Ghali, William A.Hall, Ruth E.Rosen, Amy K.Ash, Arlene S.Moskowitz, Mark A.2022-08-232022-08-231996-03-012010-07-01J Clin Epidemiol. 1996 Mar;49(3):273-8. <a href="http://dx.doi.org/10.1016/0895-4356(95)00564-1">Link to article on publisher's site</a>0895-4356 (Linking)10.1016/0895-4356(95)00564-18676173https://hdl.handle.net/20.500.14038/47512We 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.en-USAgedComorbidityCoronary Artery BypassCoronary DiseaseFemaleHospital MortalityHumansMaleMiddle AgedModels, StatisticalMultivariate AnalysisReproducibility of ResultsBiostatisticsEpidemiologyHealth Services ResearchJournal Articlehttps://escholarship.umassmed.edu/qhs_pp/6481378794qhs_pp/648