Novel data visualization method to measure alert efficiency in computerized physician order entry (CPOE) system

IF 3.4 3区 医学 Q1 HEALTH POLICY & SERVICES Health Policy and Technology Pub Date : 2024-06-01 DOI:10.1016/j.hlpt.2024.100852
Shuo-Chen Chien , Chia-Hui Chien , Chun-You Chen , Yen-Po (Harvey) Chin , Po-Han Chien , Chun-Kung Hsu , Hsuan-Chia Yang , Yu-Chuan (Jack) Li
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Abstract

Objectives

To introduce a novel visualization technique for evaluating the efficacy of clinical decision support system (CDSS) alerts as perceived by physicians and to differentiate between various alert categories for optimization.

Methods

We developed a visualization method, which segments into four distinct zones: Appropriate (+/+), Over-frequent yet Effective (−/+), Potentially Problematic (−/−), and Less Effective but Acceptably Frequent (+/−). Alerts from a 908-bed academic medical center in Northern Taiwan were collected over two years and classified using this technique, along with three perspectives: Safety, Completeness, and Response.

Results

We collected the viewpoints of 72 clinical physicians on the system's top 20 most frequent alerts. The proposed visualization technique offers a user-centric, adaptable method for assessing CDSS alerts. Roughly five alerts were categorized as Potentially Problematic, whereas another five were deemed Appropriate. Intriguingly, certain alerts, while not beneficial for patient safety, were found to assist physicians in completing clinical workflows.

Conclusions

This approach, emphasizing visual clarity and adaptability, diverges from traditional methods that lean heavily on expert opinions or statistics. It paves the way for diverse assessment perspectives, furnishing healthcare institutions with a valuable tool to improve CDSS alert systems, ensuring a harmonious balance between user efficiency and patient safety.

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测量计算机化医嘱输入系统(CPOE)中警报效率的新型数据可视化方法
目的介绍一种新颖的可视化技术,用于评估医生感知到的临床决策支持系统(CDSS)警报的有效性,并区分各种警报类别以进行优化:我们开发了一种可视化方法,将警报划分为四个不同的区域:适当(+/+)、过于频繁但有效(-/+)、有潜在问题(-/-)和不太有效但可接受的频率(+/-)。在两年的时间里,我们收集了台湾北部一家拥有 908 张病床的学术医疗中心的警报,并使用这种技术和三个视角对警报进行了分类:结果我们收集了 72 位临床医师对系统中最常见的前 20 个警报的看法。所提出的可视化技术为评估 CDSS 警报提供了一种以用户为中心、适应性强的方法。大约有五个警报被归类为潜在问题,而另外五个被认为是适当的。耐人寻味的是,某些警报虽然不利于患者安全,但却有助于医生完成临床工作流程。它为不同的评估视角铺平了道路,为医疗机构改进 CDSS 警报系统提供了宝贵的工具,确保了用户效率和患者安全之间的和谐平衡。
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来源期刊
Health Policy and Technology
Health Policy and Technology Medicine-Health Policy
CiteScore
9.20
自引率
3.30%
发文量
78
审稿时长
88 days
期刊介绍: Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments. HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology. Topics covered by HPT will include: - Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems - Cross-national comparisons on health policy using evidence-based approaches - National studies on health policy to determine the outcomes of technology-driven initiatives - Cross-border eHealth including health tourism - The digital divide in mobility, access and affordability of healthcare - Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies - Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies - Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making - Stakeholder engagement with health technologies (clinical and patient/citizen buy-in) - Regulation and health economics
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