Evaluating AI-Supported CDS Systems with Real-World Evidence

Evaluating AI-Supported CDS Systems with Real-World Evidence

A new analysis from the Duke-Margolis Center for Health Policy details the data elements that real-world data (RWD) sources need when evaluating the performance of artificial intelligence (AI)-supported clinical decision support (CDS) tools. RWD can provide performance measures to assess the clinical performance of these AI-supported tools and address issues related to data access, data sharing, privacy, and security. Intended use would guide the construction of the data elements and likely be located in an EHR data system, claims data, or a registry. Specific data elements that should be captured within RWD sources.

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