Comorbidity measurement in elderly female breast cancer patients with administrative and medical records data

Craig J. Newschaffer, Trudy L. Bush, Lynne T. Penberthy

Research output: Contribution to journalArticlepeer-review

124 Scopus citations


The inter-rater reliability, cross-source (Medicare claims versus medical record) agreement, and ability to predict all-cause mortality of three aggregate comorbidity indices were evaluated in a group of 404 elderly, incident breast cancer casts identified from the Virginia Cancer Registry and linked to Medicare administrative data files. Comorbidity was based on both medical records and Medicare claims data using indices from Charlson et al, Satariano and Ragland, and Kaplan and Feinstein. Inter-rater agreement was good for all indices (kappas ≤ 0.80). Agreement between comorbidity indices measured by claims and medical records was considerably poorer (kappas between 0.30 and 0.40). However, claims-based and medical records-based comorbidity indices were similarly associated with mortality. For the Charlson index, the index best predicting survival, the adjusted relative risk for an increase from a lower to higher comorbidity category was 1.48 (95% confidence interval 1.23, 1.78) based on medical records compared to 1.53 (95% confidence interval 1.23, 1.93) based on Medicare claims. The claims-based Charlson index score still appeared to be associated with survival (relative risk = 1.30; 95% confidence interval = 1.00, 1.70) after controlling for the medical records-based score. This suggests that both comorbidity data sources add valuable prognostic information and, conversely, that the use of either source alone will result in some misclassification of comorbidity.

Original languageEnglish (US)
Pages (from-to)725-733
Number of pages9
JournalJournal of Clinical Epidemiology
Issue number6
StatePublished - Aug 26 1997

All Science Journal Classification (ASJC) codes

  • Epidemiology


Dive into the research topics of 'Comorbidity measurement in elderly female breast cancer patients with administrative and medical records data'. Together they form a unique fingerprint.

Cite this