Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality
<p>Abstract</p> <p>Background</p> <p>It is important to find a comorbidity measure with better performance for use with administrative data. The new method proposed by Elixhauser et al. has never been validated and compared to the widely used Charlson method in the Asia...
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doaj-4d7555487edd4a6db2b645570e3630712020-11-25T00:52:16ZengBMCBMC Health Services Research1472-69632010-05-0110114010.1186/1472-6963-10-140Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortalityNg Yee-YungChu Yu-TsengWu Shiao-Chi<p>Abstract</p> <p>Background</p> <p>It is important to find a comorbidity measure with better performance for use with administrative data. The new method proposed by Elixhauser et al. has never been validated and compared to the widely used Charlson method in the Asia region. The objective of this study was to compare the performance of three comorbidity measures using information from different data periods in predicting short- and long-term mortality among patients with acute myocardial infarction (AMI) and chronic obstructive pulmonary disease (COPD).</p> <p>Methods</p> <p>We conducted a retrospective cohort study using National Health Insurance claims data (2001-2002) in Taiwan. We constructed the Elixhauser, the Charlson/Deyo, and the Charlson/Romano methods based on the International Classification of Disease, 9th Revision, Clinical Modification codes in the claims data. Two data periods, including the index hospitalization as well as the index and prior 1-year hospitalizations, were used in the analysis. The performances were compared using the c-statistics derived from multiple logistic regression models that included age, gender, race, and whether the patient received surgery or not. The outcomes of interest were in-hospital and 1-year mortality.</p> <p>Results</p> <p>The performance was in the same rank order among both populations regardless of the outcome and data period: Elixhauser > Charlson/Romano > Charlson/Deyo. In predicting in-hospital mortality, the Elixhauser models using information from the index hospitalization performed best, even better than the Charlson/Deyo or Charlson/Romano models using information from the index and prior hospitalizations. Nevertheless, in predicting 1-year mortality, the Elixhauser models using information from the index and 1-year prior hospitalizations performed better than using information from the index hospitalization only.</p> <p>Conclusions</p> <p>This is so far the first study to validate the Elixhauser method and compare it to other methods in the Asia region, and is the first to report its differences in data periods between short- and long-term outcomes. The comorbidity measurement developed by Elixhauser et al. has relatively good predictive validity, and researchers should consider its use in claims-based studies.</p> http://www.biomedcentral.com/1472-6963/10/140 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ng Yee-Yung Chu Yu-Tseng Wu Shiao-Chi |
spellingShingle |
Ng Yee-Yung Chu Yu-Tseng Wu Shiao-Chi Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality BMC Health Services Research |
author_facet |
Ng Yee-Yung Chu Yu-Tseng Wu Shiao-Chi |
author_sort |
Ng Yee-Yung |
title |
Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality |
title_short |
Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality |
title_full |
Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality |
title_fullStr |
Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality |
title_full_unstemmed |
Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality |
title_sort |
comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality |
publisher |
BMC |
series |
BMC Health Services Research |
issn |
1472-6963 |
publishDate |
2010-05-01 |
description |
<p>Abstract</p> <p>Background</p> <p>It is important to find a comorbidity measure with better performance for use with administrative data. The new method proposed by Elixhauser et al. has never been validated and compared to the widely used Charlson method in the Asia region. The objective of this study was to compare the performance of three comorbidity measures using information from different data periods in predicting short- and long-term mortality among patients with acute myocardial infarction (AMI) and chronic obstructive pulmonary disease (COPD).</p> <p>Methods</p> <p>We conducted a retrospective cohort study using National Health Insurance claims data (2001-2002) in Taiwan. We constructed the Elixhauser, the Charlson/Deyo, and the Charlson/Romano methods based on the International Classification of Disease, 9th Revision, Clinical Modification codes in the claims data. Two data periods, including the index hospitalization as well as the index and prior 1-year hospitalizations, were used in the analysis. The performances were compared using the c-statistics derived from multiple logistic regression models that included age, gender, race, and whether the patient received surgery or not. The outcomes of interest were in-hospital and 1-year mortality.</p> <p>Results</p> <p>The performance was in the same rank order among both populations regardless of the outcome and data period: Elixhauser > Charlson/Romano > Charlson/Deyo. In predicting in-hospital mortality, the Elixhauser models using information from the index hospitalization performed best, even better than the Charlson/Deyo or Charlson/Romano models using information from the index and prior hospitalizations. Nevertheless, in predicting 1-year mortality, the Elixhauser models using information from the index and 1-year prior hospitalizations performed better than using information from the index hospitalization only.</p> <p>Conclusions</p> <p>This is so far the first study to validate the Elixhauser method and compare it to other methods in the Asia region, and is the first to report its differences in data periods between short- and long-term outcomes. The comorbidity measurement developed by Elixhauser et al. has relatively good predictive validity, and researchers should consider its use in claims-based studies.</p> |
url |
http://www.biomedcentral.com/1472-6963/10/140 |
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