Systematic Exploration of Hospital Cost Variability: A Conformal Prediction-Based Outlier Detection Method for Electronic Health Records.

Journal: AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Published Date: Jun 10, 2025

Abstract

Marked variability in inpatient hospitalization costs poses significant challenges to healthcare quality, resource allocation, and patient outcomes. Traditional methods like Diagnosis-Related Groups (DRGs) aid in cost management but lack practical solutions for enhancing hospital care value. We introduce a novel methodology for outlier detection in Electronic Health Records (EHRs) using Conformal Prediction. This approach identifies and prioritizes areas for optimizing high-value care processes. Unlike conventional predictive models that neglect uncertainty, our method employs Conformal Quantile Regression (CQR) to generate robust prediction intervals, offering a comprehensive view of cost variability. By integrating Conformal Prediction with machine learning models, healthcare professionals can more accurately pinpoint opportunities for quality and efficiency improvements. Our framework systematically evaluates unexplained hospital cost variations and generates interpretable hypotheses for refining clinical practices associated with atypical costs. This data-driven approach offers a systematic method to generate clinically sound hypotheses that may inform processes to enhance care quality and optimize resource utilization.

Authors

  • François Grolleau
    Centre of Research in Epidemiology and Statistics (CRESS), Université de Paris, French Institute of Health and Medical Research (INSERM), National Institute of Agricultural Research (INRA), Paris, France.
  • Ethan Goh
    Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
  • Stephen P Ma
    Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, United States.
  • Jonathan Masterson
    Stanford Health Care, Menlo Park, CA.
  • Ted Ross
    Stanford Health Care, Menlo Park, CA.
  • Arnold Milstein
    Stanford Clinical Excellence Research Center, Stanford University, Stanford, CA, USA.
  • Jonathan H Chen
    Stanford Center for Biomedical Informatics Research, Stanford, CA.

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