• 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

将商业智能应用于计算机断层扫描中碘造影剂的使用。

Business intelligence applied to the consumption of iodinated contrast agents in computed tomography scans.

机构信息

Graduate Program in Information Technology and Healthcare Management, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil.

出版信息

BMC Med Inform Decis Mak. 2022 Mar 25;22(1):76. doi: 10.1186/s12911-022-01814-9.

DOI:10.1186/s12911-022-01814-9
PMID:35337316
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8957133/
Abstract

BACKGROUND

The management of the use of iodinated contrast agents (ICA) in the computed tomography (CT) has clinical and financial impacts; however, the approaches in the current research setting have limitations with regard to their exploration of the theme. This work describes the application of the stages of a process of business intelligence (BI), from the formulation of business questions, the building of a research database, and the adaptation of a multidimensional model, to the creation of dashboards to give support to the decision-making process in a hospital. This research aims to apply and document a BI process that provides support to the decision making of managers, so the use of ICA can be better managed, allowing for the identification of situations in which the material was wasted using a study applied to the hospital field.

METHODS

An applied exploratory research with a quantitative approach in a database made up by 24 variables and 35,388 records extracted from the RIS (Radiology Information System) that is used by the General Hospital of Porto Alegre-HCPA. The software used, supplied by AGFA Healthcare, were the Qdoc system (version 6.2.0) and the Impax BI (Version 11.1.1) for, respectively, data entry and data exploration. At the end of the process, a total of 48 variables was considered.

RESULTS

The BI process applied allowed for the identification of situations in which ICA was being wasted during the operationalization of the volume/mass ratio of the agent injected in the patient. It also offered the necessary substantiation for the managers to formulate plans, actions, and controls associated to the use of the material. This work made it possible to diminish in 15.65% the total consumption of ICA injected in the patients who underwent the CTAB1 exam (full CT scan of the abdomen), with a projected economy of US$ 10,039.95, for the performance of this exam from 2020 on. The measuring of the impact and the relevance of the process was 99.6% positive, according to the evaluation of the managers.

CONCLUSIONS

This research generated clinical and financial benefits for the HCPA, a positive evaluation by the managers and the generation of new knowledge, which can be shared with other public or private health organizations.

摘要

背景

在计算机断层扫描(CT)中使用碘造影剂(ICA)的管理具有临床和财务影响;然而,当前研究环境中的方法在探索主题方面存在局限性。本工作描述了业务智能(BI)过程的各个阶段的应用,从制定业务问题、构建研究数据库以及适应多维模型,到创建仪表板,以支持医院的决策过程。本研究旨在应用和记录 BI 流程,为管理者的决策提供支持,以便更好地管理 ICA 的使用,从而通过应用于医院领域的研究来识别浪费材料的情况。

方法

这是一项应用探索性研究,采用定量方法,基于从波尔图阿雷格里港总医院使用的 RIS(放射信息系统)中提取的 24 个变量和 35388 条记录组成的数据库。使用的软件由 AGFA Healthcare 提供,分别是 Qdoc 系统(版本 6.2.0)和 Impax BI(版本 11.1.1),用于数据输入和数据探索。在流程结束时,共考虑了 48 个变量。

结果

应用 BI 流程可以识别在操作注入患者的 ICA 时浪费情况,并为管理者制定与材料使用相关的计划、行动和控制提供必要的依据。这项工作使 CTAB1 检查(腹部全面 CT 扫描)中患者接受的 ICA 总注射量减少了 15.65%,预计 2020 年以来,该检查的节省费用为 10039.95 美元。根据管理者的评估,该流程的影响和相关性的测量结果为 99.6%为正。

结论

本研究为 HCPA 带来了临床和经济效益,得到了管理者的积极评价,并产生了新的知识,可以与其他公共或私人卫生组织共享。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/3be2741c4c2f/12911_2022_1814_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/e57592e0f238/12911_2022_1814_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/fba7aa64ecb6/12911_2022_1814_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/958034f27f80/12911_2022_1814_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/fd3aa8b82083/12911_2022_1814_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/1f117d7d3df6/12911_2022_1814_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/ad93fa847227/12911_2022_1814_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/050319421a5c/12911_2022_1814_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/7a18690c2b2d/12911_2022_1814_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/8b131a7a60ec/12911_2022_1814_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/3be2741c4c2f/12911_2022_1814_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/e57592e0f238/12911_2022_1814_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/fba7aa64ecb6/12911_2022_1814_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/958034f27f80/12911_2022_1814_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/fd3aa8b82083/12911_2022_1814_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/1f117d7d3df6/12911_2022_1814_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/ad93fa847227/12911_2022_1814_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/050319421a5c/12911_2022_1814_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/7a18690c2b2d/12911_2022_1814_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/8b131a7a60ec/12911_2022_1814_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94de/8957133/3be2741c4c2f/12911_2022_1814_Fig10_HTML.jpg

相似文献

1
Business intelligence applied to the consumption of iodinated contrast agents in computed tomography scans.将商业智能应用于计算机断层扫描中碘造影剂的使用。
BMC Med Inform Decis Mak. 2022 Mar 25;22(1):76. doi: 10.1186/s12911-022-01814-9.
2
Business intelligence tools for radiology: creating a prototype model using open-source tools.放射科用商业智能工具:使用开源工具创建原型模型。
J Digit Imaging. 2010 Apr;23(2):133-41. doi: 10.1007/s10278-008-9167-3. Epub 2008 Nov 15.
3
Business intelligence for the radiologist: making your data work for you.放射科医生的商业智能:让您的数据为您服务。
J Am Coll Radiol. 2014 Dec;11(12 Pt B):1238-40. doi: 10.1016/j.jacr.2014.09.008. Epub 2014 Dec 1.
4
Business intelligence and the leverage of information in healthcare organizations from a managerial perspective: a systematic literature review and research agenda.从管理视角看商业智能与医疗组织信息杠杆作用:系统文献回顾与研究议程
J Health Organ Manag. 2024 Mar 29;ahead-of-print(ahead-of-print). doi: 10.1108/JHOM-02-2023-0039.
5
Performance Evaluation of Clinical Decision Support Systems (CDSS): Developing a Business Intelligence (BI) Dashboard.临床决策支持系统(CDSS)的性能评估:开发一个商业智能(BI)仪表板。
Stud Health Technol Inform. 2019 Aug 21;264:829-833. doi: 10.3233/SHTI190339.
6
The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model.协同商业智能技术在医院SPD物流管理模式中的应用
Iran J Public Health. 2017 Jun;46(6):744-754.
7
[Business intelligence in radiology. Challenges and opportunities].[放射学中的商业智能。挑战与机遇]
Radiologe. 2015 Oct;55(10):896-900. doi: 10.1007/s00117-015-0014-5.
8
Functional imaging in computed tomography. The use of contrast-enhanced computed tomography for the study of renal function and physiology.计算机断层扫描中的功能成像。使用对比增强计算机断层扫描研究肾功能和生理学。
Invest Radiol. 1993 Nov;28 Suppl 5:S79-84; discussion S85-6.
9
Power Up: Combining Behavior Monitoring Software with Business Intelligence Tools to Enhance Proactive Animal Welfare Reporting.助力提升:将行为监测软件与商业智能工具相结合以加强主动式动物福利报告。
Animals (Basel). 2022 Jun 22;12(13):1606. doi: 10.3390/ani12131606.
10
Computers in imaging and health care: now and in the future.成像与医疗保健中的计算机:现状与未来。
J Digit Imaging. 2000 Nov;13(4):145-56. doi: 10.1007/BF03168389.

本文引用的文献

1
The Importance of Data Analytics and Business Intelligence for Radiologists.数据分析与商业智能对放射科医生的重要性。
J Am Coll Radiol. 2020 Apr;17(4):511-514. doi: 10.1016/j.jacr.2019.12.022. Epub 2020 Jan 17.
2
ACR Manual on Contrast Media: 2018 Updates.《美国放射学会对比剂手册:2018年更新版》
Radiol Technol. 2019 Sep;91(1):97-100.
3
Risk for adverse reaction to iodinated contrast media: a validation study.碘化造影剂不良反应风险:一项验证研究。
Rev Gaucha Enferm. 2017 Jul 6;38(2):e68449. doi: 10.1590/1983-1447.2017.02.68449.
4
A Business Analytics Software Tool for Monitoring and Predicting Radiology Throughput Performance.一种用于监测和预测放射科吞吐量性能的商业分析软件工具。
J Digit Imaging. 2016 Dec;29(6):645-653. doi: 10.1007/s10278-016-9871-3.
5
Informatics in radiology: automated Web-based graphical dashboard for radiology operational business intelligence.放射学中的信息学:用于放射学运营商业智能的自动化基于 Web 的图形仪表板。
Radiographics. 2009 Nov;29(7):1897-906. doi: 10.1148/rg.297095701. Epub 2009 Sep 4.
6
Business intelligence tools for radiology: creating a prototype model using open-source tools.放射科用商业智能工具:使用开源工具创建原型模型。
J Digit Imaging. 2010 Apr;23(2):133-41. doi: 10.1007/s10278-008-9167-3. Epub 2008 Nov 15.
7
Immediate adverse reactions to intravenous iodinated contrast media in computed tomography.计算机断层扫描中静脉注射碘化造影剂的即时不良反应。
Rev Lat Am Enfermagem. 2007 Jan-Feb;15(1):78-83. doi: 10.1590/s0104-11692007000100012.