Phenome based analysis as a means for discovering context dependent clinical reference ranges

AMIA Annu Symp Proc. 2012:2012:1441-9. Epub 2012 Nov 3.

Abstract

Robust electronic medical records (EMR's) have made large-scale phenome-based analysis feasible. The context-dependent phenome of a large ICU-based EMR database (MIMIC II) was explored, as a function of a clinical feature: white blood cell count (WBC). Phenome visualization led to the discovery that peak WBC in the range 15-45 K/μl was highly associated with the diagnoses of Clostridium difficile and bacterial sepsis; thus, it is conceivable that clinicians might delay ordering targeted antimicrobials towards C. difficile for patients with peak WBC in this range. This hypothesis was confirmed, with significant delays in this group (median 135 vs. 85 hours, p = 0.002). These delays could be associated with adverse effects on patient health and high hospitalization costs (e.g. an additional $3,000,000 for the MIMIC II cohort). In conclusion, context-dependent clinical reference ranges are critical to clinical decision making; furthermore, important findings can be discovered through EMR-driven phenome association studies.

MeSH terms

  • Anti-Bacterial Agents / therapeutic use
  • Clostridioides difficile*
  • Clostridium Infections / drug therapy
  • Clostridium Infections / immunology*
  • Critical Illness
  • Delayed Diagnosis
  • Electronic Health Records
  • Genomics
  • Humans
  • Intensive Care Units
  • International Classification of Diseases
  • Leukocyte Count*
  • Leukocytosis / etiology
  • Medical Records Systems, Computerized
  • Phenotype*
  • Reference Values

Substances

  • Anti-Bacterial Agents