Wang Jonathan Xin, Somani Sulaiman, Chen Jonathan H, Murray Sara, Sarkar Urmimala
Center for Vulnerable Populations at San Francisco General Hospital, University of California San Francisco, San Francisco, CA, United States.
Division of General Internal Medicine, University of California San Francisco, San Francisco, CA, United States.
JMIR Res Protoc. 2021 Sep 17;10(9):e27799. doi: 10.2196/27799.
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.
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.
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.
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.
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.
尽管人工智能（AI）有潜力增强初级保健中患者与医生的关系，但智能医疗系统中的偏见可能会对弱势患者群体产生不同程度的影响。
本范围综述的目的是总结初级保健中的人工智能系统在多大程度上审视了对弱势人群的固有偏见，并评估这些系统在开发过程中如何减轻此类偏见的影响。
我们将对现有的范围综述进行检索更新，以在以下数据库中识别关于人工智能与初级保健的研究：Medline - OVID、Embase、CINAHL、Cochrane图书馆、科学引文索引、Scopus、IEEE Xplore、ACM数字图书馆、MathSciNet、美国人工智能协会和arXiv。两名筛选人员将独立审查所有摘要、标题和全文文章。研究团队将使用结构化数据提取表提取数据，并根据PRISMA - ScR（系统评价和Meta分析扩展的范围综述的首选报告项目）指南综合结果。
本综述将对初级保健人工智能领域内的医疗公平现状进行评估。具体而言，我们将确定弱势患者被纳入的程度，评估偏见是如何被解释和记录的，并了解有害偏见得到解决的程度。截至2020年10月，范围综述处于标题和摘要筛选阶段。预计结果将于2021年秋季提交发表。
初级保健中的人工智能应用正日益成为医疗服务和为服务不足人群提供预防保健工作中的常用工具。本范围综述可能会展示初级保健中关于人工智能的研究在多大程度上采用了健康公平视角并采取措施减轻偏见。
国际注册报告识别号（IRRID）：PRR1-10.2196/27799
