• 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

健康信息学中心:加速健康数据科学领域发展的新方法。

The centre for health informatics: a novel approach to accelerating the field of health data science.

作者信息

Southern Danielle A, Eastwood Cathy A, O'Connor Erin, Doktorchik Chelsea, Tonelli Marcello, Meddings Jon, Quan Hude, Williamson Tyler S

机构信息

Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Canada.

Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Canada.

出版信息

Int J Popul Data Sci. 2024 Mar 21;9(1):2368. doi: 10.23889/ijpds.v9i1.2368. eCollection 2024.

DOI:10.23889/ijpds.v9i1.2368
PMID:39620123
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11606538/
Abstract

Precision Medicine and Precision Public Health are approaches to improve population health. Achieving these goals requires innovation in health informatics. The Centre for Health Informatics (CHI) within the Cumming School of Medicine (CSM) at the University of Calgary (UC), Canada, was created to respond to this need by fostering multidisciplinary collaborations, building capacity by recruiting and training outstanding faculty and students, and harnessing Alberta's rich health data to advance health informatics. To establish CHI as a health informatics leader, CHI has struck partnerships with stakeholders, including Alberta Health Services (AHS), Alberta Health (AH), and the Alberta Strategy for Patient-Oriented Research Unit (AbSPORU) among others. Through these close relationships, the CHI intake team facilitates access to Alberta's rich health data sources and educates researchers on the available health data in Alberta. The concept of a "One Stop Shop" for CSM and UC researchers encourages multidisciplinary collaboration, helps investigators access a wide range of datasets, and receive analytical support. Population-based data sets enable the development of methods to turn raw data into health information, improve health data collection, linkage, analysis, and quality, and applied studies creating clinical decision-support tools, prognostic tools, improved health surveillance methods, and health system performance indicators. CHI's ecosystem of diverse research expertise, cutting-edge technology, and embedded AHS analysts to support data access via a wide-ranging network of partnerships allows our provincial researchers, national and international collaborators tremendous opportunities for empirical research. It paves the way for implementing Precision Medicine in the real world.

摘要

精准医学和精准公共卫生是改善人群健康的方法。实现这些目标需要健康信息学方面的创新。加拿大卡尔加里大学卡明医学院(CSM)内的健康信息学中心(CHI)就是为满足这一需求而设立的,它通过促进多学科合作、招募和培养优秀教职员工及学生来建设能力,并利用艾伯塔省丰富的健康数据来推动健康信息学发展。为将CHI打造成健康信息学领域的领军者,CHI与包括艾伯塔省卫生服务局(AHS)、艾伯塔省卫生部(AH)以及艾伯塔省患者导向研究战略单位(AbSPORU)等在内的利益相关者建立了合作关系。通过这些紧密联系,CHI的接收团队为获取艾伯塔省丰富的健康数据源提供便利,并就该省可用的健康数据对研究人员进行培训。为CSM和卡尔加里大学的研究人员提供“一站式服务”的理念鼓励了多学科合作,帮助研究人员获取广泛的数据集,并获得分析支持。基于人群的数据集有助于开发将原始数据转化为健康信息的方法,改善健康数据的收集、关联、分析和质量,以及开展应用研究以创建临床决策支持工具、预后工具、改进的健康监测方法和卫生系统绩效指标。CHI拥有多样的研究专业知识、前沿技术以及嵌入式AHS分析师的生态系统,通过广泛的合作网络支持数据访问,这为我们的省级研究人员、国内和国际合作者提供了大量实证研究机会。它为在现实世界中实施精准医学铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87e2/11606538/dc1e7b8931e3/ijpds-09-2368-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87e2/11606538/6649ad3a0ce7/ijpds-09-2368-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87e2/11606538/dc1e7b8931e3/ijpds-09-2368-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87e2/11606538/6649ad3a0ce7/ijpds-09-2368-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87e2/11606538/dc1e7b8931e3/ijpds-09-2368-g002.jpg

相似文献

1
The centre for health informatics: a novel approach to accelerating the field of health data science.健康信息学中心:加速健康数据科学领域发展的新方法。
Int J Popul Data Sci. 2024 Mar 21;9(1):2368. doi: 10.23889/ijpds.v9i1.2368. eCollection 2024.
2
Health data governance for research use in Alberta.艾伯塔省健康数据用于研究的治理。
Int J Popul Data Sci. 2023 Oct 28;8(4):2160. doi: 10.23889/ijpds.v8i4.2160. eCollection 2023.
3
Partnership-building considerations for implementation science in learning health systems: a case study of the Implementation Science Collaborative in Alberta, Canada.学习型健康系统中实施科学的伙伴关系构建考量:以加拿大艾伯塔省实施科学协作组织为例
Front Health Serv. 2024 Feb 16;4:1327395. doi: 10.3389/frhs.2024.1327395. eCollection 2024.
4
Health Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform.医疗保健与精准医学研究:一个可扩展数据科学平台的分析
J Med Internet Res. 2019 Apr 9;21(4):e13043. doi: 10.2196/13043.
5
An informatics research agenda to support precision medicine: seven key areas.支持精准医学的信息学研究议程:七个关键领域。
J Am Med Inform Assoc. 2016 Jul;23(4):791-5. doi: 10.1093/jamia/ocv213. Epub 2016 Apr 23.
6
Application of Digital Informatics in Precision Prevention, Epidemiology, and Clinicogenomics Research to Advance Precision Healthcare.数字信息学在精准预防、流行病学和临床基因组学研究中的应用以推动精准医疗保健。
Yearb Med Inform. 2024 Aug;33(1):250-261. doi: 10.1055/s-0044-1800753. Epub 2025 Apr 8.
7
The Iowa Health Data Resource (IHDR): an innovative framework for transforming the clinical health data ecosystem.爱荷华州健康数据资源(IHDR):一个用于转变临床健康数据生态系统的创新框架。
J Am Med Inform Assoc. 2024 Feb 16;31(3):720-726. doi: 10.1093/jamia/ocad236.
8
Consumer Health Informatics to Advance Precision Prevention.促进精准预防的消费者健康信息学
Yearb Med Inform. 2024 Aug;33(1):149-157. doi: 10.1055/s-0044-1800735. Epub 2025 Apr 8.
9
Experimenting with Governance: Alberta's Strategic Clinical Networks.治理试验:艾伯塔省的战略临床网络
Healthc Q. 2019 Jan;21(4):37-42. doi: 10.12927/hcq.2019.25742.
10
Critical Care Network in the State of Qatar.卡塔尔国重症监护网络。
Qatar Med J. 2019 Nov 7;2019(2):2. doi: 10.5339/qmj.2019.qccc.2. eCollection 2019.

本文引用的文献

1
Developing an Inpatient Electronic Medical Record Phenotype for Hospital-Acquired Pressure Injuries: Case Study Using Natural Language Processing Models.开发用于医院获得性压力性损伤的住院电子病历表型:使用自然语言处理模型的案例研究
JMIR AI. 2023 Mar 8;2:e41264. doi: 10.2196/41264.
2
Health data governance for research use in Alberta.艾伯塔省健康数据用于研究的治理。
Int J Popul Data Sci. 2023 Oct 28;8(4):2160. doi: 10.23889/ijpds.v8i4.2160. eCollection 2023.
3
Performance of machine learning algorithms for surgical site infection case detection and prediction: A systematic review and meta-analysis.
用于手术部位感染病例检测和预测的机器学习算法性能:系统评价与荟萃分析。
Ann Med Surg (Lond). 2022 Nov 23;84:104956. doi: 10.1016/j.amsu.2022.104956. eCollection 2022 Dec.
4
Personalized prediction of incident hospitalization for cardiovascular disease in patients with hypertension using machine learning.利用机器学习对高血压患者的心血管疾病发病住院进行个体化预测。
BMC Med Res Methodol. 2022 Dec 17;22(1):325. doi: 10.1186/s12874-022-01814-3.
5
Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population.对一个明确界定的城市人群进行跨多种规模的 SARS-CoV-2 RNA 污水纵向监测,与总病例和区域 COVID-19 负担相关。
Water Res. 2022 Jul 15;220:118611. doi: 10.1016/j.watres.2022.118611. Epub 2022 May 14.
6
Stringency of containment and closures on the growth of SARS-CoV-2 in Canada prior to accelerated vaccine roll-out.在加速疫苗接种之前,加拿大对 SARS-CoV-2 的遏制和关闭措施的严格程度。
Int J Infect Dis. 2022 May;118:73-82. doi: 10.1016/j.ijid.2022.02.030. Epub 2022 Feb 23.
7
Healthy food prescription incentive programme for adults with type 2 diabetes who are experiencing food insecurity: protocol for a randomised controlled trial, modelling and implementation studies.健康食物处方激励计划用于患有 2 型糖尿病且面临食物不安全的成年人:一项随机对照试验、建模和实施研究方案。
BMJ Open. 2022 Feb 15;12(2):e050006. doi: 10.1136/bmjopen-2021-050006.
8
Developing a Prediction Model for Pathologic Complete Response Following Neoadjuvant Chemotherapy in Breast Cancer: A Comparison of Model Building Approaches.建立新辅助化疗后乳腺癌病理完全缓解的预测模型:模型构建方法的比较。
JCO Clin Cancer Inform. 2022 Feb;6:e2100055. doi: 10.1200/CCI.21.00055.
9
Validity of ICD-10 codes for COVID-19 patients with hospital admissions or ED visits in Canada: a retrospective cohort study.加拿大新冠病毒疾病患者住院或急诊就诊时国际疾病分类第十版编码的有效性:一项回顾性队列研究
BMJ Open. 2022 Jan 21;12(1):e057838. doi: 10.1136/bmjopen-2021-057838.
10
CREATE: A New Data Resource to Support Cardiac Precision Health.创建:支持心脏精准健康的新数据资源。
CJC Open. 2020 Dec 27;3(5):639-645. doi: 10.1016/j.cjco.2020.12.019. eCollection 2021 May.