• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

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

社区药房中药物相互作用警报的管理。

Management of drug-interaction alerts in community pharmacies.

作者信息

Indermitte J, Beutler M, Bruppacher R, Meier C R, Hersberger K E

机构信息

Department of Pharmaceutical Sciences, Institute of Clinical Pharmacy, University of Basel, Basel, Switzerland.

出版信息

J Clin Pharm Ther. 2007 Apr;32(2):133-42. doi: 10.1111/j.1365-2710.2007.00802.x.

DOI:10.1111/j.1365-2710.2007.00802.x
PMID:17381663
Abstract

BACKGROUND AND OBJECTIVE

Drug-interaction alert systems are commonly used in community pharmacies to identify potential drug-drug interactions. However, depending on the software default setting, pharmacists may override alerts because they are too numerous. We explored the handling of drug-interaction alerts by community pharmacies in Switzerland.

METHODS

Data were collected by 15 trained pharmacy students in 15 Swiss community pharmacies. The medication history and the drug-interaction alerts of 600 patients who had >or=2 drugs on prescription were assessed, and the pharmacists in charge were interviewed about their management of drug-interaction alerts.

RESULTS

In the 15 pharmacies studied, the computer systems were programmed to flag only 'severe' drug interactions in four, 'severe or moderate' in six or 'severe, moderate or minor' in five pharmacies. The median frequency of drug-interaction alerts increased with decreasing default severity level from 0.5 to 40, respectively, to 76 per 40 patient visits and pharmacy. Because of these default settings, 277 (35 x 2%) of 787 potential drug-interaction alerts on new or repeated prescriptions were overridden by the computer systems. Only 256 (32 x 5%) of 787 potential drug interactions emerged from new prescriptions. The alert systems produced 656 alerts of which 146 were irrelevant because of multiple alerting of the same interaction or of drug combinations currently no longer taken. Of the 510 remaining relevant drug-interaction alerts, 289 (56 x 7%) were overridden by community pharmacists without any action taken. If the pharmacist took care of a patient's prescription him- or herself (as opposed to just controlling a prescription after a technician took care of the patient), fewer drug-interaction alerts were overridden by the pharmacist [Odds ratio (OR) 0 x 6, 95% confidence interval (CI) 0 x 42-0 x 98; P=0 x 042). Technical overrides (by default settings) and pharmacists' overrides together accounted for 71 x 9% (566 of 787 potential drug interactions). Of the remaining 211 interactions alerts, 87 (41 x 2%) were checked more closely by consulting the literature, contacting the prescribing physician or discussion with the patient. This led to 55 (63 x 2%) interventions (close monitoring, adjustment of dose or ingestion time, therapy stop or switching to alternative therapy). Determinants associated with action taken after an interaction alert were potential high severity (severe or moderate) (OR 3 x 34, 95% CI 1 x 77-6 x 31; P<0 x 001) and alert flagged for the first time (OR 3 x 76, 95% CI 1 x 98-7 x 14; P<0 x 001). All severe potential drug interactions (n=10) generated an alert and all caused an intervention.

CONCLUSIONS

Pharmacists override a substantial proportion of drug-interaction alerts of minor or moderate potential severity by ignoring them or by programming the system to only flag drug interactions of potentially high severity. More sophisticated systems with improved sensitivity and specificity are required. Until these become available, it is important to ensure that at least potentially severe drug interactions are not missed; a goal that seems to be largely achieved.

摘要

背景与目的

药物相互作用警报系统常用于社区药房,以识别潜在的药物相互作用。然而,根据软件默认设置,药剂师可能会忽略过多的警报。我们对瑞士社区药房处理药物相互作用警报的情况进行了探究。

方法

15名经过培训的药学专业学生在15家瑞士社区药房收集数据。评估了600名处方中使用≥2种药物的患者的用药史和药物相互作用警报,并就负责药剂师对药物相互作用警报的管理情况进行了访谈。

结果

在所研究的15家药房中,计算机系统被设置为仅标记4家药房中的“严重”药物相互作用、6家药房中的“严重或中度”药物相互作用或5家药房中的“严重、中度或轻度”药物相互作用。药物相互作用警报的中位数频率随着默认严重程度的降低而增加,分别从每40次患者就诊和药房0.5次增加到40次,再到76次。由于这些默认设置,计算机系统忽略了新处方或重复处方上787条潜在药物相互作用警报中的277条(35.2%)。787条潜在药物相互作用中只有256条(32.5%)来自新处方。警报系统发出了656条警报,其中146条因对同一相互作用或当前不再服用的药物组合多次发出警报而无关。在剩下的510条相关药物相互作用警报中,289条(56.7%)被社区药剂师忽略且未采取任何行动。如果药剂师亲自处理患者的处方(而不是在技术人员处理患者后仅审核处方),药剂师忽略的药物相互作用警报较少[比值比(OR)0.6,95%置信区间(CI)0.42 - 0.98;P = 0.042]。技术忽略(通过默认设置)和药剂师的忽略共同占787条潜在药物相互作用的71.9%(566条)。在剩下的211条相互作用警报中,87条(41.2%)通过查阅文献、联系开处方医生或与患者讨论进行了更仔细的检查。这导致了55条(63.2%)干预措施(密切监测、调整剂量或服药时间、停药或改用替代疗法)。与相互作用警报后采取行动相关的决定因素是潜在的高严重程度(严重或中度)(OR 3.34,95% CI 1.77 - 6.31;P < 0.001)和首次标记的警报(OR 3.76,95% CI l.98 - 7.14;P < 0.001)。所有严重的潜在药物相互作用(n = 10)都产生了警报,并且都导致了干预措施。

结论

药剂师通过忽略或设置系统仅标记潜在高严重程度的药物相互作用,忽略了很大一部分轻度或中度潜在严重程度的药物相互作用警报。需要更复杂、灵敏度和特异性更高的系统。在这些系统可用之前,重要的是要确保至少不遗漏潜在严重的药物相互作用;这一目标似乎在很大程度上已经实现。

相似文献

1
Management of drug-interaction alerts in community pharmacies.社区药房中药物相互作用警报的管理。
J Clin Pharm Ther. 2007 Apr;32(2):133-42. doi: 10.1111/j.1365-2710.2007.00802.x.
2
Prevalence and patient awareness of selected potential drug interactions with self-medication.自我药疗中特定潜在药物相互作用的发生率及患者知晓情况。
J Clin Pharm Ther. 2007 Apr;32(2):149-59. doi: 10.1111/j.1365-2710.2007.00809.x.
3
Preventing drug interactions by online prescription screening in community pharmacies and medical practices.通过社区药房和医疗机构的在线处方筛查预防药物相互作用。
Clin Pharmacol Ther. 2001 Apr;69(4):260-5. doi: 10.1067/mcp.2001.114228.
4
Compliance with national guidelines for the management of drug-drug interactions in Dutch community pharmacies.荷兰社区药房对国家药物相互作用管理指南的遵循情况。
Ann Pharmacother. 2007 Dec;41(12):2024-31. doi: 10.1345/aph.1K240. Epub 2007 Oct 30.
5
Pharmacist workload and pharmacy characteristics associated with the dispensing of potentially clinically important drug-drug interactions.与潜在具有临床重要性的药物相互作用配药相关的药剂师工作量及药房特征
Med Care. 2007 May;45(5):456-62. doi: 10.1097/01.mlr.0000257839.83765.07.
6
Physicians' decisions to override computerized drug alerts in primary care.基层医疗中医生对计算机化药物警报的忽视决策。
Arch Intern Med. 2003 Nov 24;163(21):2625-31. doi: 10.1001/archinte.163.21.2625.
7
Survey of drug-related problems identified by community pharmacies.社区药房发现的药物相关问题调查。
Ann Pharmacother. 2007 Nov;41(11):1825-32. doi: 10.1345/aph.1K207. Epub 2007 Oct 9.
8
Overrides of medication alerts in ambulatory care.门诊护理中药物警报的覆盖情况。
Arch Intern Med. 2009 Feb 9;169(3):305-11. doi: 10.1001/archinternmed.2008.551.
9
Assessing the value of electronic prescribing in ambulatory care: a focus group study.评估门诊医疗中电子处方的价值:一项焦点小组研究。
Int J Med Inform. 2009 Sep;78(9):571-8. doi: 10.1016/j.ijmedinf.2009.03.007. Epub 2009 Apr 22.
10
Drug safety alert generation and overriding in a large Dutch university medical centre.荷兰一家大型大学医学中心的药物安全警报生成与覆盖
Pharmacoepidemiol Drug Saf. 2009 Oct;18(10):941-7. doi: 10.1002/pds.1800.

引用本文的文献

1
Co-prescription of metoprolol and CYP2D6-inhibiting antidepressants before and after implementation of an optimized drug interaction database in Norway.挪威实施优化药物相互作用数据库前后美托洛尔与 CYP2D6 抑制性抗抑郁药的联合处方。
Eur J Clin Pharmacol. 2022 Oct;78(10):1623-1632. doi: 10.1007/s00228-022-03364-5. Epub 2022 Jul 25.
2
Determination of Potential Drug-Drug Interactions Using Various Software Programs in a Community Pharmacy Setting.在社区药房环境中使用各种软件程序确定潜在的药物相互作用。
Turk J Pharm Sci. 2019 Mar;16(1):14-19. doi: 10.4274/tjps.30932. Epub 2018 Dec 31.
3
Evaluation of community pharmacists' knowledge about drug-drug interaction in Central Saudi Arabia.
沙特阿拉伯中部地区社区药剂师对药物相互作用知识的评估。
Saudi Pharm J. 2019 May;27(4):463-466. doi: 10.1016/j.jsps.2019.01.008. Epub 2019 Jan 7.
4
Identifying Core Content for Electrocardiogram Instruction in Doctor of Pharmacy Curricula.确定药学博士课程中心电图教学的核心内容。
Am J Pharm Educ. 2018 Dec;82(10):7009. doi: 10.5688/ajpe7009.
5
Relationship between drug interactions and drug-related negative clinical outcomes.药物相互作用与药物相关不良临床结局之间的关系。
Pharm Pract (Granada). 2009 Jan;7(1):34-9. doi: 10.4321/s1886-36552009000100005. Epub 2009 Mar 15.
6
Frequency of use of QT-interval prolonging drugs in psychiatry in Belgium.比利时精神病学中 QT 间期延长药物的使用频率。
Int J Clin Pharm. 2014 Aug;36(4):757-65. doi: 10.1007/s11096-014-9953-6. Epub 2014 May 8.
7
Identification and evaluation of drug-supplement interactions in Hungarian hospital patients.识别和评估匈牙利住院患者的药物-保健品相互作用。
Int J Clin Pharm. 2014 Apr;36(2):451-9. doi: 10.1007/s11096-014-9923-z. Epub 2014 Feb 23.
8
The evidence for the effectiveness of safety alerts in electronic patient medication record systems at the point of pharmacy order entry: a systematic review.电子患者用药记录系统中在药房医嘱输入点的安全警报的有效性的证据:系统评价。
BMC Med Inform Decis Mak. 2013 Jul 1;13:69. doi: 10.1186/1472-6947-13-69.
9
Pharmaceutical interventions on prescription problems in a Danish pharmacy setting.丹麦药房环境下的处方问题药物干预。
Int J Clin Pharm. 2011 Dec;33(6):1019-27. doi: 10.1007/s11096-011-9580-4. Epub 2011 Nov 15.
10
Detection and prevention of prescriptions with excessive doses in electronic prescribing systems.电子处方系统中过量处方的检测与预防
Eur J Clin Pharmacol. 2007 Dec;63(12):1185-92. doi: 10.1007/s00228-007-0370-9. Epub 2007 Sep 5.