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Deploying AI changes in clinical settings requires rigorous validation. This comprehensive testing framework guides you through designing, executing, and analysing A/B tests for AI healthcare software—ensuring both statistical validity and patient safety.
This detailed checklist covers twelve critical domains from pre-test planning through post-implementation monitoring. You'll find guidance on statistical power analysis, randomisation strategies, regulatory considerations (FDA/CE classification, IRB approval), clinical safety monitoring, bias prevention, and fairness metrics. The framework addresses the unique challenges of healthcare AI, including clinical endpoint selection, algorithmic fairness across patient subgroups, workflow integration, and real-time safety monitoring with defined stopping rules.
Essential for product teams, clinical informatics leaders, data scientists, and quality assurance teams validating AI-driven clinical decision support, diagnostic tools, or treatment recommendation systems.
Download your free framework now—and if you need support designing your A/B test strategy, selecting appropriate metrics, or interpreting results for regulatory submission, book an exploratory consultation with us.
Deploying AI changes in clinical settings requires rigorous validation. This comprehensive testing framework guides you through designing, executing, and analysing A/B tests for AI healthcare software—ensuring both statistical validity and patient safety.
This detailed checklist covers twelve critical domains from pre-test planning through post-implementation monitoring. You'll find guidance on statistical power analysis, randomisation strategies, regulatory considerations (FDA/CE classification, IRB approval), clinical safety monitoring, bias prevention, and fairness metrics. The framework addresses the unique challenges of healthcare AI, including clinical endpoint selection, algorithmic fairness across patient subgroups, workflow integration, and real-time safety monitoring with defined stopping rules.
Essential for product teams, clinical informatics leaders, data scientists, and quality assurance teams validating AI-driven clinical decision support, diagnostic tools, or treatment recommendation systems.
Download your free framework now—and if you need support designing your A/B test strategy, selecting appropriate metrics, or interpreting results for regulatory submission, book an exploratory consultation with us.