Can Machine Learning Algorithms use Contextual Factors to Detect Unwarranted Clinical Variation from Electronic Health Record Encounter Data during the Treatment of Children Diagnosed with Acute Viral Pharyngitis

2026-03-02 health informatics Title + abstract only

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Rationale, Aims and ObjectivesUnwarranted clinical variation (UCV) in patient care often arises from contextual factors and contributes to increased costs, unnecessary treatments, and deviations from evidence-based practice. Detecting UCV is challenging due to the complexity of care decisions. Current approaches rely on centralized data aggregation and mixed-effects regression, which estimate relative variation but cannot detect absolute variation. Moreover, machine learning (ML) methods leverag...

Can Machine Learning Algorithms use Contextual Factors to Detect Unwarranted Clinical Variation from Electronic Health Record Encounter Data during the Treatment of Children Diagnosed with Acute Viral Pharyngitis

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