ArticlemedRxiv : the preprint server for health sciences2025
Accuracy of electronic medical records to quantify rates of sedative and analgesic infusions for acute disorders of consciousness big data research.
Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background/Objective: The reliability of electronic medical records (EMR) for exposure to sedative and analgesic medications in patients with acute disorders of consciousness is unknown. Our objective was to quantify the accuracy of sedative and analgesic infusion rates derived from the EMR to support its use in big data clinical research. Methods: We conducted a prospective cohort study enrolling critically ill patients who were unresponsive to verbal commands after acute brain injury. During standardized behavioral assessments, research coordinators documented infusing sedative and analgesic medications in case report forms (CRF; reference standard). We extracted infusion rates from the EMR (index) and calculated concordance correlation coefficients for drugs with ≥ 10 EMR-CRF infusion rate pairs. Results: Among 63 included patients (median age: 61 [46-72]; 22 [35%] female), we collected 404 pairs (225 fentanyl, 86 propofol, 70 dexmedetomidine, 19 midazolam, 4 ketamine). Correlation coefficients were 0.82 (95% CI: 0.69-0.91) for propofol, 0.93 (95% CI: 0.85-0.97) for fentanyl, 0.92 (95% CI: 0.81-0.98) for dexmedetomidine and 0.94 (95% CI: 0.55-1.00) for midazolam. Conclusions: EMR derived data on sedative and analgesic infusion rates has variable but overall adequate accuracy to support big data research. External validation is required to support its routine use in clinical research.
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