Policy Implementation Framework: Ensuring Equitable Use of AI and Emerging Technologies in Healthcare

Authors

  • Katy Woodard Oklahoma State University Center for Health Sciences - School of Health Care Administration
  • Binh Phung Oklahoma State University Center for Health Sciences School of Health Care Administration https://orcid.org/0000-0002-3041-2335

Abstract

Artificial Intelligence (AI) and emerging technologies are rapidly transforming healthcare, offering breakthroughs previously unattainable in clinical practice. The potential of AI in healthcare includes improving clinical decision-making through predictive analytics, enhancing patient outcomes via personalized treatment plans, and streamlining administrative processes. These advancements can help address systemic issues such as limited access to specialists, inefficiencies in care delivery, and workforce limitations. For example, AI-driven diagnostics are capable of early disease detection, paving the way for more effective treatments and improved patient outcomes (Topol, 2019).

However, the widespread adoption of AI in healthcare brings significant challenges that must be addressed to ensure equitable benefit across all patient populations. A primary concern is algorithmic bias, where improperly design AI systems may replicate or amplify existing disparities within healthcare. Research indicates that certain AI algorithms, particularly those predicting health outcomes, underperform for minority populations due to biased training data (Obermeyer et al., 2019). This not only diminishes trust in these technologies but also risks exacerbating health inequities by delivering suboptimal care to those in need.

Additionally, the integration of AI into healthcare raises critical privacy issues. The collection and utilization of large datasets necessary for training AI models require careful attention to the issues surrounding patient consent, confidentiality, and the potential for misuse of this sensitive data. As AI becomes increasingly embedded in patient care, concerns regarding data breaches or abuse could undermine public confidence and impede these technologies’ widespread adoption.

Another pressing challenge is the uneven access to AI-driven healthcare solutions, especially for underrepresented populations. Factors such as socioeconomic status, geographic location, and access to digital infrastructure can create disparities in who benefits from AI advancements. For instance, rural or low-income communities may have limited internet access and/or modern medical technology, posing challenges to reaping AI-driven care benefits. Thus, policies must ensure that these innovations do not marginalize vulnerable populations.

By addressing these critical issues, the proposed policy aims to foster innovation while safeguarding the interests of all patients, especially those from marginalized groups. The overarching goal is to cultivate a healthcare system where AI and emerging technologies are not only effective but also equitable, transparent, and accessible to all, ultimately contributing to improved health outcomes and the reduction of health disparities.

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Published

2025-05-14

Issue

Vol. 9 No. 1 (2025): Articles

Section

Healthcare Administration

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