The Bridge “Artificial Intelligence” Over the “Healthcare Quality” Lake

Abstract The pandemic, aging population, and legacy healthcare delivery systems have severely impacted health care, and there is a need to deliver high-quality care by leveraging real-world data-driven insights directly into patient care. Several artificial intelligence (AI)-assisted tools have been adopted to empower clinical decision-making, optimize operations, refine medical image analysis, and monitor patients using AI-powered wearables. AI systems rely on the data they are trained on. Training data that lack representativity, inclusivity, and diversity are often biased and can generate biased AI outcomes. It is important to limit algorithm bias, ensure developmental transparency, enhance data security, and facilitate equitable access for the healthcare industry to harness AI benefits when minimizing its potential challenges. Balancing innovation with caution is critical for clinicians to ensure that the AI bridge over the healthcare quality lake is crossed successfully, without harm.