Health AI for Safety-Net Providers: Risks, Barriers and Opportunities

BACKGROUND

Health AI promises the delivery of care that is more predictive, preventative, and personalized. But a key question remains: To what extent can we design health AI in ways that cut across the patient and provider spectrum to ensure that the promise of AI is accessible to broader segments of the population?

To date, little research or experimentation in Health AI has focused on safety-net providers. We believe this is a missed opportunity and serves to perpetuate one of the core concerns about AI: the degree to which its design excludes participation from diverse populations and perspectives. Safety-net providers face a unique set of circumstances in the patients they serve. Many of these circumstances intersect with non-medical drivers, or social determinants, of health. This includes, for example, transportation challenges, resource-constrained neighborhoods, and poor access to health services.

PROJECT DESCRIPTION AND OBJECTIVES

With funding from the Episcopal Health Foundation, researchers are seeking to understand how safety-net providers in rural areas perceive, and use, health AI in their delivery of health care.  Researchers will address three core questions:

• What are the risks, barriers and opportunities associated with developing health AI for underserved populations?
• What are the barriers and opportunities related to building a more diverse AI workforce among safety-net providers?
• How can the perspectives and expertise of safety-net providers inform the design and deployment of Health AI in ways that transform their capacity to deliver impactful care to underserved populations?

RESEARCH METHODS

In addition to a literature review and substantial interviews with thought leaders, researchers will be launching a survey of clinicians and health care administrators in across Texas. The survey will be used to evaluate participants’ understanding of AI and machine learning (ML) and to examine participants’ perceptions of the relevance, or usefulness, of AI to their work. A key element of the survey will be 4-6 vignettes, which will place the survey participant in a “real-world” scenario in which AI could be deployed to assist with tasks such as data collection, patient diagnosis, intervention, and communication.