Digital transformation is reshaping health systems across the world. Electronic health records, digital health identities, telemedicine platforms, remote monitoring tools, clinical decision-support systems, data dashboards, and artificial intelligence are increasingly becoming part of healthcare delivery. These technologies hold significant promise. They can improve access, support providers, strengthen continuity of care, reduce duplication, and help health systems become more efficient and responsive.
Yet, as digital health and AI move from innovation to implementation, a central question becomes more urgent: how do we assess whether these technologies are truly improving health systems and the lives of people?
This is where Health Technology Assessment, or HTA, becomes increasingly relevant. HTA has traditionally helped decision-makers evaluate health technologies by examining their clinical effectiveness, safety, cost-effectiveness, ethical implications, organizational requirements, and broader health system value. The World Health Organization describes HTA as a systematic and multidisciplinary evaluation of the properties of health technologies and interventions, including their direct and indirect consequences.
In the age of digital transformation, HTA must become even more important. Digital health and AI are not only products or platforms. They are interventions that can change how care is delivered, how decisions are made, how providers work, how patients navigate systems, and how health systems allocate resources. Their impact goes beyond technical performance. It extends to trust, equity, safety, dignity, continuity, accountability, and health outcomes.
Too often, digital health interventions are assessed through a narrow technology lens. We ask whether a platform is modern, interoperable, scalable, secure, efficient, and cost-effective. These are necessary questions. Health systems do need technologies that are up to date, reliable, integrated, and financially sustainable. But these questions are not sufficient.
The more important question is whether digital health is being assessed against its ultimate purpose: serving people and improving health outcomes.
Are digital tools helping people receive timely diagnosis? Are they enabling better follow-up after screening or discharge? Are they reducing missed referrals? Are they improving adherence to treatment? Are they helping patients avoid complications? Are they reducing avoidable costs, travel, confusion, and delay? Are they supporting providers to make better decisions? Are they strengthening continuity of care across levels of the health system?
A digital health intervention may be technically advanced, but unless it improves the experience and outcomes of care, it cannot be considered truly transformative.
This is especially important as artificial intelligence becomes more prominent in healthcare. AI tools can support diagnosis, triage, risk prediction, workflow management, drug discovery, and personalized care. But they also raise important questions of bias, transparency, explainability, accountability, patient safety, privacy, and human autonomy. WHO has emphasized that AI for health must protect autonomy, promote human well-being and safety, ensure transparency and explainability, foster responsibility and accountability, ensure inclusiveness and equity, and remain responsive and sustainable.
These principles must be reflected in how we assess AI and digital health technologies. HTA for the digital age cannot look only at whether an AI tool works in a controlled setting. It must examine whether it works safely and fairly in real health systems, across diverse populations, and within the constraints of everyday service delivery.
Equity must be central to this assessment. Digital health can reduce gaps, but it can also widen them. If a technology assumes that every person has a smartphone, reliable internet, digital literacy, language comfort, or trust in digital systems, it may exclude those who most need support. Older persons, low-income households, rural communities, migrant workers, people with disabilities, and those with limited literacy may be left behind if digital pathways are not designed with inclusion in mind.
A people-centered HTA approach should therefore ask: who benefits, who is excluded, who bears the burden, and who may be harmed? It should examine whether digital tools are reducing inequities or deepening them. It should also consider whether assisted digital models, community-based support, multilingual interfaces, offline options, and low-tech alternatives are built into the design.
Human impact must also be assessed from the provider’s perspective. Doctors, nurses, community health workers, care coordinators, and health managers are often expected to adopt new digital systems while managing already demanding workloads. If digital tools add administrative burden, duplicate data entry, disrupt workflows, or reduce time for patient interaction, their value becomes limited. HTA must therefore examine whether a technology strengthens the health workforce or overwhelms it.
Another challenge is that digital health and AI technologies evolve quickly. Unlike many traditional health technologies, software can change through updates, new datasets, algorithm modifications, and changing patterns of use. This means assessment cannot be a one-time exercise conducted only before adoption. HTA for digital health must include continuous evaluation, real-world evidence, post-implementation monitoring, and periodic reassessment.
This is particularly important because the true value of digital health may become visible only over time. A referral tracking system, for example, should not be judged only by whether it was deployed successfully. It should be judged by whether more patients completed referrals, received timely care, avoided complications, and experienced greater confidence in the health system. A telemedicine platform should not be assessed only by the number of consultations conducted. It should also be assessed by quality of care, appropriateness of treatment, patient satisfaction, continuity, and equity of access.
HTA must therefore evolve from asking, “Does this technology work?” to asking, “Does this technology improve care, strengthen systems, and protect people?”
The future of digital health should not be driven only by innovation, market adoption, or institutional enthusiasm. It should be guided by evidence, ethics, equity, and public value. Health systems need digital technologies that are modern, interoperable, scalable, efficient, and secure. But above all, they need technologies that are purposeful.
Technology by itself does not transform health systems. Transformation happens when technology is embedded in strong governance, responsive service delivery, sustainable financing, motivated health workers, and trusted relationships with communities. HTA can help ensure that digital health and AI are not adopted merely because they are new, but because they are necessary, effective, equitable, and aligned with the needs of people.
As health systems enter a more digital and AI-enabled future, the relevance of HTA will only grow. But HTA itself must remain people-centred. It must continue to assess cost, efficiency, safety, scalability, and system readiness. But it must also place human impact at the centre: better health outcomes, improved care experiences, reduced inequities, greater trust, and stronger accountability.
The measure of digital transformation in health should not be how much technology we deploy. It should be how well that technology helps health systems care for every person, at every stage, over time.