A Systematic Review and Meta-analysis of Externally Validated Epic Clinical Decision Support Tools

BACKGROUND: Clinical Decision Support (CDS) tools integrated with Electronic Health Records increasingly guide clinical practice. Epic Systems, storing more than 325 million patient records, offers various proprietary predictive models to healthcare systems. Despite widespread adoption, no systematic review has examined these tools' real-world performance compared to vendor-reported metrics. METHODS: . RESULTS: ≥ 93%, p < 0.001). For ESM, EURM, and EEOL-CI, Epic's reported confidence intervals did not overlap with our pooled estimates, with Epic reporting consistently higher performance. Two additional models (ED-to-Inpatients and ICU Mortality) had one study each. CONCLUSION: Epic's CDS tools demonstrated modest real-world performance, with none exceeding AUROC 0.79. Three models (ESM, EURM, EEOL-CI) underperformed Epic's reported ranges. High heterogeneity across sites emphasizes the need for local validation before clinical deployment.