title: Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality?
abstract: OBJECTIVE
  Incomplete coding of secondary diagnoses may bias assessments of patient risks of poor outcomes using administrative health care databases, most of which allow only five diagnoses. The Medicare program is expanding the number of possible diagnoses from five to nine, aiming to improve coding completeness. We examined the impact of having more diagnosis codes available on assessments of risk of death.
  
  
  METHODS
  We used 1988 computerized hospital discharge abstract data from California, which allow up to 25 diagnoses per discharge, to select a sample of hospitalized patients and assessed the relationship between the presence of 29 specific secondary diagnoses and the risk of in-hospital death.
  
  
  METHODS
  Nonfederal acute-care hospitals in California.
  
  
  METHODS
  All patients at least 65 years of age who were hospitalized for stroke, pneumonia, acute myocardial infarction, or congestive heart failure in California in 1988 (N = 162,790).
  
  
  METHODS
  Relative risk of death for each specific secondary diagnosis.
  
  
  RESULTS
  Many conditions that on a clinical basis would be expected to increase the risk of death, such as adult-onset diabetes mellitus, previous myocardial infarction, angina, and ventricular premature beats, were associated with a lower risk of in-hospital death.
  
  
  CONCLUSIONS
  Bias against coding of chronic or comorbid conditions on the computerized discharge abstracts of patients who die best explains these results. Efforts to improve diagnosis coding completeness solely by increasing the number of available coding spaces may not succeed.
authors.affiliation: Department of Medicine, Harvard Medical School, Beth Israel Hospital, Boston, MA 02215.
authors.forename: L I
authors.initials: LI
authors.lastname: Iezzoni
authors.forename: S M
authors.initials: SM
authors.lastname: Foley
authors.forename: J
authors.initials: J
authors.lastname: Daley
authors.forename: J
authors.initials: J
authors.lastname: Hughes
authors.forename: E S
authors.initials: ES
authors.lastname: Fisher
authors.forename: T
authors.initials: T
authors.lastname: Heeren
mesh_terms: D000368:Aged; D015982:Bias; D002140:California / Q000453:epidemiology; D002561:Cerebrovascular Disorders / Q000401:mortality; D015897:Comorbidity; D003953:Diagnosis-Related Groups / Q000706:statistics & numerical data*; D006333:Heart Failure / Q000401:mortality; D017052:Hospital Mortality; D006801:Humans; D008404:Massachusetts; D009203:Myocardial Infarction / Q000401:mortality; D010351:Patient Discharge / Q000706:statistics & numerical data; D011014:Pneumonia / Q000401:mortality; D012307:Risk Factors