Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases.
Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases.
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DOI：
10.1186/1472-6963-8-12
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发表时间：
2008-01-14
影响因子：
2.8
通讯作者：
Quan H
中科院分区：
文献类型：
--
作者：
Li B;Evans D;Faris P;Dean S;Quan H
Charlson 和 Elixhauser 合并症测量在预测患者结果方面的表现已通过 ICD-9 数据得到了很好的验证，但未通过 ICD-10 数据得到了很好的验证，特别是在特定疾病的患者队列中。本研究的目的是评估这两种合并症指标在预测充血性心力衰竭 (CHF)、糖尿病、慢性肾衰竭 (CRF)、中风和接受冠状动脉旁路移植术 (CABG) 患者的院内死亡率和 1 年死亡率方面的表现。加拿大省医院出院管理数据库用于定义 17 种 Charlson 合并症和 30 种 Elixhauser 合并症。计算 C 统计值以评估两种措施的性能。一年的死亡率信息是从省生命统计部门获得的。 对于预测院内或 1 年死亡率的 Charlson 和 Elixhauser 合并症指标，ICD-9 和 ICD-10 数据在 C 统计中的绝对差异在 5 个队列中为 0 到 0.04。在使用 ICD-10 数据预测院内死亡率的模型中，Charlson 测量的 C 统计量范围为 0.62（中风）至 0.82（糖尿病），Elixhauser 测量的 C 统计量范围为 0.62（中风）至 0.83（CABG）。编码算法的变化并不影响 Charlson 或 Elixhauser 合并症测量在结果预测中的表现。这两种合并症指标在 ICD-10 数据中仍然是有效的预后指标，并且在 ICD-9 和 ICD-10 数据中预测短期和长期死亡率方面具有相似的表现。
The performance of the Charlson and Elixhauser comorbidity measures in predicting patient outcomes have been well validated with ICD-9 data but not with ICD-10 data, especially in disease specific patient cohorts. The objective of this study was to assess the performance of these two comorbidity measures in the prediction of in-hospital and 1 year mortality among patients with congestive heart failure (CHF), diabetes, chronic renal failure (CRF), stroke and patients undergoing coronary artery bypass grafting (CABG). A Canadian provincial hospital discharge administrative database was used to define 17 Charlson comorbidities and 30 Elixhauser comorbidities. C-statistic values were calculated to evaluate the performance of two measures. One year mortality information was obtained from the provincial Vital Statistics Department. The absolute difference between ICD-9 and ICD-10 data in C-statistics ranged from 0 to 0.04 across five cohorts for the Charlson and Elixhauser comorbidity measures predicting in-hospital or 1 year mortality. In the models predicting in-hospital mortality using ICD-10 data, the C-statistics ranged from 0.62 (for stroke) – 0.82 (for diabetes) for Charlson measure and 0.62 (for stroke) to 0.83 (for CABG) for Elixhauser measure. The change in coding algorithms did not influence the performance of either the Charlson or Elixhauser comorbidity measures in the prediction of outcome. Both comorbidity measures were still valid prognostic indicators in the ICD-10 data and had a similar performance in predicting short and long term mortality in the ICD-9 and ICD-10 data.
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影响因子：
7.2
作者：
Gabriel, SE;Crowson, CS;O'Fallon, WM
通讯作者：
O'Fallon, WM
影响因子：
3
作者：
Elixhauser, A;Steiner, C;Coffey, RN
通讯作者：
Coffey, RN
影响因子：
3
作者：
Stukenborg, GJ;Wagner, DP;Connors, AF
通讯作者：
Connors, AF
DOI：
10.1002/art.21440
发表时间：
2005-10-15
期刊：
ARTHRITIS & RHEUMATISM-ARTHRITIS CARE & RESEARCH
影响因子：
--
作者：
Dominick, KL;Dudley, TK;Bosworth, HB
通讯作者：
Bosworth, HB
影响因子：
3
作者：
Southern, DA;Quan, H;Ghali, WA
通讯作者：
Ghali, WA