Sociodemographic Factors Influencing eHealth Access in Spain: Addressing the Digital Divide - Scorecard - MDSpire

Sociodemographic Factors Influencing eHealth Access in Spain: Addressing the Digital Divide

  • By

  • Antón Lodeiro-VÁzquez

  • Bran Barral-Buceta

  • Irene Loureiro-Álvarez

  • March 1, 2026

  • 0 min

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Clinical Scorecard: Sociodemographic Factors Influencing eHealth Access in Spain: Addressing the Digital Divide

At a Glance

CategoryDetail
ConditionDigital divide impacting equitable access to eHealth services
Key MechanismsBarriers in ICT access, skills, and use influenced by sociodemographic factors such as age, gender, income, education, and health status
Target PopulationGeneral population in Spain with emphasis on vulnerable groups marginalized by digital exclusion
Care SettingPublic health services integrating digital tools including teleconsultations, electronic prescriptions, and digital health records

Key Highlights

  • eHealth encompasses digital tools aimed at improving health access, quality, and equity but faces challenges from the digital divide.
  • The digital divide is multidimensional, involving access, skills, and usage disparities shaped by sociodemographic factors like age, gender, income, and education.
  • COVID-19 accelerated healthcare digitalisation, enhancing eHealth services but also exacerbating exclusion risks for disadvantaged groups.

Guideline-Based Recommendations

Diagnosis

  • Assess patient access to and competence with digital health technologies considering sociodemographic factors.
  • Identify barriers related to digital literacy, device availability, and internet connectivity.

Management

  • Implement targeted interventions to improve digital skills and access among vulnerable populations.
  • Promote inclusive eHealth service design to accommodate diverse user needs and reduce exclusion.
  • Balance digital and traditional healthcare modalities to ensure equitable access.

Monitoring & Follow-up

  • Continuously evaluate disparities in eHealth usage across sociodemographic groups.
  • Monitor patient satisfaction and outcomes related to digital health service utilization.

Risks

  • Risk of social exclusion and marginalization due to lack of digital access or skills.
  • Potential for reduced quality and equity of care if AI and digital tools reproduce biases.
  • Information overload leading to medicalisation and patient anxiety.

Patient & Prescribing Data

Patients across all age groups in Spain, with particular attention to older adults, low-income, and low-education groups.

Digital health tools can empower patients but require addressing digital literacy and access gaps to avoid exacerbating health inequities.

Clinical Best Practices

  • Evaluate individual patient’s digital access and literacy before recommending eHealth solutions.
  • Provide education and support to enhance digital competencies among disadvantaged groups.
  • Incorporate patient feedback to tailor eHealth services for usability and inclusivity.
  • Maintain alternative non-digital healthcare options to ensure no patient is excluded.
  • Be vigilant about ethical implications and biases in AI-driven health technologies.

References

Original Source(s)

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