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美国医院中与死亡率相关的医院及药房特征。

Hospital and pharmacy characteristics associated with mortality rates in United States hospitals.

作者信息

Pitterle M E, Bond C A, Raehl C L, Franke T

机构信息

School of Pharmacy, University of Wisconsin-Madison 53706.

出版信息

Pharmacotherapy. 1994 Sep-Oct;14(5):620-30.

PMID:7997398
Abstract

We attempted to determine hospital and pharmacy characteristics associated with mortality rates in 4864 United States hospitals. Data were obtained from the Health Care Financing Administration, the American Hospital Association, and the National Clinical Pharmacy Services survey. Univariate and multivariate regression models were used to determine which hospital characteristics were associated with mortality. A similar regression analysis was performed on 718 hospitals for which detailed pharmacy information was available. In a multivariate regression model, some characteristics of 4864 hospitals associated with reduced mortality rates were high-technology index (R2 = 0.09, p < 0.001), severity of illness (R2 = 0.048, p < 0.001), number of hospital beds (R2 = 0.016, p < 0.001), and medical personnel (R2 = 0.012, p < 0.001). This analysis accounted for 41% of the mortality rate variance. For the 718 hospitals and pharmacies, some of these characteristics were high-technology index (R2 = 0.157, p < 0.001), severity of illness (R2 = 0.07, p < 0.001), number of pharmacists/average daily census (R2 = 0.021, p < 0.001), and combined hospitalwide clinical pharmacy services (R2 = 0.016, p < 0.01). The results of this analysis were similar to those in the only other large study in this area, but that excluded pharmacy characteristics. This is the first study to show a statistically significant association between pharmacist and pharmacy variables and reduced hospital mortality rates.

摘要

我们试图确定美国4864家医院中与死亡率相关的医院和药房特征。数据来自医疗保健财务管理局、美国医院协会和国家临床药学服务调查。使用单变量和多变量回归模型来确定哪些医院特征与死亡率相关。对718家可获取详细药房信息的医院进行了类似的回归分析。在多变量回归模型中,4864家医院中与死亡率降低相关的一些特征包括高科技指数(R2 = 0.09,p < 0.001)、疾病严重程度(R2 = 0.048,p < 0.001)、医院病床数量(R2 = 0.016,p < 0.001)和医务人员(R2 = 0.012,p < 0.001)。该分析解释了死亡率差异的41%。对于718家医院和药房,其中一些特征包括高科技指数(R2 = 0.157,p < 0.001)、疾病严重程度(R2 = 0.07,p < 0.001)、药剂师数量/平均每日普查人数(R2 = 0.021,p < 0.001)以及全院综合临床药学服务(R2 = 0.016,p < 0.01)。该分析结果与该领域另一项唯一的大型研究结果相似,但后者未纳入药房特征。这是第一项显示药剂师和药房变量与降低医院死亡率之间存在统计学显著关联的研究。

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