AI evaluation in clinical decision support: Building a foundation of trust
September 18, 2025Artificial Intelligence (AI) is rapidly transforming healthcare, offering clinicians innovative tools to optimize workflows and enhance patient outcomes. Amid this promising revolution, ensuring these AI systems are safe, reliable, and effective is essential for their successful integration into the clinical setting. This is where rigorous evaluation frameworks, such as the one developed by Elsevier’s generative AI evaluation team, step in, establishing standards that prioritize trust, accuracy, and safety.
Drawing from insights in the ClinicalKey AI Evaluation Framework and the Clinician of the Future 2025 report, we explore how thoughtful evaluations and the adoption of AI technologies are shaping the future of clinical decision-making.
Why AI evaluation frameworks matter in healthcare
AI has become an integral part of the clinician's toolkit. According to the Clinician of the Future 2025 report, nearly half of surveyed clinicians – 48% – have already used AI tools in clinical settings, a notable increase from 26% in 2024. While this adoption signals enthusiasm from healthcare professionals, it also highlights the need for robust evaluation frameworks to ensure AI tools deliver credible and actionable insights.