Anthony Morton MScAppl, MD, MS, David Looke FRACP, FRCPA, MMedSci
{"title":"Monitoring antibiotic usage: an update","authors":"Anthony Morton MScAppl, MD, MS, David Looke FRACP, FRCPA, MMedSci","doi":"10.1016/S1329-9360(16)30003-7","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p><p>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.</p></div>","PeriodicalId":92877,"journal":{"name":"Australian infection control : official journal of the Australian Infection Control Association Inc","volume":"12 4","pages":"Pages 127-129"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1329-9360(16)30003-7","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Australian infection control : official journal of the Australian Infection Control Association Inc","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1329936016300037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2016/3/17 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
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.