Process Improvement Before Artificial Intelligence and Automation: Building Trust With the...

Artificial intelligence (AI) and automation are rapidly transforming health care, yet their integration into clinical workflows often falls short owing to technical, ethical, and organizational challenges. Lack of trust emerges as the central hurdle, encompassing both patient and provider confidence in AI systems. Patients raise concerns over safety, transparency, and the physician-patient relationship, whereas providers express apprehension toward algorithmic opacity, data quality and, legal ambiguity. To address these concerns, the understand, transform, and sustain (UTS) framework offers a behavior-based, systems-level approach to AI deployment. Developed by Mayo Clinic's Quality Academy, UTS integrates process improvement principles across 3 phases, emphasizing stakeholder engagement, transparency and patient safety throughout the AI lifecycle. The understand phase identifies inefficiencies by mapping workflows, collecting data, and recognizing areas for improvement, ensuring developers create tools that address appropriate priorities. In the transform phase, interventions are designed, implemented and tested through improvement cycles and feedback loops. Data to build algorithms is carefully evaluated to avoid biases, and AI output is assessed for opacity risk to maintain transparency and explainability. The sustain phase monitors outcomes and standardizes practices for long-term value. Data audits and automated extraction tools are applied for fidelity and harmonization, promoting scalability and collaboration among organizations. By keeping human intelligence central, UTS represents a catalyst for responsible innovation by aligning technological advancement with clinical priorities. Previous frameworks are more prescriptive in terms of tools and actions; UTS builds on this, targeting the underlying decision-making teams needed for sustainable process improvement, critical for successful health care transformation.