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住院患者口服喹诺酮类药物:一项计算机化决策支持干预措施的评估

Oral quinolones in hospitalized patients: an evaluation of a computerized decision support intervention.

作者信息

Hulgan T, Rosenbloom S T, Hargrove F, Talbert D A, Arbogast P G, Bansal P, Miller R A, Kernodle D S

机构信息

Department of Medicine, Division of Infectious Diseases, Vanderbilt University School of Medicine, 345 24th Avenue N, Suite 105, Nashville, TN 37203, USA.

出版信息

J Intern Med. 2004 Oct;256(4):349-57. doi: 10.1111/j.1365-2796.2004.01375.x.

Abstract

OBJECTIVE

To determine whether a computerized decision support system could increase the proportion of oral quinolone antibiotic orders placed for hospitalized patients.

DESIGN

Prospective, interrupted time-series analysis.

SETTING

University hospital in the south-eastern United States.

SUBJECTS

Inpatient quinolone orders placed from 1 February 2001 to 31 January 2003.

INTERVENTION

A web-based intervention was deployed as part of an existing order entry system at a university hospital on 5 February 2002. Based on an automated query of active medication and diet orders, some users ordering intravenous quinolones were presented with a suggestion to consider choosing an oral formulation.

MAIN OUTCOME MEASURE

The proportion of inpatient quinolone orders placed for oral formulations before and after deployment of the intervention.

RESULTS

There were a total of 15 194 quinolone orders during the study period, of which 8962 (59%) were for oral forms. Orders for oral quinolones increased from 4202 (56%) before the intervention to 4760 (62%) after, without a change in total orders. In the time-series analysis, there was an overall 5.6% increase (95% CI 2.8-8.4%; P < 0.001) in weekly oral quinolone orders due to the intervention, with the greatest effect on nonintensive care medical units.

CONCLUSIONS

A web-based intervention was able to increase oral quinolone orders in hospitalized patients. This is one of the first studies to demonstrate a significant effect of a computerized intervention on dosing route within an antibiotic class. This model could be applied to other antibiotics or other drug classes with good oral bioavailability.

摘要

目的

确定计算机化决策支持系统能否提高住院患者口服喹诺酮类抗生素医嘱的比例。

设计

前瞻性中断时间序列分析。

地点

美国东南部的大学医院。

研究对象

2001年2月1日至2003年1月31日期间下达的住院患者喹诺酮类医嘱。

干预措施

2002年2月5日,在一所大学医院,基于现有医嘱录入系统部署了一项基于网络的干预措施。根据对当前用药和饮食医嘱的自动查询,一些开具静脉用喹诺酮类药物的用户会收到考虑选择口服剂型的建议。

主要观察指标

干预措施实施前后住院患者口服喹诺酮类药物医嘱的比例。

结果

研究期间共下达了15194条喹诺酮类医嘱,其中8962条(59%)为口服剂型。口服喹诺酮类药物的医嘱从干预前的4202条(56%)增加到干预后的4760条(62%),总医嘱数量未变。在时间序列分析中,由于该干预措施,每周口服喹诺酮类药物医嘱总体增加了5.6%(95%可信区间2.8 - 8.4%;P < 0.001),对非重症监护病房的影响最大。

结论

基于网络的干预措施能够增加住院患者口服喹诺酮类药物的医嘱。这是首批证明计算机化干预措施对某一类抗生素给药途径有显著影响的研究之一。该模式可应用于其他抗生素或具有良好口服生物利用度的其他药物类别。

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