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Original article Best Definitions of Multimorbidity to Identify Patients With High Health Care Resource Utilization

机译:原始文章多重定义的多重定义,用于识别医疗保健资源利用率高的患者

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Objective To compare different definitions of multimorbidity to identify patients with higher health care resource utilization. Patients and Methods We used a multinational retrospective cohort including 147,806 medical inpatients discharged from 11 hospitals in 3 countries (United States, Switzerland, and Israel) between January 1, 2010, and December 31, 2011. We compared the area under the receiver operating characteristic curve (AUC) of 8 definitions of multimorbidity, based on International Classification of Diseases codes defining health conditions, the Deyo-Charlson Comorbidity Index, the Elixhauser-van Walraven Comorbidity Index, body systems, or Clinical Classification Software categories to predict 30-day hospital readmission and/or prolonged length of stay (longer than or equal to the country-specific upper quartile). We used a lower (yielding sensitivity ≥90%) and an upper (yielding specificity ≥60%) cutoff to create risk categories. Results Definitions had poor to fair discriminatory power in the derivation (AUC, 0.61-0.65) and validation cohorts (AUC, 0.64-0.71). The definitions with the highest AUC were number of (1) health conditions with involvement of 2 or more body systems, (2) body systems, (3) Clinical Classification Software categories, and (4) health conditions. At the upper cutoff, sensitivity and specificity were 65% to 79% and 50% to 53%, respectively, in the validation cohort; of the 147,806 patients, 5% to 12% (7474 to 18,008) were classified at low risk, 38% to 55% (54,484 to 81,540) at intermediate risk, and 32% to 50% (47,331 to 72,435) at high risk. Conclusion Of the 8 definitions of multimorbidity, 4 had comparable discriminatory power to identify patients with higher health care resource utilization. Of these 4, the number of health conditions may represent the easiest definition to apply in clinical routine. The cutoff chosen, favoring sensitivity or specificity, should be determined depending on the aim of the definition.
机译:目的比较多重定义的多重定义,鉴定保健资源利用更高的患者。患者和方法我们利用了一项跨国回顾队列,其中包括147,806名医疗住院患者,其中包括2010年1月1日至12月31日在3个国家(美国,瑞士和以色列)的11个国家(美国,瑞士和以色列)。我们比较了接收器运营特征下的区域8多个定义的曲线(AUC)的多重定义,基于国际疾病代码定义健康状况,Deyo-Charlson合并症,Elixhauser-van Walraven合并症指数,身体系统或临床分类软件类别预测30天医院阅览室和/或长时间的停留时间(比或等于国家特异性的上四分位数)。我们使用较低的(产生敏感性≥90%)和上部(产生特异性≥60%)截止,以创建风险类别。结果定义在衍生(AUC,0.61-0.65)和验证队列(AUC,0.64-0.71)中的公平歧视性差。具有最高AUC的定义是(1)健康状况的数量,其中2个或更多的身体系统,(2)机身系统,(3)临床分类软件类别,(4)健康状况。在验证队列中,在上部截止值下,敏感性和特异性分别为65%至79%和50%至53%;在147,806名患者中,5%至12%(7474至18,008)以低风险分类,中间风险为38%至55%(54,484至81,544),高风险高达32%至50%(47,331至72,435)。结论80多压率的定义,4具有可比的歧视动力来识别保健资源利用率更高的患者。在这4中,健康状况的数量可以代表临床常规应用最容易的定义。应根据定义的目的来确定选择,有利于灵敏度或特异性的截止值。

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