十国静脉血栓栓塞负担:手术和ICU患者的疾病成本马尔可夫模型
评估十国手术和ICU患者中医院获得性静脉血栓栓塞的经济与临床负担,基于马尔可夫模型和调查数据。

基本信息
资源简介
十国静脉血栓栓塞负担:手术和ICU患者的疾病成本马尔可夫模型
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集,收录 3 个文件、合计 1.66 MB,主题涵盖 Iatrogenic VTE、deep vein thrombosis、pulmonary embolism、burden-of-disease、prophylaxis,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《The burden of venous thromboembolism in ten countries: a cost-of-illness Markov model on surgical and ICU patients》。配套论文《The burden of venous thromboembolism in ten countries: a cost-of-illness Markov model on surgical and ICU patients》发表于 Journal of Medical Economics(2024),DOI:10.1080/13696998.2024.2436797。项目资助方:This study was supported by funding from Cardinal Health. Coreva Scientific GmbH & Co. KG, and Alex Veloz received consultancy fees from Cardinal Health for work related to this manuscript. Cardinal Health had no role in the design and conduct of the study; management, analysis, and interpretation of the data; preparation, or approval of the manuscript.。源站首次发布:2024-12-10。
【数据内容】
源站原始描述:The objective of this study was to assess the burden of hospital-acquired venous thromboembolism (VTE) on healthcare systems and patients across ten countries. A multi-methodological approach was taken to estimate the burden of hospital-acquired VTE across five key clinical specialties and ten countries (Australia, Brazil, China, France, Mexico, South Korea, Spain, Taiwan, Thailand, and the United Kingdom). Surveys with healthcare professionals (surgeons, hematologists, and hospital management)…
【数据结构与技术规格】
文件数 3 个,合计 1.66 MB。ijme_a_2436797_sm4089.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,1.25 MB。ijme_a_2436797_sm4088.pdf:application/pdf,227.84 KB。ijme_a_2436797_sm4087.pdf:application/pdf,186.24 KB。数据集 DOI:10.6084/m9.figshare.27931539.v2。
【主题与分类】
源站学科分类:Medicine、Biotechnology、Biological Sciences not elsewhere classified、Cancer、Science Policy、Hematology。主题标签:Iatrogenic VTE、deep vein thrombosis、pulmonary embolism、burden-of-disease、prophylaxis、cost of illness、hospital-acquired condition、H51、I19。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://tandf.figshare.com/articles/dataset/The_burden_of_venous_thromboembolism_in_ten_countries_A_cost-of-illness_Markov_model_on_surgical_and_ICU-patients/27931539
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:The burden of venous thromboembolism in ten countries: a cost-of-illness Markov model on surgical and ICU patients. Taylor & Francis. Seemann, Kim; Silas, Ubong; Smith, Antonia Bosworth; Münch, Tobias; Saunders, Sita J.; Veloz, Alex; et al
【使用注意】
· 源站最后修改于 2026-01-21,引用时请注意版本时效。
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:The burden of venous thromboembolism in ten countries: a cost-of-illness Markov model on surgical and ICU patients
- DOI:10.6084/m9.figshare.27931539.v2
- 发布日期:2024-12-10
- 文件数:3 个
- 文件总体积:1.66 MB
- 源站页面:https://tandf.figshare.com/articles/dataset/The_burden_of_venous_thromboembolism_in_ten_countries_A_cost-of-illness_Markov_model_on_surgical_and_ICU-patients/27931539
命令行下载
curl -L -o "ijme_a_2436797_sm4089.docx" "https://ndownloader.figshare.com/files/50883327"
curl -L -o "ijme_a_2436797_sm4088.pdf" "https://ndownloader.figshare.com/files/50883330"
curl -L -o "ijme_a_2436797_sm4087.pdf" "https://ndownloader.figshare.com/files/50883333"
文件清单
ijme_a_2436797_sm4089.docx(1.25 MB)ijme_a_2436797_sm4088.pdf(227.84 KB)ijme_a_2436797_sm4087.pdf(186.24 KB)
文件总体积 1.66 MB(源站 API 实测)。
数据加载示例(图像类)
from PIL import Image
import glob, os
files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)
# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path) # 要求 子目录=类别
目录组织与标注格式以源站说明和下载后实际文件为准。
数据说明
The objective of this study was to assess the burden of hospital-acquired venous thromboembolism (VTE) on healthcare systems and patients across ten countries.
A multi-methodological approach was taken to estimate the burden of hospital-acquired VTE across five key clinical specialties and ten countries (Australia, Brazil, China, France, Mexico, South Korea, Spain, Taiwan, Thailand, and the United Kingdom). Surveys with healthcare professionals (surgeons, hematologists, and hospital management) were conducted to identify clinical specialties of interest. A systematic literature review and interviews were conducted to identify data for incidences and costs. A health-economic model was developed, using a decision tree and Markov model to estimate 1-year costs. Costs are presented in 2022 USD.
Orthopedics, oncology, long-term ICU, cardiology, and obstetrics and gynecology were identified as the clinical specialties of interest. The total cost burden of hospital-acquired VTE was estimated to be $41,280 million, which equals $503 per patient at risk. Expressed as a share of 2022 GDP, an average spending per country of 0.05% to 0.18% was observed. The VTE-associated mortality was substantial, accounting for 150,081 deaths in a 74.2 million population, translating into an average mortality rate of 2.02 (0.64–3.05) per 1,000 patients at risk.
There were limited data available concerning VTE incidences in some countries and clinical specialties. Where data were available, there was heterogeneity of incidence definitions across the identified studies. Generalizations, imputations, and the country-agnostic structure of the model might have contributed to biases.
The burden of hospital-acquired VTE is substantial both from an economic and from a patient perspective in all countries evaluated.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.27931539.v2(source: https://tandf.figshare.com/articles/dataset/The_burden_of_venous_thromboembolism_in_ten_countries_A_cost-of-illness_Markov_model_on_surgical_and_ICU-patients/27931539)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
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