title: Correlating electronic health record concepts with healthcare process events.
abstract: OBJECTIVE
  To study the relation between electronic health record (EHR) variables and healthcare process events.
  
  
  METHODS
  Lagged linear correlation was calculated between five healthcare process events and 84 EHR variables (24 clinical laboratory values and 60 clinical concepts extracted from clinical notes) in a 24-year database. The EHR variables were clustered for each healthcare process event and interpreted.
  
  
  RESULTS
  Laboratory tests tended to cluster together and note concepts tended to cluster together. Within each of those two classes, the variables clustered into clinically sensible groupings. The exact groupings varied from healthcare process event to event, with the largest differences occurring between inpatient events and outpatient events.
  
  
  CONCLUSIONS
  Unlike previously reported pairwise associations between variables, which highlighted correlations across the laboratory-clinical note divide, incorporating healthcare process events appeared to be sensitive to the manner in which the variables were collected.
  
  
  CONCLUSIONS
  We believe that it may be possible to exploit this sensitivity to help knowledge engineers select variables and correct for biases.
authors: Biomedical Informatics, Columbia University, New York, New York, USA.
authors: George
authors: G
authors: Hripcsak
authors: David J
authors: DJ
authors: Albers
mesh_terms: D019411:Clinical Laboratory Techniques; D003627:Data Interpretation, Statistical; D057225:Data Mining; D016208:Databases, Factual; D003695:Delivery of Health Care / Q000706:statistics & numerical data*; D057286:Electronic Health Records / Q000458:organization & administration; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D055641:Mathematical Concepts; D010641:Phenotype
keywords: Data Mining; Electronic Health Record; Phenotype
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