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Unlocking Opportunity: Digital Health Access

by | Sep 2, 2025 | Health Technologies

This article continues Talencio’s 2025 spotlight on Health Tech Trends, diving into the 9th of 10 emerging topics: “Digital Health Access.” The need for access to digital health and equity is urgent, particularly as AI, remote monitoring, and telehealth transform medical practice. According to a recent study published in BMJ Journals, “In the USA alone, the yearly excess healthcare costs due to racial health disparities are estimated at US$93 billion and closing the global women’s health gap promises a US$1 trillion opportunity.”1

The American Medical Association (AMA) insists that affordable, accessible technology that mitigates disparities is the only viable future for digital health. Their 2025 guidance frames equity not as an add-on, but as an essential principle in everything from AI-enabled diagnostics to algorithm-driven clinical decision support.2

Leaders in medical devices, biopharma, digital health, and diagnostics must ensure these innovations deliver on their promise—for everyone.

Trends: Transforming Health Access & Equity

Artificial Intelligence and Machine Learning: AI in 2025 is automating everything from risk prediction to radiological analysis. Machine learning models, such as those powering diagnostic chatbots or imaging analysis platforms, promise faster and more personalized care. When applied equitably and tested for bias, they enhance chronic disease management, increase efficiency, and free up providers to focus on patient relationships.2,3

Wearables and Remote Monitoring: Consumer devices (e.g., smartwatches), as well as FDA-approved medical-grade sensors, are helping patients manage diabetes, hypertension, and heart disease from home. Algorithms now detect arrhythmias, predict asthma exacerbations, and nudge patients toward physical activity.4,6

Telehealth Expansion: Especially crucial for rural Americans and urban underserved groups, remote visits for cardiology, neurology, and behavioral health reduce travel costs and bridge access gaps.5,9

Challenges: The Persisting Gaps

Socioeconomic and Digital Divide: Research has demonstrated that less-privileged populations, such as individuals with lower levels of education, lower income, older age, non-white populations, or those from rural geographies, are less likely to start or continue using digital tools – despite uptake and usage being considered prerequisites for effectiveness.6, 7,11

Bias in AI Algorithms: A major challenge in implementing digital health technologies is the risk of bias in AI algorithms, which can stem from the use of non-representative historical data and design choices during algorithm development. These biases may perpetuate existing health disparities and lead to unfavorable outcomes for underrepresented or priority populations. Additionally, as digital healthcare expands, it can exacerbate the digital divide by disadvantaging individuals with limited access to technology, low digital health literacy, or inadequate socioeconomic resources, making it crucial to prioritize equity in all aspects of digital health technology development.1,8

Rural Health Infrastructure: Many rural hospitals lack high-speed connections or funding for specialty telemedicine hubs. The result: Rural patients may not fully benefit from stroke teleconsults or remote chronic care.5

Cognitive and Workflow Burden: A surge in digital data risks overwhelming clinicians, especially if systems aren’t deeply integrated with electronic health records or provider workflow.2

Opportunities: Getting Access & Equity Right

  1. Responsible, Inclusive AI Case Studies
    • AI for Predictive Risk in Diverse Populations: At Carna Health, machine learning models are stratifying patients not just by clinical data, but by community-level “social determinants”—housing, food security, and more. This allows clinics to proactively target interventions where they matter most, an approach recommended by the Brookings AI Equity Lab.9
    • Transparency and Governance: The Brookings Lab convenes working groups to review AI models for bias and recommend cross-sector policies for fair development and deployment. Health systems like Mass General Brigham deploy generative AI only after assessing equity impacts and include frontline clinicians in vetting those tools.9
    • Algorithmic Fairness and Training: Clinics are combining training sessions for staff and algorithm governance frameworks mandated by regulatory agencies. This helps ensure both clinicians and patients are aware of (and can question) AI-generated recommendations, building trust and broadening adoption.6
  1. Wearables Advancing Health Access
    • Cost and Usability Initiatives: Global sales of wearable devices are booming. The market is projected to grow from USD 103.04 billion in 2025 to USD 324.73 billion by 2032, a CAGR of 17.8%. Yet their penetration remains lowest in low-income, elderly, and rural groups. Policy recommendations now include financial subsidies or integration of wearables into public health coverage, making sensors more affordable to marginalized populations.4,6,11,12
    • Digital Literacy Programs: Public health organizations are funding hands-on workshops to upskill patients and clinicians, ensuring they can interpret and act on data from wearables.4,6
    • Chronic Disease Monitoring: In Philadelphia, remote monitoring programs for hypertension—relying on subsidized, internet-connected blood pressure cuffs and digital coaching—saw blood pressure control rates improve by over 20% among Medicaid patients in pilot studies (2025 AMA report).2
  1. Telehealth and Rural Health Disparities
    • Specialist Access for Rural America: Teleconsults for telestroke or teleneurology will enable patients in Alaska or Appalachia to be seen by top physicians within the “golden hour”—critical in stroke care.5
    • Cost-Effectiveness: Telehealth not only improves care quality for rural patients but leads to long-term cost savings by reducing patient travel, preventing unnecessary transfers to urban hospitals, and alleviating the burden of specialist shortages in rural areas.5
    • Policy and Infrastructure: Expanded broadband funding and new telehealth reimbursement policies—such as ongoing Medicare coverage for remote consults—are key to making these gains sustainable.5
  1. Data Integration and Holistic Health Insights
    • Expanding Data Sources: Advanced platforms now combine EHR clinical notes, wearables, public health, and even consumer data (e.g., city housing statistics) to surface social barriers—flagging risks that siloed medical records commonly miss.10
    • AI-Driven Translation and Access: Generative AI is increasingly used for real-time translation, bridging care gaps for non-English speakers or those with lower health literacy, making digital health solutions more inclusive.2

Actionable Recommendations for Health Technology Leaders

Prioritize Equity in Product Design: Build tools with underserved patients and providers in mind. Test algorithms and devices with real-world settings, engaging a diverse mix of end-users.2,9

Push for Policy, Incentives, and Interoperability: Work with industry bodies and policymakers to expand reimbursement, fund infrastructure, and mandate interoperability—with equity metrics baked in.2,11

Fund and Pilot Digital Literacy and Subsidy Programs: Support local and system-wide training and subsidized device programs for patients most at risk of being left behind.4,6

Champion Ongoing Evaluation and Transparency: Regularly assess algorithms, wearables, and telehealth solutions for equitable impact. Publish the results—successes and failures alike—so the field continues to evolve, building trust and knowledge.3

Conclusion

The digital health revolution of 2025 is an access and equity test: Without concentrated industry, clinical, and policy effort, new tools risk perpetuating—rather than erasing—health disparities. However, when responsibly designed and deployed, technologies like AI, wearables, and telehealth offer a profound ability to close gaps, including in the most challenging-to-reach populations. Executives in health technology play a pivotal role by advocating for policy, investing in inclusive design and training, and embracing ongoing transparency and evaluation. Now more than ever, it is imperative for innovation to fulfill its promise for all.

Sources:

  1. PubMed Central – Advancing health equity and the role of digital health technologies: a scoping review
  2. AMA – Health care technology trends 2025: AI benefits, wearable use cases and telehealth expansion
  3. Harvard Medical School – AI Implications for Health Equity: Shaping the Future of Health Care Quality and Safety
  4. JAMA Health Forum – Pursuing Equity With Artificial Intelligence in Health Care
  5. NRHA – Telehealth’s impact on rural hospitals: A literature review
  6. PubMed Central – Adoption barriers and facilitators of wearable health devices with AI integration
  7. Frontiers – Technology access, use, socioeconomic status, and healthcare disparities among African Americans in the US
  8. Science Direct – Bridging the digital divide: artificial intelligence as a catalyst for health equity in primary care settings
  9. Brookings – Health and AI: Advancing responsible and ethical AI for all communities
  10. Fierce Healthcare – 2025 Outlook: What’s driving health equity work amid Trump 2.0 uncertainty?
  11. PubMed Central – Bridging the digital health divide: a narrative review of the causes, implications, and solutions for digital health inequalities
  12. Fortune Business Insights – Wearable Medical Devices Market

 

About the Author

Paula Norbom Paula Norbom is the Founder and CEO of Talencio, an executive search and staffing firm serving health technology companies. She has worked in the health technology industry for over 30 years.

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