Assessing and using comorbidity measures in elderly veterans with lower extremity amputations
Assessing and using comorbidity measures in elderly veterans with lower extremity amputations
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DOI：
10.1159/000101703
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发表时间：
2007-01-01
期刊：
影响因子：
3.5
通讯作者：
Reker, Dean M.
中科院分区：
文献类型：
--
作者：
Kurichi, Jibby E.;Stineman, Margaret G.;Reker, Dean M.
背景：了解下肢截肢老年退伍军人的合并症患病率和合并症的影响可能有助于评估患者的治疗结果、资源使用和设施水平的护理质量。目标：确定将门诊患者添加到住院患者管理数据源中可以在多大程度上产生更高的合并症患病率估计值和提高预测 1 年死亡率模型的解释力，并比较 Charlson/Deyo 和 Elixhauser 合并症测量值。方法：进行了一项应用频率、交叉表和逻辑回归模型的回顾性队列研究，其中包括 2,375 名下肢截肢退伍军人的数据。根据 Charlson/Deyo 和 Elixhauser 指标分析了合并症患病率、1 年死亡率和标准化死亡率 (SMR)。结果：通过添加来自多个环境的数据，Charlson/Deyo 和 Elixhauser 测量的合并症患病率估计值急剧增加。与 Charlson/Deyo 相比，Elixhauser 通常产生更高的估计值，但并没有提高对死亡率的解释能力。预期死亡人数与实际死亡人数的建模在不同地理区域产生了不同的 SMR，但不依赖于使用的衡量标准或数据源。结论：将门诊患者与住院患者数据合并可能会减少合并症的编码不足，但不会提高死亡率预测。与 Charlson/Deyo 相比，Elixhauser 对于糖尿病和周围血管疾病等合并症有更完整的编码方案，这对于解决下肢截肢的病因很重要。版权所有 (c) 2007 S. Karger AG，巴塞尔。
Background: Understanding comorbidity prevalence and the effects of comorbidities in older veterans with lower extremity amputations may aid in assessing patient outcomes, resource use, and facility-level quality of care. Objectives: To determine the degree to which adding outpatient to inpatient administrative data sources yields higher comorbidity prevalence estimates and improved explanatory power of models predicting 1-year mortality and to compare the Charlson/Deyo and Elixhauser comorbidity measures. Methods: A retrospective cohort study applying frequencies, cross-tabulations, and logistic regression models was conducted, including data from 2,375 veterans with lower extremity amputations. Comorbidity prevalence according to the Charlson/Deyo and Elixhauser measures, 1-year mortality rates, and standardized mortality ratios (SMRs) were analyzed. Results: Comorbidity prevalence estimates increased sharply for both the Charlson/Deyo and Elixhauser measures with the addition of data from multiple settings. The Elixhauser compared to the Charlson/Deyo generally yielded higher estimates but did not improve explanatory power for mortality. Modeling expected versus actual deaths produced varying SMRs across geographic regions but was not dependent on which measure or data sources were used. Conclusions: Merging outpatient with inpatient data may reduce the under coding of comorbidities but does not enhance mortality prediction. Compared to the Charlson/ Deyo, the Elixhauser has a more complete coding scheme for comorbid conditions, such as diabetes mellitus and peripheral vascular disease, important to addressing lower extremity amputation etiology. Copyright (c) 2007 S. Karger AG, Basel.