Development and Implementation of an e-Trigger Tool for Adverse Drug Events in a Swiss University Hospital.

IF 2.2 Q2 HEALTH CARE SCIENCES & SERVICES Drug, Healthcare and Patient Safety Pub Date : 2021-12-24 eCollection Date: 2021-01-01 DOI:10.2147/DHPS.S334987
Amina El Saghir, Georgios Dimitriou, Miriam Scholer, Ioanna Istampoulouoglou, Patrick Heinrich, Klaus Baumgartl, René Schwendimann, Stefano Bassetti, Anne Leuppi-Taegtmeyer
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Abstract

Purpose: The purpose of the study was to develop and implement an institution-specific trigger tool based on the Institute for Healthcare Improvement medication module trigger tool (IHI MMTT) in order to detect and monitor ADEs.

Methods: We performed an investigator-driven, single-center study using retrospective and prospective patient data to develop ("development phase") and implement ("implementation phase") an efficient, institution-specific trigger tool based on the IHI MMTT. Complete medical data from 1008 patients hospitalized in 2018 were used in the development phase. ADEs were identified by chart review. The performance of two versions of the tool was assessed by comparing their sensitivities and specificities. Tool A employed only digitally extracted triggers ("e-trigger-tool") while Tool B employed an additional manually extracted trigger. The superior tool - taking efficiency into account - was applied prospectively to 19-22 randomly chosen charts per month for 26 months during the implementation phase.

Results: In the development phase, 189 (19%) patients had ≥1 ADE (total 277 ADEs). The time needed to identify these ADEs was 15 minutes/chart. A total of 203 patients had ≥1 trigger (total 273 triggers - Tool B). The sensitivities and specificities of Tools A and B were 0.41 and 0.86, and 0.43 and 0.86, respectively. Tool A was more time-efficient than Tool B (4 vs 9 minutes/chart) and was therefore used in the implementation phase. During the 26-month implementation phase, 22 patients experienced trigger-identified ADEs and 529 did not. The median number of ADEs per 1000 patient days was 6 (range 0-13). Patients with at least one ADE had a mean hospital stay of 22.3 ± 19.7 days, compared to 8.0 ± 7.6 days for those without an ADE (p = 2.7×10-14).

Conclusion: We developed and implemented an e-trigger tool that was specific and moderately sensitive, gave consistent results and required minimal resources.

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在瑞士一家大学医院开发并实施药物不良事件电子触发工具。
目的:本研究的目的是在美国医疗保健改进研究所药物模块触发工具(IHI MMTT)的基础上开发和实施一种特定机构的触发工具,以检测和监控 ADEs:我们利用回顾性和前瞻性患者数据开展了一项由研究者驱动的单中心研究,以开发("开发阶段")和实施("实施阶段")基于 IHI MMTT 的高效的特定机构触发工具。开发阶段使用了 2018 年住院的 1008 名患者的完整医疗数据。通过病历审查确定了 ADE。通过比较两个版本工具的敏感性和特异性,对其性能进行了评估。工具 A 仅采用了数字提取的触发器("电子触发器工具"),而工具 B 则采用了额外的人工提取触发器。在实施阶段的 26 个月中,考虑到效率问题,优选工具每月对随机选择的 19-22 张病历进行前瞻性应用:结果:在开发阶段,189 名(19%)患者出现了≥1 次 ADE(共 277 次 ADE)。识别这些 ADE 所需的时间为 15 分钟/图表。共有 203 名患者的触发因素≥1 个(触发因素总数为 273 个 - 工具 B)。工具 A 和工具 B 的敏感性和特异性分别为 0.41 和 0.86,以及 0.43 和 0.86。工具 A 比工具 B 更省时(4 分钟对 9 分钟/图表),因此在实施阶段被采用。在为期 26 个月的实施阶段,22 名患者发生了触发识别的 ADE,529 名患者没有发生。每 1000 个患者日的 ADE 中位数为 6(范围为 0-13)。至少发生一次 ADE 的患者平均住院时间为 22.3 ± 19.7 天,而未发生 ADE 的患者平均住院时间为 8.0 ± 7.6 天(P = 2.7×10-14):我们开发并实施了一种电子触发工具,该工具具有特异性和中等灵敏度,可提供一致的结果,且所需资源极少。
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来源期刊
Drug, Healthcare and Patient Safety
Drug, Healthcare and Patient Safety HEALTH CARE SCIENCES & SERVICES-
CiteScore
4.10
自引率
0.00%
发文量
24
审稿时长
16 weeks
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