Abstract
Clinical Decision Support Systems (CDSS) have shown considerable potential in reducing medical errors, yet a persistent gap remains between their technical capabilities and their real-world impact on diagnostic and management errors in the high-stakes environment of Obstetrics. This paper addresses a critical question in the current state of the art: why has the promise of error reduction through CDSS not been fully realized? We argue that the primary obstacles are no longer technical but arise from a complex interplay of human and organizational factors. While sophisticated algorithms for pre-eclampsia prediction and fetal monitoring are increasingly robust, their effectiveness is often undermined by pervasive issues such as alert fatigue, poor workflow integration, automation bias, and lack of trust in the system. This review synthesizes current literature to provide a comprehensive analysis of these non-technical barriers. We then propose a human-centered design and governance framework, arguing that to transition CDSS from a technically sound tool to a reliable, error-eliminating partner in Obstetrics, the focus must shift from algorithm development to a deep understanding of the socio-technical context in which these systems are deployed.
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