Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Sep 17;10(9):e27799.
doi: 10.2196/27799.

Health Equity in Artificial Intelligence and Primary Care Research: Protocol for a Scoping Review

Jonathan Xin Wang #  1   2 , Sulaiman Somani #  3 , Jonathan H Chen  4 , Sara Murray  2 , Urmimala Sarkar  1   2
Affiliations

Health Equity in Artificial Intelligence and Primary Care Research: Protocol for a Scoping Review

Jonathan Xin Wang et al. JMIR Res Protoc. .

Abstract

Background: Though artificial intelligence (AI) has the potential to augment the patient-physician relationship in primary care, bias in intelligent health care 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 toward 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 studies on AI and primary care 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-text articles. The team will extract data using a structured data extraction form and synthesize the results in accordance with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines.

Results: This review will provide an assessment of the current state of health care 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 to which 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 2021.

Conclusions: AI applications in primary care are becoming an increasingly common tool in health care delivery and in preventative care efforts for underserved populations. This scoping review would potentially show the extent to which studies on AI in primary care employ a health equity lens and take steps to mitigate bias.

International registered report identifier (irrid): PRR1-10.2196/27799.

Keywords: artificial intelligence; big data; data mining; decision support; diagnosis; electronic health records; family medicine; health disparity; health equity; health informatics; health information technology; primary care; scoping review; treatment.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: US is funded by the National Institute of Health’s National Cancer Institute, the California Healthcare Foundation, the Center for Care Innovation, the United States Food and Drug Administration, the National Library of Medicine, and the Commonwealth Fund. She is also supported by an unrestricted gift from the Doctors Company Foundation. She has received prior funding from the United States Department of Health and Human Services’ Agency for Healthcare Research and Quality, Gordon and Betty Moore Foundation, and the Blue Shield of California Foundation. She holds contract funding from AppliedVR, Inquisithealth, and Somnology. Furthermore, US serves as a scientific/expert advisor for the nonprofit organizations HealthTech 4 Medicaid and for HopeLab. She has been a clinical advisor for Omada Health and an advisory panel member for Doximity. SS is a co-founder and equity holder in Monogram Orthopedics. JHC is supported in part by the National Institutes of Health/National Library of Medicine via Award R56LM013365 and Stanford Clinical Excellence Research Center (CERC), is the co-founder of Reaction Explorer LLC, which develops and licenses organic chemistry education software, and has been paid consulting or speaker fees by the National Institute of Drug Abuse Clinical Trials Network, Tuolc Inc, Roche Inc, and Younker Hyde MacFarlane PLLC.

References

    1. Kok J. Artificial Intelligence. Paris: EOLSS Publications; 2009.
    1. Baştanlar Y, Özuysal M. miRNomics: MicroRNA Biology and Computational Analysis. Totowa, NJ: Humana Press; 2014. Introduction to Machine Learning; pp. 105–128. - PubMed
    1. Covington P, Adams J, Sargin E. Deep Neural Networks for YouTube Recommendations. RecSys '16: Tenth ACM Conference on Recommender Systems; September 15-19, 2016; Boston, MA. 2016. - DOI
    1. Carbonneau R, Laframboise K, Vahidov R. Application of machine learning techniques for supply chain demand forecasting. Eur J Oper Res. 2008 Feb;184(3):1140–1154. doi: 10.1016/j.ejor.2006.12.004. - DOI
    1. Pierson HA, Gashler MS. Deep learning in robotics: a review of recent research. Adv Robot. 2017 Aug 21;31(16):821–835. doi: 10.1080/01691864.2017.1365009. - DOI