Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality
Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality
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DOI：
10.1186/1472-6963-10-140
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发表时间：
2010-05-27
影响因子：
2.8
通讯作者：
Wu, Shiao-Chi
中科院分区：
文献类型：
--
作者：
Chu, Yu-Tseng;Ng, Yee-Yung;Wu, Shiao-Chi
背景：重要的是要找到一个更好的性能与管理数据使用的共效性措施。Elixhauser等人提出的新方法从未经过验证，也从未与亚洲地区广泛使用的Charlson方法进行过比较。本研究的目的是比较三个comorbance措施的性能，使用不同的数据期间的信息，在预测短期和长期死亡率的急性心肌梗死（AMI）和慢性阻塞性肺疾病（COPD）患者之间的方法：我们进行了一项回顾性队列研究，使用国民健康保险索赔数据（2001-2002年）在台湾。我们根据国际疾病分类第9版和索赔数据中的临床修改代码构建了Elixhauser、Charlson/Deyo和Charlson/Romano方法。分析中使用了两个数据期，包括首次住院以及首次和既往1年住院。使用来自多元逻辑回归模型的c-统计量比较性能，包括年龄、性别、种族和患者是否接受手术。感兴趣的结果是在医院和1年mortals.Results：性能是在两个人群中，无论结果和数据期间相同的排名顺序：Elixhauser > Charlson/Romano > Charlson/Deyo。在预测住院死亡率方面，使用指数住院信息的Elixhauser模型表现最好，甚至优于使用指数和既往住院信息的Charlson/Deyo或Charlson/Romano模型。然而，在预测1年的死亡率，Elixhauser模型使用的信息，从指数和1年前住院比使用的信息，从指数hospitalization.Conclusions：这是迄今为止第一项研究，以验证Elixhauser方法，并将其与其他方法在亚洲地区，是第一个报告其差异的数据期间之间的短期和长期的结果。Elixhauser等人开发的共病测量具有相对较好的预测效度，研究人员应考虑将其用于基于索赔的研究。
Background: 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).Methods: 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.Results: 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.Conclusions: 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.