Abstract
The integration of advanced analytics and artificial intelligence (AI) technologies into the practice of medicine holds much promise. Yet, the opportunity to leverage these tools carries with it an equal responsibility to ensure that principles of equity are incorporated into their implementation and use. Without such efforts, tools will potentially reflect the myriad of ways in which data, algorithmic, and analytic biases can be produced, with the potential to widen inequities by race, ethnicity, gender, and other sociodemographic factors implicated in disparate health outcomes. We propose a set of strategic assertions to examine before, during, and after adoption of these technologies in order to facilitate healthcare equity across all patient population groups. The purpose is to enable generalists to promote engagement with technology companies and co-create, promote, or support innovation and insights that can potentially inform decision-making and health care equity.
Highlights
P rimary care has a critical role to play in ensuring that mission-driven values aimed at eliminating health care disparities are prioritized in the development, selection, clinical implementation, and use of advanced analytics and artificial intelligence (AI) technologies
Because the application of these technologies in primary care is in its infancy, primary care professionals have a unique opportunity to guide the growth of fair, transparent, and ethical AI and analytics applications that embody health equity principles that meet the needs of diverse populations
We propose the following series of questions that should be considered before and during the adoption of an AI technology or advanced analytic strategy into practice
Summary
The ideal implementation of advanced analytics and AI technologies should democratize health care and actively address problems that are relevant to the health needs of socially marginalized populations who face structural racism and discrimination in access to care, resulting in disparate health outcomes.[15]. We note that the existing academic medical literature employing AI-based techniques has rarely focused on diversity, health equity or health care disparities (Fig. 2). When used to explicitly address health care equity, AI techniques can help identify and prevent disease progression in diverse populations. As we seek more equitable technology solutions to improve health care delivery, we must actively seek to understand and offer solutions relevant to the needs of all patients, especially patients in historically underserved or marginalized groups
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