Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality?

JAMA. 1992 Apr;267(16):2197-203. doi: 10.1001/jama.267.16.2197.


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.

Design: 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.

Setting: Nonfederal acute-care hospitals in California.

Study population: 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).

Main outcome measures: 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.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Aged
  • Bias
  • California / epidemiology
  • Cerebrovascular Disorders / mortality
  • Comorbidity
  • Diagnosis-Related Groups / statistics & numerical data*
  • Heart Failure / mortality
  • Hospital Mortality*
  • Humans
  • Massachusetts
  • Myocardial Infarction / mortality
  • Patient Discharge / statistics & numerical data
  • Pneumonia / mortality
  • Risk Factors