BACKGROUND: By accounting for level of comorbidity, risk-adjustment models should quantify the risk of death. How accurately comorbidity indices predict risk of death in Medicare beneficiaries with atrial fibrillation is unclear. OBJECTIVES: We sought to quantify how well 3 administrative-data based comorbidity indices (Deyo, Romano, and Elixhauser) predict mortality compared with a chart-review index. DESIGN: We undertook a retrospective cohort study using Medicare claim data (1995-1999) and medical record review. SUBJECTS: We studied Medicare beneficiaries (n = 2728; mean age = 77) with a common cardiac dysrhythmia, atrial fibrillation. MEASURES: The outcome was time to death with the accuracy of the comorbidity indices measured by the c-statistic. RESULTS: Correlation between Deyo and Romano indices was strong, but weak between them and the other indices. Prevalence of many comorbidity conditions varied with different indices. Compared with demographic data alone (c = 0.64), all comorbidity indices predicted death significantly (P < 0.001) better: the c index was 0.76 for Deyo, 0.78 for Romano, 0.76 for Elixhauser, and 0.75 for medical record review. The 95% confidence intervals of the c-statistic for the 4 indices overlapped with one another. Key comorbidity conditions for death included metastatic cancer, neuropsychiatric disease, heart failure, and liver disease. CONCLUSION: The predictive accuracy of 3 administrative-data based indices was similar and comparable with chart-review.
BACKGROUND: By accounting for level of comorbidity, risk-adjustment models should quantify the risk of death. How accurately comorbidity indices predict risk of death in Medicare beneficiaries with atrial fibrillation is unclear. OBJECTIVES: We sought to quantify how well 3 administrative-data based comorbidity indices (Deyo, Romano, and Elixhauser) predict mortality compared with a chart-review index. DESIGN: We undertook a retrospective cohort study using Medicare claim data (1995-1999) and medical record review. SUBJECTS: We studied Medicare beneficiaries (n = 2728; mean age = 77) with a common cardiac dysrhythmia, atrial fibrillation. MEASURES: The outcome was time to death with the accuracy of the comorbidity indices measured by the c-statistic. RESULTS: Correlation between Deyo and Romano indices was strong, but weak between them and the other indices. Prevalence of many comorbidity conditions varied with different indices. Compared with demographic data alone (c = 0.64), all comorbidity indices predicted death significantly (P < 0.001) better: the c index was 0.76 for Deyo, 0.78 for Romano, 0.76 for Elixhauser, and 0.75 for medical record review. The 95% confidence intervals of the c-statistic for the 4 indices overlapped with one another. Key comorbidity conditions for death included metastatic cancer, neuropsychiatric disease, heart failure, and liver disease. CONCLUSION: The predictive accuracy of 3 administrative-data based indices was similar and comparable with chart-review.
Authors: Huang-Tz Ou; Bhramar Mukherjee; Steven R Erickson; John D Piette; Richard P Bagozzi; Rajesh Balkrishnan Journal: Popul Health Manag Date: 2012-06-25 Impact factor: 2.459
Authors: Seungyoung Hwang; Ravishankar Jayadevappa; Jarcy Zee; Kara Zivin; Hillary R Bogner; Patrick J Raue; Martha L Bruce; Charles F Reynolds; Joseph J Gallo Journal: Am J Geriatr Psychiatry Date: 2014-08-27 Impact factor: 4.105
Authors: Wolfgang C Winkelmayer; Amanda R Patrick; Jun Liu; M Alan Brookhart; Soko Setoguchi Journal: J Am Soc Nephrol Date: 2011-01-13 Impact factor: 10.121
Authors: Wolfgang C Winkelmayer; Jun Liu; Amanda R Patrick; Soko Setoguchi; Niteesh K Choudhry Journal: J Nephrol Date: 2012 May-Jun Impact factor: 3.902
Authors: Benjamin A Goldstein; Cristina M Arce; Mark A Hlatky; Mintu Turakhia; Soko Setoguchi; Wolfgang C Winkelmayer Journal: Circulation Date: 2012-10-02 Impact factor: 29.690
Authors: Angelina R Sutin; Antonio Terracciano; Yuri Milaneschi; Yang An; Luigi Ferrucci; Alan B Zonderman Journal: JAMA Psychiatry Date: 2013-08 Impact factor: 21.596