Bridging the Divide: Digital Literacy and Health Equity in the Age of Consumer Health Informatics

In the digital health revolution, access is not enough. In a world overflowing with health apps, portals, wearables, and AI-driven advice, knowing how to navigate these tools is just as crucial as having access to them. This is the foundation of consumer health informatics (CHI), a field dedicated to empowering individuals through the use of health information technology. Yet, as the systems grow smarter, the inequities grow sharper.

At the core of this challenge lies a quiet, often overlooked factor: digital literacy. In an era where online health portals are replacing paper records and chatbot triage is becoming routine, not everyone has the knowledge, confidence, or skills to keep up. And when digital health solutions fail to be inclusive, they risk widening the very disparities they aim to solve.

Let's explore how CHI, when grounded in principles of digital inclusion and equity, can become a powerful tool to bridge, rather than widen, the health divide.

Consumer Health Informatics: Where Patients Become Participants

Consumer Health Informatics is an interdisciplinary field that analyzes consumers’ needs for information, studies and implements methods to make information accessible, and designs interfaces for patients to interact with their health data [1]. CHI enables patients to participate in health decision-making through electronic health portals, remote monitoring, and mobile health (mHealth) tools.

However, this relies on one fundamental assumption: that people can and will utilize these tools effectively.

Unfortunately, that’s not always the case. Research shows that limited digital skills, combined with poor health literacy, can prevent marginalized communities from using CHI tools, leading to information gaps, fragmented care, and delayed help-seeking behaviors [2].

The Double Burden: Low Digital Literacy and Health Inequity

Digital health technologies often presume a level of literacy, language fluency, and device access that many populations, especially older adults, people with disabilities, rural residents, and low-income groups, do not possess [3].

For example, a 2021 U.S. study found that nearly 60% of adults aged 65 and over had never accessed their online health portals without assistance [4]. Similarly, many low-income patients are “smartphone-dependent,” meaning they rely on a single device with limited data, reducing their ability to access rich multimedia content or participate in telehealth visits [5].

This lack of digital literacy exacerbates existing social determinants of health, such as educational level, housing instability, and limited financial capabilities, creating a “digital divide within a health divide.”

When Informatics Meets Empathy: Designing for Equity

To address these inequities, informatics must adopt a human-centered, equity-focused design approach. This means involving underserved populations in the design and testing of tools, simplifying interfaces, and ensuring materials are culturally and linguistically appropriate.

Health informatics platforms that incorporate universal design principles, readability algorithms, voice-activated features, and multi-language support have shown increased engagement among vulnerable populations [6].

For instance, Kaiser Permanente's multilingual patient portal experienced increased use among non-English-speaking members after incorporating cultural tailoring and improving usability [7]. Similarly, community-based digital literacy programs, such as those initiated in rural India and underserved U.S. neighborhoods, have not only improved digital skills but also fostered trust in healthcare systems [8].

The Role of Digital Health Literacy Assessment Tools

To personalize interventions, many researchers have advocated for the use of Digital Health Literacy Instruments (DHLI) or eHEALS (eHealth Literacy Scale) during clinical intake. These tools assess a patient’s capacity to seek, understand, and evaluate digital health information [9].

By identifying gaps early, healthcare providers can tailor support to meet individual needs, whether through digital platforms, simplified instructions, or alternative services like telephone support, ensuring that no patient is left behind.

Policy, Practice, and the Path Forward

Addressing digital health equity requires a multi-layered approach that spans technology, education, infrastructure, and policy.

• Technology: Invest in adaptive interfaces, AI-powered personalization, and accessibility features by default.
• Education: Integrate digital literacy programs into community health initiatives and primary care settings.
• Infrastructure: Expand broadband access in underserved regions and provide device subsidies where needed.
• Policy: Implement national standards for accessible digital health and require health tech vendors to meet inclusion benchmarks.

Australia’s My Health Record system, for example, has initiated regional digital literacy workshops to improve system use in Indigenous communities, while Canada’s Digital Health Equity Framework encourages the assessment of tech-readiness as a public health priority [10].

Reframing Digital Literacy as a Social Determinant of Health

It’s time to reframe digital literacy not as a technical skill, but as a social determinant of health. Just as we recognize that clean water or housing affects health outcomes, so too should we recognize the vital role of digital access and capability in today’s health landscape.

When we equip people with the skills and confidence to navigate digital health systems, we are not only improving the user experience but also saving lives, restoring dignity, and giving communities the tools to care for themselves.

Conclusion: A More Just and Human Future in Health Informatics

As the world moves deeper into digital health, we must not let the speed of innovation outpace our compassion. Consumer Health Informatics holds incredible promise but only if it works for everyone.

Building a future of equitable digital health doesn’t start with more apps. It begins with listening. It starts with understanding. And most importantly, it starts with ensuring that the digital revolution in healthcare doesn’t leave the most vulnerable behind, but brings them forward.

References

1. Eysenbach, G. (2000). Consumer health informatics. BMJ, 320(7251), 1713–1716. https://doi.org/10.1136/bmj.320.7251.1713
2. Sarkar, U., Karter, A. J., Liu, J. Y., et al. (2010). The literacy divide: Health literacy and the use of an internet-based patient portal in an integrated health system—results from the Diabetes Study of Northern California (DISTANCE). Journal of Health Communication, 15(S2), 183–196. https://doi.org/10.1080/10810730.2010.499988
3. Nouri, S. S., et al. (2020). Addressing equity in telemedicine for chronic disease management during the Covid-19 pandemic. NEJM Catalyst. https://catalyst.nejm.org/doi/full/10.1056/CAT.20.0123
4. Anderson, M., & Perrin, A. (2017). Tech adoption climbs among older adults. Pew Research Center. https://www.pewresearch.org
5. Vogels, E. A. (2021). Digital divide persists even as Americans with lower incomes make gains in tech adoption. Pew Research Center. https://www.pewresearch.org
6. Zarcadoolas, C., et al. (2006). Advancing health literacy: A framework for understanding and action. Jossey-Bass.
7. Lyles, C. R., et al. (2017). User-centered design of a patient-facing personal health record to promote patient engagement. Applied Clinical Informatics, 8(2), 460–471. https://doi.org/10.4338/ACI-2016-10-RA-0177
8. Thomas, J. C., et al. (2018). Health literacy training programs for community health workers: A systematic scoping review. Health Promotion Practice, 19(3), 423–433. https://doi.org/10.1177/1524839917731242
9. Norman, C. D., & Skinner, H. A. (2006). eHealth literacy: Essential skills for consumer health in a networked world. Journal of Medical Internet Research, 8(2), e9. https://doi.org/10.2196/jmir.8.2.e9
10. Shaw, J., et al. (2018). Digital health and equity: A scoping review. Journal of the American Medical Informatics Association, 25(8), 1177–1188. https://doi.org/10.1093/jamia/ocy052