Elsevier has unveiled a comprehensive evaluation framework designed to mitigate risks associated with generative AI in clinical decision support tools, particularly focusing on its ClinicalKey AI platform. This initiative aims to ensure the safe, responsible, and ethical application of AI in healthcare settings. The framework incorporates rigorous assessment methodologies, including independent clinician reviews of approximately 3,000 clinical questions sourced from both in-house and open databases. These evaluations focus on the accuracy, completeness, and potential harmfulness of AI-generated responses. Additionally, the framework emphasizes real-world monitoring, allowing clinicians to report inconsistencies or inaccuracies, thereby facilitating continuous improvement.
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ClinicalKey AI, developed in collaboration with OpenEvidence and tested by over 30,000 physicians across the U.S., offers a conversational search interface that provides personalized, evidence-based clinical information. The tool draws from a vast repository of trusted medical content, including peer-reviewed journals and medical textbooks, and considers patient-specific factors such as comorbidities and current medications. By integrating this robust evaluation framework, Elsevier reinforces its commitment to responsible AI practices, ensuring that generative AI tools like ClinicalKey AI enhance clinical decision-making without compromising patient safety.