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Individual clinical Knowledge Artifacts (KA) are designed to be used inClinical Decision Support (CDS) systems at the point of care for delivery ofsafe, evidence-based care in modern healthcare systems. For formal authoring ofa KA, syntax verification and validation is guaranteed by the grammar. However,there are no methods for semantic verification. Any semantic fallacy may leadto rejection of the outcomes by care providers. As a first step toward solvingthis problem, we present a framework for translating the logical segments ofKAs into Satisfiability Modulo Theory (SMT) models. We present theeffectiveness and efficiency of our work by automatically translating the logicfragment of publicly available KAs and verifying them using Z3 SMT solver.

Model Checking Clinical Decision Support Systems Using SMT