Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jun 1, 2025

Abstract

OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when searching for patients with phenotypes of interest. This study aims to determine whether PheMAP, a comprehensive knowledgebase integrating multiple clinical terminologies beyond diagnosis to capture phenotypes, can effectively identify patients lacking relevant EHR diagnosis codes.

Authors

  • Chao Yan
    School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Monika E Grabowska
    Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN, USA.
  • Rut Thakkar
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
  • Alyson L Dickson
    Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
  • Peter J Embi
    Regenstrief Institute Inc, Indiana University School of Medicine, Indianapolis.
  • QiPing Feng
    Division of Clinical Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Joshua C Denny
    Vanderbilt University, Nashville, TN.
  • Vern Eric Kerchberger
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Division of Allergy, Pulmonary & Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Bradley A Malin
    Vanderbilt University, Nashville, TN.
  • Wei-Qi Wei
    Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA.

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