BACKGROUND
Though artificial intelligence (AI) has potential to augment the patient-physician relationship in primary care, bias in intelligent healthcare systems has the potential to differentially impact vulnerable patient populations.
OBJECTIVE
The purpose of this scoping review is to summarize the extent to which AI systems in primary care examine the inherent bias towards or against vulnerable populations and appraise how these systems have mitigated the impact of such biases during their development.
METHODS
We will conduct a search update from an existing scoping review to identify AI and primary care articles in the following databases: Medline-OVID,Embase,CINAHL, Cochrane Library, Web of Science, Scopus, IEEE Xplore, ACM Digital Library, MathSciNet, AAAI, and arXiv. Two screeners will independently review all abstracts, titles and full-texts. The team will extract data using structured data extraction form and synthesize the results according to PRISMA-Scr guidelines.
RESULTS
This review will provide an assessment of the current state of healthcare equity within AI for primary care. Specifically, we will identify the degree to which vulnerable patients have been included, assess how bias is interpreted and documented, and understand the extent harmful biases are addressed. As of October 2020, the scoping review is in the title and abstract screening stage. The results are expected to be submitted for publication in fall of 2021.
CONCLUSIONS
AI applications in primary care are becoming an increasingly common tool in health care delivery, including in preventative care efforts for underserved populations. This scoping review aims to understand to what extent AI-primary care studies employ a health equity lens and take steps to mitigate bias.
Health Equity in Artificial Intelligence and Primary Care Research: Protocol for a Scoping Review (Preprint)
