• 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

利用临床决策支持系统决策日志数据进行决策发现，以支持护士的决策过程。

Decision discovery using clinical decision support system decision log data for supporting the nurse decision-making process.

机构信息

Digital Ethics, HU University of Applied Sciences Utrecht, Heidelberglaan 15, Utrecht, 3584 CS, The Netherlands.

Open University of the Netherlands, Valkenburgerweg 177, Heerlen, 6419 AT, The Netherlands.

出版信息

BMC Med Inform Decis Mak. 2024 Apr 18;24(1):100. doi: 10.1186/s12911-024-02486-3.

DOI:10.1186/s12911-024-02486-3
PMID:38637792
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11025262/
Abstract

BACKGROUND

Decision-making in healthcare is increasingly complex; notably in hospital environments where the information density is high, e.g., emergency departments, oncology departments, and psychiatry departments. This study aims to discover decisions from logged data to improve the decision-making process.

METHODS

The Design Science Research Methodology (DSRM) was chosen to design an artifact (algorithm) for the discovery and visualization of decisions. The DSRM's different activities are explained, from the definition of the problem to the evaluation of the artifact. During the design and development activities, the algorithm itself is created. During the demonstration and evaluation activities, the algorithm was tested with an authentic synthetic dataset.

RESULTS

The results show the design and simulation of an algorithm for the discovery and visualization of decisions. A fuzzy classifier algorithm was adapted for (1) discovering decisions from a decision log and (2) visualizing the decisions using the Decision Model and Notation standard.

CONCLUSIONS

In this paper, we show that decisions can be discovered from a decision log and visualized for the improvement of the decision-making process of healthcare professionals or to support the periodic evaluation of protocols and guidelines.

摘要

背景

医疗保健领域的决策变得越来越复杂；尤其是在信息密度高的医院环境中，例如急诊科、肿瘤科和精神科。本研究旨在从日志数据中发现决策，以改善决策过程。

方法

选择设计科学研究方法论（DSRM）来设计用于发现和可视化决策的人工制品（算法）。解释了 DSRM 的不同活动，从问题的定义到人工制品的评估。在设计和开发活动期间，创建了算法本身。在演示和评估活动期间，使用真实的合成数据集测试了算法。

结果

结果显示了用于发现和可视化决策的算法的设计和模拟。模糊分类器算法被用于（1）从决策日志中发现决策，以及（2）使用决策模型和符号标准可视化决策。

结论

在本文中，我们表明可以从决策日志中发现决策，并将其可视化，以改善医疗保健专业人员的决策过程，或支持协议和指南的定期评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/37107639d612/12911_2024_2486_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/2a6c57f1c2d2/12911_2024_2486_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/456041c24d0b/12911_2024_2486_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/c658a7275970/12911_2024_2486_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/699026ffe997/12911_2024_2486_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/0b58ba4b5a82/12911_2024_2486_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/d95c181e525c/12911_2024_2486_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/c883c6efd597/12911_2024_2486_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/69e1e0949233/12911_2024_2486_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/57028b22d2b5/12911_2024_2486_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/d8098fbdcf87/12911_2024_2486_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/95d415786af9/12911_2024_2486_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/ae5812985915/12911_2024_2486_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/c06eb3af45ca/12911_2024_2486_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/7ecc3c55925d/12911_2024_2486_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/ecf718c7ead5/12911_2024_2486_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/37107639d612/12911_2024_2486_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/2a6c57f1c2d2/12911_2024_2486_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/456041c24d0b/12911_2024_2486_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/c658a7275970/12911_2024_2486_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/699026ffe997/12911_2024_2486_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/0b58ba4b5a82/12911_2024_2486_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/d95c181e525c/12911_2024_2486_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/c883c6efd597/12911_2024_2486_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/69e1e0949233/12911_2024_2486_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/57028b22d2b5/12911_2024_2486_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/d8098fbdcf87/12911_2024_2486_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/95d415786af9/12911_2024_2486_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/ae5812985915/12911_2024_2486_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/c06eb3af45ca/12911_2024_2486_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/7ecc3c55925d/12911_2024_2486_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/ecf718c7ead5/12911_2024_2486_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4aa/11025262/37107639d612/12911_2024_2486_Fig16_HTML.jpg

相似文献

1
Decision discovery using clinical decision support system decision log data for supporting the nurse decision-making process.利用临床决策支持系统决策日志数据进行决策发现，以支持护士的决策过程。
BMC Med Inform Decis Mak. 2024 Apr 18;24(1):100. doi: 10.1186/s12911-024-02486-3.
2
CDSS-RM: a clinical decision support system reference model.CDSS-RM：临床决策支持系统参考模型。
BMC Med Res Methodol. 2018 Nov 16;18(1):137. doi: 10.1186/s12874-018-0587-6.
3
The effects of computerised decision support systems on nursing and allied health professional performance and patient outcomes: a systematic review and user contextualisation.计算机化决策支持系统对护理及相关健康专业人员绩效和患者结局的影响：一项系统综述与用户情境化分析
Health Soc Care Deliv Res. 2024 Oct;12(40):1-93. doi: 10.3310/GRNM5147.
4
Implementing an online pharmaceutical service using design science research.运用设计科学研究实施在线药品服务。
BMC Med Inform Decis Mak. 2017 Mar 27;17(1):31. doi: 10.1186/s12911-017-0428-2.
5
How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments.如何提高用于临床决策支持系统的生命体征数据质量？一项针对瑞典九个急诊科的定性研究。
BMC Med Inform Decis Mak. 2016 Jun 4;16:61. doi: 10.1186/s12911-016-0305-4.
6
Clinical Decision Support Systems for Triage in the Emergency Department using Intelligent Systems: a Review.基于智能系统的急诊科分诊临床决策支持系统：综述
Artif Intell Med. 2020 Jan;102:101762. doi: 10.1016/j.artmed.2019.101762. Epub 2019 Nov 17.
7
A novel bagging C4.5 algorithm based on wrapper feature selection for supporting wise clinical decision making.一种基于包装特征选择的新型 C4.5 装袋算法，用于支持明智的临床决策。
J Biomed Inform. 2018 Feb;78:144-155. doi: 10.1016/j.jbi.2017.11.005. Epub 2017 Nov 11.
8
Application of human factors to improve usability of clinical decision support for diagnostic decision-making: a scenario-based simulation study.将人为因素应用于改善临床决策支持的可用性以用于诊断决策：基于场景的模拟研究。
BMJ Qual Saf. 2020 Apr;29(4):329-340. doi: 10.1136/bmjqs-2019-009857. Epub 2019 Nov 27.
9
Development of a Knowledge Base for Chronic Wound Management Using the Decision Model & Notation.利用决策模型与符号学开发慢性伤口管理知识库
Stud Health Technol Inform. 2022 Aug 17;296:1-8. doi: 10.3233/SHTI220797.
10
Shared Decision-Support Tools in Hospital Emergency Departments: A Systematic Review.医院急诊科的共享决策支持工具：一项系统评价。
J Emerg Nurs. 2019 Jul;45(4):386-393. doi: 10.1016/j.jen.2019.01.002. Epub 2019 Feb 25.

本文引用的文献

1
Factors Influencing Clinician Trust in Predictive Clinical Decision Support Systems for In-Hospital Deterioration: Qualitative Descriptive Study.影响临床医生对院内病情恶化预测性临床决策支持系统信任度的因素：定性描述性研究
JMIR Hum Factors. 2022 May 12;9(2):e33960. doi: 10.2196/33960.
2
Transforming healthcare with big data analytics and artificial intelligence: A systematic mapping study.利用大数据分析和人工智能改变医疗保健：系统映射研究。
J Biomed Inform. 2019 Dec;100:103311. doi: 10.1016/j.jbi.2019.103311. Epub 2019 Oct 17.
3
Clinical Requirements of Future Patient Monitoring in the Intensive Care Unit: Qualitative Study.
重症监护病房未来患者监测的临床需求：定性研究
JMIR Med Inform. 2019 Apr 30;7(2):e13064. doi: 10.2196/13064.
4
A call to alarms: Current state and future directions in the battle against alarm fatigue.敲响警钟：对抗警报疲劳的现状与未来方向
J Electrocardiol. 2018 Nov-Dec;51(6S):S44-S48. doi: 10.1016/j.jelectrocard.2018.07.024. Epub 2018 Jul 29.
5
Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature.决定电子健康干预成败的因素：文献系统综述
J Med Internet Res. 2018 May 1;20(5):e10235. doi: 10.2196/10235.
6
Decision-making under pressure: medical errors in uncertain and dynamic environments.压力下的决策：不确定和动态环境中的医疗差错
Aust Health Rev. 2018 Aug;42(4):395-402. doi: 10.1071/AH16088.
7
Validation workflow for a clinical Bayesian network model in multidisciplinary decision making in head and neck oncology treatment.头颈部肿瘤治疗中多学科决策的临床贝叶斯网络模型的验证工作流程。
Int J Comput Assist Radiol Surg. 2017 Nov;12(11):1959-1970. doi: 10.1007/s11548-017-1531-7. Epub 2017 Feb 15.
8
Shared Decision Making With Vulnerable Populations in the Emergency Department.急诊科中与弱势群体的共同决策
Acad Emerg Med. 2016 Dec;23(12):1410-1416. doi: 10.1111/acem.13134.
9
Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.用于医疗保健决策的多标准决策分析——简介：ISPOR多标准决策分析新兴良好实践工作组报告1
Value Health. 2016 Jan;19(1):1-13. doi: 10.1016/j.jval.2015.12.003. Epub 2016 Jan 8.
10
Alarm fatigue: impacts on patient safety.警报疲劳：对患者安全的影响。
Curr Opin Anaesthesiol. 2015 Dec;28(6):685-90. doi: 10.1097/ACO.0000000000000260.