SynthesisJournal of general internal medicine2026
A Systematic Review and Meta-analysis of Externally Validated Epic Clinical Decision Support Tools.
Synthesis in Journal of general internal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
backgroundClinical 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.
methodsThis study was prospectively registered on PROSPERO (CRD420251148571). We systematically searched PubMed, Scopus, and Embase (January 2018 to August 2025) for external validations of Epic's CDS tools. We pooled Area Under the Receiver Operating Characteristic Curve (AUROC) values using random-effects models and assessed heterogeneity using Higgins' I
resultsWe included 22 studies in our systematic review, validating Epic CDS tools on a total of over 2.3 million patients and 34 sites. The Epic Deterioration Index (EDI, 7 studies, 542,983 patients) achieved pooled AUROC 0.79 [95% CI 0.76-0.80]; Epic Sepsis Model (ESM, 3 studies, 922,754 patients) 0.65 [0.61-0.70]; Epic Unplanned Readmission Model (EURM, 5 studies, 145,595 patients) 0.70 [0.68-0.73]; Epic End-of-Life Care Index (EEOL-CI, 3 studies, 217,885 patients) 0.76 [0.67-0.83]; and Epic Risk of Patient No-Show (ERPNS, 2 studies, 93,863 patients) 0.62 [0.54-0.68]. All models showed high heterogeneity (I
conclusionEpic'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.
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Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.