Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
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DOI：
10.1016/j.hjdsi.2021.100598
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发表时间：
2022-03
期刊：
影响因子：
--
通讯作者：
Patterson BW
中科院分区：
文献类型：
--
作者：
Jacobsohn GC;Leaf M;Liao F;Maru AP;Engstrom CJ;Salwei ME;Pankratz GT;Eastman A;Carayon P;Wiegmann DA;Galang JS;Smith MA;Shah MN;Patterson BW
在每年寻求与跌倒相关的紧急护理的300万老年人中，近三分之一的人在过去6个月内去过急诊科（艾德）。艾德提供者有很大的机会在这些初次就诊时为患者提供跌倒预防服务，但缺乏识别高风险患者的可行工具。由于艾德工作人员/提供者的负担和缺乏工作流程集成，现有的跌倒筛查工具采用得不好。为了解决这个问题，我们开发了一个自动化的临床决策支持（CDS）系统，用于识别和转介老年艾德患者在未来的福尔斯的风险。我们聘请了一个跨学科的设计团队（艾德提供者、健康服务研究人员、信息技术/预测分析专业人员和门诊福尔斯Clinic工作人员），共同开发一个成功满足用户需求并无缝集成到现有艾德工作流程中的系统。我们的快速周期开发和评估过程采用了以人为本的设计、实施科学和患者体验策略的新颖组合，促进了CDS工具和干预实施策略的同时设计。这包括定义系统需求，系统地识别和解决可用性问题，评估实施的障碍和促进因素（例如，数据可访问性、缺乏时间、高患者量、预约可用性），以及改进出院时与转诊患者沟通的协议。艾德医生、护士和患者利益相关者也通过在线调查和用户测试参与其中。成功的CDS设计和实施需要将多种新技术和流程整合到现有的工作流程中，从一开始就需要跨学科的合作。通过使用这种迭代方法，我们能够设计和实现满足所有项目目标的干预措施。临床-IT-研究合作伙伴关系中使用的流程可以应用于其他用例，包括自动风险分层，CDS开发和EHR促进的护理协调。
Of the 3 million older adults seeking fall-related emergency care each year, nearly one-third visited the Emergency Department (ED) in the previous 6 months. ED providers have a great opportunity to refer patients for fall prevention services at these initial visits, but lack feasible tools for identifying those at highest-risk. Existing fall screening tools have been poorly adopted due to ED staff/provider burden and lack of workflow integration. To address this, we developed an automated clinical decision support (CDS) system for identifying and referring older adult ED patients at risk of future falls. We engaged an interdisciplinary design team (ED providers, health services researchers, information technology/predictive analytics professionals, and outpatient Falls Clinic staff) to collaboratively develop a system that successfully met user requirements and integrated seamlessly into existing ED workflows. Our rapid-cycle development and evaluation process employed a novel combination of human-centered design, implementation science, and patient experience strategies, facilitating simultaneous design of the CDS tool and intervention implementation strategies. This included defining system requirements, systematically identifying and resolving usability problems, assessing barriers and facilitators to implementation (e.g., data accessibility, lack of time, high patient volumes, appointment availability) from multiple vantage points, and refining protocols for communicating with referred patients at discharge. ED physician, nurse, and patient stakeholders were also engaged through online surveys and user testing. Successful CDS design and implementation required integration of multiple new technologies and processes into existing workflows, necessitating interdisciplinary collaboration from the onset. By using this iterative approach, we were able to design and implement an intervention meeting all project goals. Processes used in this Clinical-IT-Research partnership can be applied to other use cases involving automated risk-stratification, CDS development, and EHR-facilitated care coordination.
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影响因子：
12.7
作者：
Glasgow, RE;Vogt, TM;Boles, SM
通讯作者：
Boles, SM
影响因子：
6.3
作者：
Florence CS;Bergen G;Atherly A;Burns E;Stevens J;Drake C
通讯作者：
Drake C
在急诊科护理的一集之后，预测老年跌倒：系统评价。
DOI：
10.1111/acem.12488
发表时间：
2014-10
期刊：
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
影响因子：
--
作者：
Carpenter CR;Avidan MS;Wildes T;Stark S;Fowler SA;Lo AX
通讯作者：
Lo AX
影响因子：
3.6
作者：
Dopp, Alex R.;Parisi, Kathryn E.;Lyon, Aaron R.
通讯作者：
Lyon, Aaron R.
影响因子：
3.1
作者：
Davenport, Kathleen;Cameron, Amy;Liu, Shan W.
通讯作者：
Liu, Shan W.