CAESAR_ConditionSeverity_Public_wSNOMED.xlsx (564.29 kB)

CAESAR_ConditionSeverity_Public_wSNOMED.xlsx

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posted on 07.06.2017, 20:39 by Mary Regina Boland
We present a method for classifying severity at the phenotype-level that uses the Systemized Nomenclature of Medicine – Clinical Terms. Our method is called the Classification Approach for Extracting Severity Automatically from Electronic Health Records (CAESAR). CAESAR combines multiple severity measures – number of comorbidities, medications, procedures, cost and treatment time, and a proportional index term. Using a random forest algorithm and these severity measures as input, CAESAR differentiates between severe and mild phenotypes (sensitivity = 91.67, specificity = 77.78) when compared to a manually evaluated gold standard (k=0.716). CAESAR enables researchers to measure phenotype severity from EHRs to identify phenotypes that are important for comparative effectiveness research.

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