micro learning, blended learning and other designs into one organized framework. This is key to building and fostering culture change, and technology adoption practices, training and leadership. For example, a study showed that ‘learn management systems’ are essential in coordinating digital health courses, delivering education on web-based environments and connecting traditional teaching with modern technology.1 Therefore it is imperative that digital learning ecosystems are introduced and utilized to support the digital transformation of healthcare. Other strategies include the assessment of skills to determine where change resistance occurs and the co-creation of digital transformation roadmaps. There should be involvement of all staff to create an atmosphere of ownership that fosters engagement, accountability and smooth adoption of new digital health practices.
Angela Ahrendt
One of the most effective strategies for building trust among healthcare professionals in adopting AI is to begin with awareness workshops grounded in clinical realities. These sessions address the significant administrative burden clinicians face daily, i.e., tasks that often divert time and energy away from direct patient care. Equally critical is investing in foundational education on data privacy, security, and AI regulation. When clinicians understand how AI tools function, how patient data is handled, and the safeguards in place, their confidence in these technologies increases. Clinicians often express concern about large-scale use of patient data due to growing cybersecurity risks. Acknowledging that IT is not their primary focus, we also engage hospital IT and security teams to strengthen the organization's cyber readiness and s cyber readiness and ensure continuous protection of sensitive data. This informed perspective helps bridge the gap between innovation and everyday practice, allowing AI to be seen as a supportive extension of clinical work, rather than a disruption to it.
Georgi Chaltikyan
Interdisciplinary collaboration is fundamental. The digital transformation of healthcare is not a technical or clinical endeavor alone – it is a cultural shift. To address this, academic curricula must be co-developed with input from health professionals, technologists, ethicists, policy-makers, and patients. At our WHO Collaborating Centre for Digital Health Education, Research and Development at DIT, we actively partner with international organizations, industry stakeholders, and public institutions to ensure that our training programs remain relevant and forward-looking. Such collaborations help us embed real-world complexity into education, ensuring graduates are equipped to navigate both technological advances and the human factors critical to their implementation.
Fara Aninha Fernandes
Scenario planning and predictive modeling are essential for designing responsive training frameworks and developing tailored training strategies to align with varying digital maturity levels in healthcare organizations. Scenario planning enables institutions to anticipate different future contexts such as incremental upgrades, integration of artificial intelligence-based tools, as well as system wide digital transformation of healthcare. In planning the integration, design, implementation, and scaling of digitally enabled interventions in healthcare settings, Cresswell and Williams outline seven principles including the planning of the integration of digital health tools with wider health and care pathways and a clear strategy for how their product will evolve over time.2 Without such scenario planning and predictive modeling, there is a risk of the introduced digital health tool being abandoned.2 The benefits of using scenario planning and predictive modeling therefore enable the workforce to be prepared for evolving technologies and workflows and allowing for strategic foresight and tactical personalization.
Angela Ahrendt
In Europe we see a growing trend of overregulation in the health sector, with fragmented and overlapping legislative requirements making compliance increasingly difficult. As holders of large amounts of health data, healthcare providers will also need to become familiar with the responsibilities under the European Health Data Space (EHDS) Regulation. On the side of the regulator, there is chronic shortage of notified bodies to certify technologies under frameworks such as the Medical Device Regulation, the AI Act, and the EHDS. These gaps are already causing deployment delays, raising concerns among clinicians about the safety and reliability of new digital tools.
Importantly, efforts to address these challenges are gaining traction. The European Commission has acknowledged these issues through simplification efforts such as the announced digital omnibus package aimed at streamlining and aligning regulatory processes. Policymaking is becoming more agile, and there is growing awareness across the healthcare ecosystem of the need to embrace new rules and support smoother national implementation for the ultimate benefit of the patient and the clinical workforce.
Georgi Chaltikyan
Such interplay is no longer optional – it is foundational to safe, efficient, and person-centered care. Clinicians equipped with digital competencies are better able to interpret data, use decision-support tools, engage with telemedicine, and safeguard patient privacy. However, digital tools must augment – not replace – clinical judgment. Our role in academia is to ensure this balance: we prepare health professionals to critically engage with technology while upholding the core principles of clinical excellence. When used responsibly, digital tools enhance diagnostics, treatment precision, and patient safety – and contribute to a more equitable, responsive health system.
Fara Aninha Fernandes
Integrating digital health tools into the real-world workflows of clinical staff is a persistent challenge in healthcare innovation. It involves an understanding of human behavior, clinical routines, institutional culture, and system complexity rather than just integrating the software into the workflows of the clinic. Digital health tools will only succeed if they align with the mundane, time-pressured, and human-centered realities of clinical work and commitment to adaptation. One of the foremost issues is the design of digital health tools that are often introduced without fully understanding the clinical reality. Another challenge is the variability in digital competencies among staff that makes uniform adoption of digital health tools difficult. Resistance to change that is often rooted in concerns about added workload, loss of autonomy, or distrust in technology also acts as a barrier.
These challenges can be overcome by co-designing digital tools with clinicians in order to ensure relevance and reduce friction. In-service programs, embedding digital health education into professional development and promoting champions can ease the transition and build confidence.
Georgi Chaltikyan
Digital health education must extend to citizens if we are to build inclusive, resilient health systems. Empowered Citizens are not passive recipients – they are co-creators of their health journeys. Education for citizens should focus on digital health literacy, data rights, navigation of digital tools (like patient portals or apps), and understanding digital risks and benefits. Community-based programs, accessible e-learning, and public awareness campaigns –developed in co-design with citizens and patients – are essential. The Chapter, where we emphasize the role of Empowered Citizens as a primary user group, reinforces this paradigm: citizens must be at the center of digital health strategies.
Fara Aninha Fernandes
The healthcare environment is stratified with varying levels of digital fluency, roles, responsibilities and learning preferences. As we explain in the chapter, there are three different user groups, each with varying knowledge, skills, and competences. Therefore, each group interacts with digital health tools differently and the consequent personalization of upskilling programs is critical in advancing digital competencies across health worker segments. Efforts must be directed towards avoiding a ‘one-size-fits-all’ training design and instead opt for advancing digital competencies among the three user groups. For example, digital health administrators require systems-level expertise in governance and informatics, while clinicians need hands-on digital skills in electronic health records, clinical decision support, and telemedicine platforms. Without personalization efforts, upskilling of the workforce can lead to disengagement, knowledge gaps, and underutilization of digital health tools, ultimately undermining the digital health transformation efforts.
Some of the methodologies of personalization include competency-based assessments to identify skill gaps, requirements of indicators to assess institutional readiness, blended and adaptive learning environments that offer role-specific education modules, and continuous in-service training. When co-developed with staff, these personalized programs enhance relevance, engagement, and effectiveness by aligning content with learners’ roles, digital literacy levels, and workflow contexts.
References:
1. Ogundiya, O., Rahman, T.J., Valnarov-Boulter, I., Young, T.M. Looking Back on Digital Medical Education Over the Last 25 Years and Looking to the Future: Narrative Review. J Med Internet Res 26:e60312. (2024). https://doi.org/10.2196/60312
2. Cresswell, K., Williams, R. Essential strategic principles for planning and developing digitally enabled interventions in health and care settings. BMC Health Serv Res 24, 1399 (2024). https://doi.org/10.1186/s12913-024-11819-x
Angela Ahrendt is Senior Director, Healthcare and Lifesciences at FTI Consulting. With over a decade of experience in the public and private sectors, Angela has built her expertise at the intersection of EU and national healthcare policies, with a particular focus on advancing innovation and the digital transformation of health systems.
Georgi Chaltikyan, MD, PhD, serves as Professor and Head of the of Digital Health (MDH) program at Deggendorf Institute of Technology (DIT-ECRI) in Germany and at Russian-Armenian University (RAU) in Armenia. He is the Founder and Head of the WHO Collaborating Center for Digital Health Education, Research, and Development at DIT-ECRI.
Fara Aninha Fernandes, BDS, MDS, MSc (Medical Informatics), is a Research Associate and PhD candidate at the Deggendorf Institute of Technology (DIT-ECRI) in Germany. Her PhD research focuses on improving the explainability of artificial intelligence-based solutions in radiology, aiming to enhance transparency, trust, and clinical integration of AI tools
