Disease-Specific Trends of Comorbidity Coding and Implications for Risk Adjustment in Hospital Administrative Data

Health Serv Res. 2016 Jun;51(3):981-1001. doi: 10.1111/1475-6773.12398. Epub 2015 Oct 7.


Objective: To investigate changes in comorbidity coding after the introduction of diagnosis related groups (DRGs) based prospective payment and whether trends differ regarding specific comorbidities.

Data sources: Nationwide administrative data (DRG statistics) from German acute care hospitals from 2005 to 2012.

Study design: Observational study to analyze trends in comorbidity coding in patients hospitalized for common primary diseases and the effects on comorbidity-related risk of in-hospital death.

Extraction methods: Comorbidity coding was operationalized by Elixhauser diagnosis groups. The analyses focused on adult patients hospitalized for the primary diseases of heart failure, stroke, and pneumonia, as well as hip fracture.

Principal findings: When focusing the total frequency of diagnosis groups per record, an increase in depth of coding was observed. Between-hospital variations in depth of coding were present throughout the observation period. Specific comorbidity increases were observed in 15 of the 31 diagnosis groups, and decreases in comorbidity were observed for 11 groups. In patients hospitalized for heart failure, shifts of comorbidity-related risk of in-hospital death occurred in nine diagnosis groups, in which eight groups were directed toward the null.

Conclusions: Comorbidity-adjusted outcomes in longitudinal administrative data analyses may be biased by nonconstant risk over time, changes in completeness of coding, and between-hospital variations in coding. Accounting for such issues is important when the respective observation period coincides with changes in the reimbursement system or other conditions that are likely to alter clinical coding practice.

Keywords: Elixhauser diagnosis groups; Risk adjustment; administrative data; coding practice; comorbidity.

Publication types

  • Observational Study

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Clinical Coding / trends*
  • Comorbidity*
  • Diagnosis-Related Groups / trends*
  • Female
  • Germany
  • Heart Failure / complications
  • Heart Failure / mortality
  • Hip Fractures / complications
  • Hip Fractures / mortality
  • Hospital Mortality / trends*
  • Hospitals / trends*
  • Humans
  • Length of Stay
  • Male
  • Middle Aged
  • Pneumonia / complications
  • Pneumonia / mortality
  • Prospective Payment System / trends
  • Risk Adjustment / trends*
  • Sex Factors
  • Stroke / complications
  • Stroke / mortality