Digital Health Literacy: Underpinning the NHS's Shift to Digital and Equitable Care

In 2025, the phrase digital-first healthcare is everywhere. Digital tools are reshaping what it means to access and deliver care.

For patients, technologies such as Telehealth, makes it possible for patients to connect with clinicians from their own homes, reducing barriers to access. Giving people access to their medical records, test results, and appointment booking systems is helping patients to become active participants rather than passive recipients of care. Remote monitoring are turning wearable devices into health companions that educate and empower patients to take more control over their care, their health and their wellbeing.

For providers, technologies such as AI-driven diagnostics and decision-support tools are increasing diagnostic accuracy, reducing administrative workload, and supporting faster clinical decisions. This means clinicians have more time with patients and less time spent on paperwork; for patients, it means safer, more efficient services and earlier detection of risk factors that can change their health trajectories.

Together technologies such as these promise more efficient services, earlier interventions, and greater patient control, shifting the NHS from reactive treatment to proactive, personalised prevention.

The NHS 10-Year Health Plan, Fit for the Future, acknowledges the vital role that technology plays in the future NHS, and the shift from analogue to digital, as one of three radical shifts: (NHS England, 2024). The plan also sets out the NHS aim to make the NHS the world's most AI-enabled health system, integrating technology into clinical pathways and diagnostics, using digital infrastructure, and leveraging patient-controlled data. AI is positioned alongside genomics, robotics, wearables, and data as driving the shift to a more digitally enabled health service and a transition from reactive treatment to one that prioritises proactive prevention.

However, technology alone cannot deliver this future vision. Success depends on people's ability to understand and navigate digital health technologies. For AI and digital health more broadly to become trusted, equitable, and effective and ultimately adopted, both clinicians and patients must be literate: in other words, to be able to understand, question, and confidently use the tools that will be increasingly shaping their care.

And yet so many are not.

Health systems often talk about "digital readiness," but literacy is more complex then that and this requires unpacking. There are four types of literacy that shape the the use of digital health tools:

Health literacy is the ability to access, understand, and apply health information. It is foundational to self-management, decision-making, and navigating care.

Digital literacy is the ability to use devices, navigate online platforms, and evaluate digital content critically.

Digital health literacy (DHL) fuses these skills. It describes the capacity to search for, evaluate, and use digital health information and services.

AI health literacy (AIHL) is the new frontier. It involves understanding how AI-enabled tools work, recognising their limits, questioning their outputs, and using them responsibly. For clinicians, it means balancing AI insights with their clinical judgement. For patients, it means knowing when to trust, or doubt, an algorithm.

The evidence base on digital health literacy paints a clear picture of the scale of the problem.

Around 43% of adults in England struggle to understand written health information; this rises to 61% when numbers are involved (NHS England, 2025). People with limited ability to understand or act on health information are more likely to experience delayed diagnoses, poorer adherence to treatment, and avoidable hospital admissions.

Across Europe, the WHO's M-POHL Health Literacy Survey demonstrates that this issue is widespread across European countries, where many adults have limited digital health literacy, with disadvantaged groups such as older people, those with lower education, and socioeconomically deprived populations, hit hardest.

Research consistently reports the financial and service impact of low health literacy. Crucially, literacy levels directly influences and predicts health behaviours and is associated with worse health outcomes. The economic costs are significant too. Poor health literacy is estimated to cost the NHS billions annually through avoidable hospital admissions and inefficient use of services (NHS England, 2025).

Individuals with below-basic or basic health literacy have significantly higher healthcare use, more GP visits, more emergency department attendances and higher prescription costs than those with higher literacy. All of this drives additional healthcare spending each year due to preventable complications and inefficient use of services, placing a strain on both patient outcomes and system capacity.

The digital shift magnifies this risk as a person now needs digital skills to use digital health technologies in addition to health literacy. The drive to digital therefore risks creating a two-tier system: where those confident and literate enough benefit, and those who are not, do not benefit.

To fully understand the role that digital health literacy plays within digital health technology and services adoption, let's consider the perspectives of patients, providers, and the system:

For patients, digital health literacy is an indicator of whether a person can access digital health technologies and services such as making use of telehealth, interpreting test results online, or confidently using a symptom checker. Without it, digital-first services present a barrier rather than an enabler.

For clinicians, digital health literacy and AI health literacy are becoming core competencies. Providers need to prescribe digital health apps, conduct clinically effective online consultations, and interpret AI-generated insights without undermining patient trust. France and Germany are already reimbursing health app prescriptions, requiring clinicians to understand and be able to recommend and guide safe use.

For the wider health system, assuming universal digital uptake as it transitions services digitally, is a risky and dangerous strategy. Studies show that many low-income, rural, older, and minority groups face a multitude of barriers in addition to literacy and skills gaps, such as access to devices and connectivity. Without literacy-focused design, digital transformation risks reinforcing exclusion.

We are at the dawn of an explosion of AI-driven care models, with use of and chatbots to predictive analytics, AI is entering everyday care. The NHS's 10-Year Plan positions AI at the centre of its future, with ambitions to become the "most AI-enabled care system in the world".

Trust is a fundamental part of successful and safe adoption.

Healthcare operates on relationships of vulnerability and accountability which are underpinned by trust. Patients share their most personal information, accept interventions that carry risk, and often cannot independently verify the accuracy of clinical advice. If trust is eroded, the entire system struggles: people may delay seeking help, disengage from services, or withhold critical information.

When it comes to scaling AI in healthcare, trust becomes even more essential. These tools often work in ways that are opaque to both patients and clinicians. If patients do not trust that AI is safe, unbiased, and used ethically, they are likely to be hesitant to engage with AI-driven models of care, undermining adoption. Conversely, if clinicians trust AI uncritically, without the literacy to interrogate outputs, there is a danger of automation bias, misdiagnosis, and ultimately harm, which will serve to further erode trust.

Evidence shows that within the healthcare workforce, gaps in low AIHL have been identified, with the weakest scores in technical understanding and critical appraisal. Public attitudes towards AI in healthcare are also marked by scepticism, driven by concerns about bias, lack of transparency, and the risk of misuse. A recent US survey found widespread hesitation to trust health-related AI, particularly among those who have experienced historical care discrimination.

In essence, trust acts as the bridge between technological potential and adoption and impact.

What can we do now to close the gap?

For patients and communities, culturally adapted, community-based interventions are the most effective in improving digital health literacy, tailoring programmes to local contexts, using trusted intermediaries to support adoption, and embedding support into existing community infrastructure. Schools also have a critical role to play; embedding digital and health literacy into education ensures the next generation enters adulthood prepared to navigate increasingly digital care environments. At the same time, hybrid models must remain available for those unable, or unwilling, to engage digitally. NHS England has already highlighted the role of libraries as trusted, inclusive spaces for building digital skills and tackling exclusion. Scaling these initiatives nationally could prevent those at risk of being left behind.

For clinicians and the healthcare workforce, digital and AI health literacy need to be viewed as core professional competencies. Structured education should be embedded in undergraduate curricula, continuing professional development, and leadership programmes. This includes training in digital consultation skills, critical appraisal of AI outputs, safe prescribing of digital apps, and ethical use of patient data. Crucially, clinicians must be engaged as co-designers of digital solutions, ensuring tools are usable, trustworthy, and aligned with frontline realities. Without clinician buy-in, digital adoption will struggle.

For systems and policymakers, literacy must be embedded into strategy, regulation, and evaluation. National digital health strategies should explicitly include digital and AI literacy aligning with international frameworks such as the WHO European Regional Digital Health Action Plan. Measurement of progress is vital: validated tools like the eHealth Literacy Questionnaire (eHLQ) should be routinely deployed to assess progress and identify gaps. Procurement and commissioning frameworks should require usability, accessibility, and literacy standards, making an assessment of literacy impact as important as its technical performance. Finally, governance frameworks should mandate transparency in AI use, bias auditing, and clear patient communication to safeguard trust.

For the NHS to be digital-first, it must also be literacy-first. That means equipping patients and providers alike with the skills, confidence, and critical awareness to thrive in a digital and AI-enabled future. Digital health literacy is not simply a technical skill, it is a super social determinant of health. Like income, education, and housing, it shapes people's ability to access, understand, and benefit from healthcare.

The future of healthcare is digital, but equity depends on literacy. Without it, the NHS risks building a digital system that works only for the already-advantaged. With it, we can ensure that digital transformation is truly transformative, for everyone and supports the transion to a more resilient, efficient, and inclusive health system.

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