Perspectives on Healthcare AI Policy from 22 Health Equity Professionals

A qualitative interview study presents perspectives from 22 professionals working on health disparities and equity across the United States. The study explores how health AI policy could be developed to address biases and advance health equity. The findings highlight three key themes related to data, multi-institutional strategies, and economic considerations.

Use Cases

• Analyzing thematic insights on AI policy development based on interview transcripts.
• Studying interdisciplinary collaboration strategies for health equity based on participant recommendations.
• Identifying structural issues in healthcare data that contribute to bias based on professional perspectives.

Strengths

• Includes perspectives from 22 health equity professionals, providing a focused expert sample.
• Thematic analysis identified three concrete policy development themes: data, institutions, and economics.
• Interview guide was developed using a recognized framework (Michener's Racial Equity Framework).

Limitations

• Dataset is a single 121.3 KB PDF document, limiting computational analysis of raw interview data.
• Row count and column-level documentation are unknown, requiring manual inspection of the PDF.
• The data consists of summarized findings rather than raw, anonymized interview transcripts.

Provenance

Source

figshare, author Kadija Ferryman.

Collection Method

Semi-structured qualitative interviews.

Freshness

Last updated 2026-05-07 05:30:52.

Geography

United States.