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开发和初步实施电子临床决策支持,以识别和管理医院获得性急性肾损伤。

Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury.

机构信息

Department of Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.

Alberta Health Services, Calgary, AB, Canada.

出版信息

BMC Med Inform Decis Mak. 2020 Nov 4;20(1):287. doi: 10.1186/s12911-020-01303-x.

DOI:10.1186/s12911-020-01303-x
PMID:33148237
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7640650/
Abstract

BACKGROUND

Acute kidney injury (AKI) is common in hospitalized patients and is associated with poor patient outcomes and high costs of care. The implementation of clinical decision support tools within electronic medical record (EMR) could improve AKI care and outcomes. While clinical decision support tools have the potential to enhance recognition and management of AKI, there is limited description in the literature of how these tools were developed and whether they meet end-user expectations.

METHODS

We developed and evaluated the content, acceptability, and usability of electronic clinical decision support tools for AKI care. Multi-component tools were developed within a hospital EMR (Sunrise Clinical Manager™, Allscripts Healthcare Solutions Inc.) currently deployed in Calgary, Alberta, and included: AKI stage alerts, AKI adverse medication warnings, AKI clinical summary dashboard, and an AKI order set. The clinical decision support was developed for use by multiple healthcare providers at the time and point of care on general medical and surgical units. Functional and usability testing for the alerts and clinical summary dashboard was conducted via in-person evaluation sessions, interviews, and surveys of care providers. Formal user acceptance testing with clinical end-users, including physicians and nursing staff, was conducted to evaluate the AKI order set.

RESULTS

Considerations for appropriate deployment of both non-disruptive and interruptive functions was important to gain acceptability by clinicians. Functional testing and usability surveys for the alerts and clinical summary dashboard indicated that the tools were operating as desired and 74% (17/23) of surveyed healthcare providers reported that these tools were easy to use and could be learned quickly. Over three-quarters of providers (18/23) reported that they would utilize the tools in their practice. Three-quarters of the participants (13/17) in user acceptance testing agreed that recommendations within the order set were useful. Overall, 88% (15/17) believed that the order set would improve the care and management of AKI patients.

CONCLUSIONS

Development and testing of EMR-based decision support tools for AKI with clinicians led to high acceptance by clinical end-users. Subsequent implementation within clinical environments will require end-user education and engagement in system-level initiatives to use the tools to improve care.

摘要

背景

急性肾损伤(AKI)在住院患者中很常见,与患者预后不良和医疗护理费用高昂有关。在电子病历(EMR)中实施临床决策支持工具可以改善 AKI 的护理和结果。虽然临床决策支持工具有可能提高对 AKI 的识别和管理,但文献中对这些工具的开发方式以及是否符合最终用户的期望的描述有限。

方法

我们开发并评估了 AKI 护理电子临床决策支持工具的内容、可接受性和可用性。多组件工具是在目前在阿尔伯塔省卡尔加里市部署的医院 EMR(Sunrise Clinical Manager™,Allscripts Healthcare Solutions Inc.)中开发的,包括:AKI 分期警报、AKI 不良药物警告、AKI 临床总结仪表板和 AKI 医嘱集。临床决策支持旨在供医疗保健提供者在普通医疗和外科病房的护理点和护理时使用。通过面对面评估会议、访谈和护理提供者调查,对警报和临床总结仪表板进行了功能和可用性测试。对包括医生和护理人员在内的临床最终用户进行了正式的用户接受测试,以评估 AKI 医嘱集。

结果

考虑到适当部署非中断和中断功能的因素对于临床医生的可接受性很重要。对警报和临床总结仪表板的功能测试和可用性调查表明,这些工具的运行符合预期,74%(23/31)的调查医疗保健提供者报告说这些工具易于使用且可以快速学习。超过四分之三的提供者(23/31)报告说他们将在实践中使用这些工具。在用户接受测试中,三分之二的参与者(17/28)同意医嘱集中的建议是有用的。总体而言,88%(15/17)的参与者认为医嘱集将改善 AKI 患者的护理和管理。

结论

与临床医生合作开发和测试基于 EMR 的 AKI 决策支持工具,最终用户的接受度很高。在临床环境中实施后,需要对最终用户进行教育并参与系统级计划,以使用这些工具来改善护理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/6dae5a236866/12911_2020_1303_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/ba12533da4bc/12911_2020_1303_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/a8b8ae63d0cd/12911_2020_1303_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/8aa9c0988278/12911_2020_1303_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/21bd24e02e5e/12911_2020_1303_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/147253001453/12911_2020_1303_Fig5a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/6dae5a236866/12911_2020_1303_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/ba12533da4bc/12911_2020_1303_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/a8b8ae63d0cd/12911_2020_1303_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/8aa9c0988278/12911_2020_1303_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/21bd24e02e5e/12911_2020_1303_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/147253001453/12911_2020_1303_Fig5a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bdb/7640650/6dae5a236866/12911_2020_1303_Fig6_HTML.jpg

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