Use of a self-report-generated charlson comorbidity index for predicting mortality
Use of a self-report-generated charlson comorbidity index for predicting mortality
复制标题
DOI：
10.1097/01.mlr.0000163658.65008.ec
复制
发表时间：
2005-06-01
期刊：
影响因子：
3
通讯作者：
Meltzer, D
中科院分区：
文献类型：
--
作者：
Chaudhry, S;Jin, L;Meltzer, D
背景：Charlson共病指数是一种流行的风险调整工具，通常是根据病历摘要或管理数据构建的。这两个来源的局限性都激发了人们对使用患者自我报告作为替代方案的兴趣。目的：我们试图确定自我报告的Chanson指数是否可以预测死亡率，它相对于来自管理数据的指数的表现，以及使用研究特定的权重而不是Charlson的原始权重是否增强了模型的拟合。方法：我们调查了4年来住进大学医疗服务的7761名患者，并提取了他们的管理数据。我们使用2种权重方案(原始Charlson权重和特定于研究对象的权重)和3种不同的数据源(ICD-9 cm指数住院数据、ICD-9 cm数据和1年回顾期间的ICD-9 cm数据以及患者的合并症报告)构建了6个不同的Charlson指数。结果：Charlson指数的6项指标均可预测1年死亡率。无论使用6个Charlson指数中的哪一个，具有年龄和性别的模型，无论是否有与诊断相关的组，都具有大致相同的预测能力。然而，使用管理数据与自我报告或研究特定权重与原始权重相比，模型拟合度有微小的改善。所有模型得到的受试者操作曲线下面积在0.70到0.77之间。结论：总的来说，自我报告的Charlson指数与基于管理数据的指数对1年死亡率的预测具有可比性。
Background: The Charlson Comorbidity Index, a popular tool for risk adjustment, often is constructed from medical record abstracts or administrative data. Limitations in both sources have fueled interest in using patient self-report as an alternative. However, little data exist on whether self-reported Charlson Indices predict mortality.Objectives: We sought to determine whether a self-reported Chanson Index predicts mortality, its performance relative to indices derived from administrative data, and whether using study-specific weights instead of Charlson's original weights enhances model fit.Methods: We surveyed 7761 patients admitted to a university medical service over the course of 4 years and extracted their administrative data. We constructed 6 different Charlson indices by using 2 weighting schemes (original Charlson weights and studyspecific weights) and 3 different datasources (ICD-9CM data for index hospitalization, ICD-9CM data with a 1-year look-back period, and patient self-report of comorbidities.) Multivariate models were constructed predicting 1-year mortality, log total costs, and log length of stay.Results: The 6 measures of the Charlson index all predicted 1-year mortality. Models with age and gender, with or without diagnosis-related group, had approximately the same predictive power regardless of which of the 6 Charlson indices were used. Nevertheless, there were small improvements in model fit using administrative data versus self-report, or study-specific versus original weights. All models obtained areas under the receiver operating curve of 0.70 to 0.77.Conclusions: Overall, self-reported Charlson indices predict 1-year mortality comparably with indices based on administrative data.