Kyoung Hoon Kim1, Lee Su Ahn. 1. Review & Assessment Policy Institute, Health Insurance Review & Assessment Service, Korea.
Abstract
OBJECTIVES: To compare the performance of three comorbidity measurements (Charlson comorbidity index, Elixhauser's comorbidity and comorbidity selection) with the effect of different comorbidity lookback periods when predicting in-hospital mortality for patients who underwent percutaneous coronary intervention. METHODS: This was a retrospective study on patients aged 40 years and older who underwent percutaneous coronary intervention. To distinguish comorbidity from complications, the records of diagnosis were drawn from the National Health Insurance Database excluding diagnosis that admitted to the hospital. C-statistic values were used as measures for in comparing the predictability of comorbidity measures with lookback period, and a bootstrapping procedure with 1,000 replications was done to determine approximate 95% confidence interval. RESULTS: Of the 61,815 patients included in this study, the mean age was 63.3 years (standard deviation: +/-10.2) and 64.8% of the population was male. Among them, 1,598 (2.6%) had died in hospital. While the predictive ability of the Elixhauser s comorbidity and comorbidity selection was better than that of the Charlson comorbidity index, there was no significant difference among the three comorbidity measurements. Although the prevalence of comorbidity increased in 3 years of lookback periods, there was no significant improvement compared to 1 year of a lookback period. CONCLUSIONS: In a health outcome study for patients who underwent percutaneous coronary intervention using National Health Insurance Database, the Charlson comorbidity index was easy to apply without significant difference in predictability compared to the other methods. The one year of observation period was adequate to adjust the comorbidity. Further work to select adequate comorbidity measurements and lookback periods on other diseases and procedures are needed.
OBJECTIVES: To compare the performance of three comorbidity measurements (Charlson comorbidity index, Elixhauser's comorbidity and comorbidity selection) with the effect of different comorbidity lookback periods when predicting in-hospital mortality for patients who underwent percutaneous coronary intervention. METHODS: This was a retrospective study on patients aged 40 years and older who underwent percutaneous coronary intervention. To distinguish comorbidity from complications, the records of diagnosis were drawn from the National Health Insurance Database excluding diagnosis that admitted to the hospital. C-statistic values were used as measures for in comparing the predictability of comorbidity measures with lookback period, and a bootstrapping procedure with 1,000 replications was done to determine approximate 95% confidence interval. RESULTS: Of the 61,815 patients included in this study, the mean age was 63.3 years (standard deviation: +/-10.2) and 64.8% of the population was male. Among them, 1,598 (2.6%) had died in hospital. While the predictive ability of the Elixhauser s comorbidity and comorbidity selection was better than that of the Charlson comorbidity index, there was no significant difference among the three comorbidity measurements. Although the prevalence of comorbidity increased in 3 years of lookback periods, there was no significant improvement compared to 1 year of a lookback period. CONCLUSIONS: In a health outcome study for patients who underwent percutaneous coronary intervention using National Health Insurance Database, the Charlson comorbidity index was easy to apply without significant difference in predictability compared to the other methods. The one year of observation period was adequate to adjust the comorbidity. Further work to select adequate comorbidity measurements and lookback periods on other diseases and procedures are needed.
Authors: Lorenzo Azzalini; Malorie Chabot-Blanchet; Danielle A Southern; Anna Nozza; Stephen B Wilton; Michelle M Graham; Guillaume Marquis Gravel; Jean-Pierre Bluteau; Jean-Lucien Rouleau; Marie-Claude Guertin; E Marc Jolicoeur Journal: CMAJ Date: 2019-03-18 Impact factor: 8.262
Authors: Abbey Diaz; Peter D Baade; Patricia C Valery; Lisa J Whop; Suzanne P Moore; Joan Cunningham; Gail Garvey; Julia M L Brotherton; Dianne L O'Connell; Karen Canfell; Diana Sarfati; David Roder; Elizabeth Buckley; John R Condon Journal: PLoS One Date: 2018-05-08 Impact factor: 3.240