Suppr超能文献

就针对婴幼儿潜在危害的医院处方指标达成共识。

Developing consensus on hospital prescribing indicators of potential harm for infants and children.

作者信息

Fox Andy, Pontefract Sarah, Brown David, Portlock Jane, Coleman Jamie

机构信息

Southampton Pharmacy Research Centre, University Hospitals Southampton, Southampton, Hampshire,, SO16 6YD.

NIHR Doctoral Research Fellow, School of Pharmacy, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT.

出版信息

Br J Clin Pharmacol. 2016 Aug;82(2):451-60. doi: 10.1111/bcp.12954. Epub 2016 May 18.

Abstract

AIMS

The aim of the study was to develop a list of hospital based paediatric prescribing indicators that can be used to assess the impact of electronic prescribing or clinical decision support tools on paediatric prescribing errors.

METHODS

Two rounds of an electronic consensus method (eDelphi) were carried out with 21 expert panellists from the UK. Panellists were asked to score each prescribing indicator for its likelihood of occurrence and severity of outcome should the error occur. The scores were combined to produce a risk score and a median score for each indicator calculated. The degree of consensus between panellists was defined as the proportion that gave a risk score in the same category as the median. Indicators were included if a consensus of 80% or higher was achieved and were in the high risk categories.

RESULTS

Each of the 21 panellists completed an exploratory round and two rounds of scoring. This identified 41 paediatric prescribing indicators with a high risk rating and greater than 80% consensus. The most common error type within the indicators was wrong dose (n = 19) and the most common drug classes were antimicrobials (n = 10) and cardiovascular (n = 7).

CONCLUSIONS

A set of 41 paediatric prescribing indicators describing potential harm for the hospital setting has been identified by an expert panel. The indicators provide a standardized method of evaluation of prescribing data on both paper and electronic systems. They can also be used to assess implementation of clinical decision support systems or other quality improvement initiatives.

摘要

目的

本研究的目的是制定一份基于医院的儿科处方指标清单,可用于评估电子处方或临床决策支持工具对儿科处方错误的影响。

方法

对来自英国的21名专家小组成员进行了两轮电子共识方法(电子德尔菲法)。要求小组成员对每个处方指标在错误发生时出现的可能性及其结果的严重性进行评分。将分数合并以产生风险分数,并计算每个指标的中位数分数。小组成员之间的共识程度定义为给出与中位数相同类别风险分数的比例。如果达成80%或更高的共识且属于高风险类别,则纳入指标。

结果

21名小组成员每人都完成了一轮探索性评分和两轮评分。这确定了41个具有高风险评级且共识度超过80%的儿科处方指标。指标中最常见的错误类型是剂量错误(n = 19),最常见的药物类别是抗菌药物(n = 10)和心血管药物(n = 7)。

结论

一个专家小组确定了一组41个描述医院环境中潜在危害的儿科处方指标。这些指标提供了一种评估纸质和电子系统处方数据的标准化方法。它们还可用于评估临床决策支持系统的实施或其他质量改进举措。

相似文献

8
[Formal criteria for good prescribing in the hospital].[医院合理处方的正式标准]
Ther Umsch. 2014 Jun;71(6):343-51. doi: 10.1024/0040-5930/a000522.
10
Preventing drug-related morbidity--determining valid indicators.预防药物相关发病——确定有效指标
Int J Qual Health Care. 2002 Jun;14(3):183-98. doi: 10.1093/oxfordjournals.intqhc.a002610.

本文引用的文献

3
Quality indicators for high acuity pediatric conditions.高质量指标与儿科急重症相关。
Pediatrics. 2013 Oct;132(4):752-62. doi: 10.1542/peds.2013-0854. Epub 2013 Sep 23.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验