Monitoring antibiotic usage: an update

Anthony Morton MScAppl, MD, MS, David Looke FRACP, FRCPA, MMedSci
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引用次数: 3

Abstract

Within a hospital, antibiotic usage can be affected by clustering of infections. In addition, pharmacy imprest systems may deliver stock in one time period that are used in a subsequent time period. As a result, hospital antibiotic usage data can be unpredictable and highly variable.

Usage of an antibiotic can be conveniently displayed in a time-series chart with monthly defined daily doses (DDDs) per 1000 bed-days on the vertical axis and months on the horizontal axis. To account for random variation, the chart should ideally have control limits, for example a Shewhart chart. However, conventional Shewhart control charts rely on the availability of a run of predictable data values so that the average and its variability can be determined. Since this may be difficult to achieve with hospital antibiotic usage data, a conventional control chart may give misleading information. A modified control chart based on a generalised additive model can overcome the difficulty in the analysis of these data. This chart is not difficult to employ or interpret.

监测抗生素使用情况:最新进展
在医院内,抗生素的使用可能受到聚集性感染的影响。此外,药房预付系统可以在一个时间段内交付库存,并在随后的时间段内使用。因此,医院抗生素使用数据可能是不可预测和高度可变的。抗生素的使用情况可以方便地以时间序列图表显示,纵轴为每1000个床日的月定义日剂量(DDDs),横轴为月。为了解释随机变化,图表应该有理想的控制限制,例如Shewhart图表。然而,传统的Shewhart控制图依赖于一系列可预测数据值的可用性,以便确定平均值及其可变性。由于医院抗生素使用数据很难做到这一点,传统的控制图可能会给出误导性的信息。一种基于广义加性模型的改进控制图可以克服这些数据分析的困难。这张图表不难运用或解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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