Validation of case-mix measures derived from self-reports of diagnoses and health
Validation of case-mix measures derived from self-reports of diagnoses and health
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DOI：
10.1016/s0895-4356(01)00493-0
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发表时间：
2002-04-01
影响因子：
7.2
通讯作者：
Fihn, SD
中科院分区：
文献类型：
--
作者：
Fan, VS;Au, D;Fihn, SD
自我报告的慢性病和健康状况与资源利用相关。然而，关于其预测死亡率或住院治疗能力的数据很少，我们试图确定自我报告的慢性疾病和 SF-36 是否可以单独或组合使用来评估门诊环境中的共病。该研究被设计为前瞻性队列研究。患者在参与流动护理质量改进项目 (ACQUIP) 的七个退伍军人事务部 (VA) 医疗中心的初级保健诊所入组。 10,947 名年龄大于或等于 50 岁的患者入组于普通内科诊所，他们返回了基线健康库存清单和基线 SF-36，并平均随访了 722.5 (+/-84.3) 天。主要结局是全因死亡率，次要结局是在 VA 系统内住院。在 5,469 名患者的开发组中使用 Cox 比例风险模型，利用年龄、吸烟状况以及 25 种自我报告的与死亡率增加相关的医疗状况中的 7 种信息构建了共病指数 [西雅图共病指数 (SIC)]。在 5,478 名患者的验证集中，SIC 可以预测 VA 系统内的死亡率和住院情况。构建了一个单独的模型，其中仅输入 SF-36 的年龄以及 PCS 和 MCS 评分来预测死亡率。 SF-36 成分评分和 SIC 具有相当的区分能力（两种模型的死亡区分 AUC 均在 2 y 0.71 以内）。合并时，SIC 和 SF-36 共同改善了对死亡率的区分（AUC = 0.74，AUC 差异的 p 值 < 0.005）。使用基线健康库存清单上自我识别的慢性医疗状况开发的新门诊合并症评分可预测一般内科患者 VA 系统内的 2 年死亡率和住院率。 (C) 2002 Elsevier Science Inc. 保留所有权利。
Self-reported chronic diseases and health status are associated with resource use. However, few data exist regarding their ability to predict mortality or hospitalizations, We sought to determine whether self-reported chronic medical conditions and the SF-36 could be used individually or in combination to assess co-morbidity in the outpatient setting. The study was designed as a prospective cohort study. Patients were enrolled in the primary care clinics at seven Veterans Affairs (VA) medical centers participating in the Ambulatory Care Quality Improvement Project (ACQUIP). 10,947 patients, greater than or equal to 50 years of age, enrolled in general internal medicine clinics who returned both a baseline health inventory checklist and the baseline SF-36 who were followed for a mean of 722.5 (+/-84.3) days. The primary outcome was all-cause mortality, with a secondary outcome of hospitalization within the VA system. Using a Cox proportional hazards model in a development set of 5,469 patients, a co-morbidity index [Seattle Index of Co-morbidity (SIC)] was constructed using information about age, smoking status and seven of 25 self-reported medical conditions that were associated with increased mortality. In the validation set of 5,478 patients, the SIC was predictive of both mortality and hospitalizations within the VA system. A separate model was constructed in which only age and the PCS and MCS scores of the SF-36 were entered to predict mortality. The SF-36 component scores and the SIC had comparable discriminatory ability (AUC for discrimination of death within 2 y 0.71 for both models), When combined, the SIC and SF-36 together had improved discrimination for mortality (AUC = 0.74, p-value for difference in AUC < 0.005). A new outpatient co-morbidity score developed using self-identified chronic medical conditions on a baseline health inventory checklist was predictive of 2-y mortality and hospitalization within the VA system in general internal medicine patients. (C) 2002 Elsevier Science Inc. All rights reserved.