AI and Digital Health Equity: A Post-Pandemic Evidence Synthesis Framework

A narrative evidence synthesis of 29 sources on AI-enabled digital health equity published between 2020 and 2025. The review, authored by Albert Nii Noi Okwei and uploaded to figshare, was conducted via structured searches of PubMed, Scopus, Web of Science, and IEEE Xplore, refreshed on March 5, 2026. It examines equity mechanisms across telehealth, predictive analytics, clinical decision support, and generative AI.

Use Cases

• Informing equitable procurement policies based on the synthesis of digital access barriers and governance concerns.
• Designing subgroup validation studies for AI models based on evidence of conditional benefits and underperformance.
• Developing post-deployment monitoring roadmaps based on the implementation oversight framework distilled from the review.
• Prioritizing research on generative AI equity based on the identified gaps in evidence for sustained downstream gains.

Strengths

• The synthesis is based on a defined corpus of 29 peer-reviewed sources and governance documents.
• Search methodology is transparent, with searches refreshed on a specific date (March 5, 2026) and a second reviewer achieving 100% agreement on a sample.
• The review covers a defined time period from January 1, 2020, to December 31, 2025.

Limitations

• The dataset is a 27.6 KB document, indicating a limited scope focused on a synthesis framework rather than primary data.
• Column-level documentation is absent; the document's structure and any potential tabular data must be inferred after download.
• The evidence base is noted to vary substantially in depth across different AI modalities, such as generative AI.

Provenance

Source

figshare, author Albert Nii Noi Okwei

Collection Method

Transparent narrative evidence synthesis from peer-reviewed literature and selected governance documents.

Time Range

Literature published between January 1, 2020 and December 31, 2025.

Freshness

Last updated 2026-05-18 05:47:17