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Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data
W A Ghali1, R E Hall, A K Rosen
1Health Care Research Unit, Boston University Medical Center, MA 02118, USA.
Insights
Developing a new comorbidity index using study-specific weights improved mortality prediction in cardiac surgery patients. This enhanced risk adjustment offers better insights than standard Charlson comorbidity index adaptations.
Area of Science:
- Health Services Research
- Medical Informatics
- Cardiovascular Surgery
Background:
- Accurate comorbidity risk adjustment is crucial for evaluating patient outcomes in healthcare.
- The Charlson comorbidity index is a widely used tool, but its adaptations may vary in effectiveness.
- Coronary artery bypass surgery (CABS) patient data from Massachusetts were used to assess comorbidity measures.
Purpose of the Study:
- To compare the performance of two International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) adaptations of the Charlson comorbidity index.
- To develop and validate a novel comorbidity index using study-specific weights for improved mortality prediction.
- To assess the impact of different comorbidity scoring methods on predicting mortality in CABS patients.
Main Methods:
- Two established ICD-9-CM adaptations of the Charlson comorbidity index (Deyo and Dartmouth-Manitoba) were applied to CABS patient data.
- A new comorbidity index was created by assigning unique weights to the original Charlson comorbidity variables based on study data.
- Statistical analysis, including kappa statistics and model performance metrics (c-statistic), was used for comparison.
Main Results:
- The two ICD-9-CM adaptations of the Charlson index demonstrated high agreement (90% identical scores) and consistency in identifying comorbidities (kappa 0.72-1.0).
- The novel, study-specific weighted index identified a 10% high-risk patient group with 15% mortality, outperforming the standard Charlson index (5% group, 8% mortality; p=0.01).
- The model incorporating the new index showed superior predictive performance (c=0.74) compared to the model using the original Charlson index (c=0.70).
Conclusions:
- The choice of ICD-9-CM adaptation for the Charlson comorbidity index had minimal impact on scoring in this CABS cohort.
- Utilizing study-specific weights with Charlson comorbidity variables significantly enhances the predictive power for mortality.
- This customized approach offers a more accurate risk adjustment strategy for patient populations undergoing coronary artery bypass surgery.
Abstract:
We studied approaches to comorbidity risk adjustment by comparing two ICD-9-CM adaptations (Deyo, Dartmouth-Manitoba) of the Charlson comorbidity index applied to Massachusetts coronary artery bypass surgery data. We also developed a new comorbidity index by assigning study-specific weights to the original Charlson comorbidity variables. The 2 ICD-9-CM coding adaptations assigned identical Charlson comorbidity scores to 90% of cases, and specific comorbidities were largely found in the same cases (kappa values of 0.72-1.0 for 15 of 16 comorbidities). Meanwhile, the study-specific comorbidity index identified a 10% subset of patients with 15% mortality, whereas the 5% highest-risk patients according to the Charlson index had only 8% mortality (p = 0.01). A model using the new index to predict mortality had better validated performance than a model based on the original Charlson index (c = 0.74 vs. 0.70). Thus, in our population, the ICD-9-CM adaptation used to create the Charlson score mattered little, but using study-specific weights with the Charlson variables substantially improved the power of these data to predict mortality.