Comparing a medical records-based and a claims-based index for measuring comorbidity in patients with lung or colon cancer.
OBJECTIVE: Ascertaining comorbid conditions in cancer patients is important for research and clinical quality measurement, and is particularly important for understanding care and outcomes for older patients and those with multi-morbidity. We compared the medical records-based ACE-27 index and the claims-based Charlson index in predicting receipt of therapy and survival for lung and colon cancer patients. MATERIALS AND METHODS: We calculated the Charlson index using administrative data and the ACE-27 score using medical records for Veterans Affairs patients diagnosed with stage I/II non-small cell lung or stage III colon cancer from January 2003 to December 2004. We compared the proportion of patients identified by each index as having any comorbidity. We used multivariable logistic regression to ascertain the predictive power of each index regarding delivery of guideline-recommended therapies and two-year survival, comparing the c-statistic and the Akaike information criterion (AIC). RESULTS: Overall, 97.2% of lung and 90.9% of colon cancer patients had any comorbidity according to the ACE-27 index, versus 59.5% and 49.7%, respectively, according to the Charlson. Multivariable models including the ACE-27 index outperformed Charlson-based models when assessing receipt of guideline-recommended therapies, with higher c-statistics and lower AICs. Neither index was clearly superior in prediction of two-year survival. CONCLUSIONS: The ACE-27 index measured using medical records captured more comorbidity and outperformed the Charlson index measured using administrative data for predicting receipt of guideline-recommended therapies, demonstrating the potential value of more detailed comorbidity data. However, the two indices had relatively similar performance when predicting survival.
Duke Scholars
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- Survival Rate
- Sensitivity and Specificity
- Prognosis
- Middle Aged
- Medical Records
- Male
- Lung Neoplasms
- Logistic Models
- Insurance, Health
- Humans
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Survival Rate
- Sensitivity and Specificity
- Prognosis
- Middle Aged
- Medical Records
- Male
- Lung Neoplasms
- Logistic Models
- Insurance, Health
- Humans