Medicine authentication technology as a counterfeit medicine-detection tool: a Delphi method study to establish expert opinion on manual medicine authentication technology in secondary care

药品鉴定技术作为假药检测工具:一项德尔菲法研究,旨在建立专家对二级医疗机构人工药品鉴定技术的意见

阅读:1

Abstract

OBJECTIVES: This study aims to establish expert opinion and potential improvements for the Falsified Medicines Directive mandated medicines authentication technology. DESIGN AND INTERVENTION: A two-round Delphi method study using an online questionnaire. SETTING: Large National Health Service (NHS) foundation trust teaching hospital. PARTICIPANTS: Secondary care pharmacists and accredited checking technicians. PRIMARY OUTCOME MEASURES: Seven-point rating scale answers which reached a consensus of 70-80% with a standard deviation (SD) of <1.0. Likert scale questions which reached a consensus of 70-80%, a SD of <1.0 and classified as important according to study criteria. RESULTS: Consensus expert opinion has described database cross-checking technology as quick and user friendly and suggested the inclusion of an audio signal to further support the detection of counterfeit medicines in secondary care (70% consensus, 0.9 SD); other important consensus with a SD of <1.0 included reviewing the colour and information in warning pop up screens to ensure they were not mistaken for the 'already dispensed here' pop up, encouraging the dispenser/checker to act on the warnings and making it mandatory to complete an 'action taken' documentation process to improve the quarantine of potentially counterfeit, expired or recalled medicines. CONCLUSIONS: This paper informs key opinion leaders and decision makers as to the positives and negatives of medicines authentication technology from an operator's perspective and suggests the adjustments which may be required to improve operator compliance and the detection of counterfeit medicines in the secondary care sector.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。