癌症护理支付改革与护理模型系统综述数据集
本数据集包含关于癌症护理中提供者支付改革对成本与质量影响的系统文献综述,涵盖26项研究,提取了资源使用、成本、护理质量等数据。

基本信息
资源简介
癌症护理支付改革与护理模型系统综述数据集
【一句话概览】
本数据集是 figshare 公开的文本数据集,收录 5 个文件、合计 95.34 KB,主题涵盖 cancer care reforms、cancer care outcomes、impact、Alternative payment models、cancer care,可用于医学自然语言处理(实体识别、信息抽取等),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 impact of provider payment reforms and associated care delivery models on cost and quality in cancer care: A systematic literature review》。配套论文《The impact of provider payment reforms and associated care delivery models on cost and quality in cancer care: A systematic literature review》发表于 PLOS ONE(2019),DOI:10.1371/journal.pone.0214382。源站首次发布:2019-04-05。
【数据内容】
源站原始描述:Objectives To investigate the impact of provider payment reforms and associated care delivery models on cost and quality in cancer care. Methods Data sources/study setting: Review of English-language literature published in PubMed, Embase and Cochrane library (2007–2019). Study design: We performed a systematic literature review (SLR) to identify the impact of cancer care reforms. Primary endpoints were resource use, cost, quality of care, and clinical outcomes. Data collection/extraction method…
【数据结构与技术规格】
文件数 5 个,合计 95.34 KB。pone.0214382.s001.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,23.84 KB。pone.0214382.s002.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,16.64 KB。pone.0214382.s003.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,15.90 KB。数据集 DOI:10.1371/journal.pone.0214382。
【主题与分类】
源站学科分类:Medicine、Sociology、Science Policy、Infectious Diseases。主题标签:cancer care reforms、cancer care outcomes、impact、Alternative payment models、cancer care、care delivery models、ACO、provider payment reforms、literature review Objectives、resource use。
【适用方向】
文本类数据可用于医学自然语言处理,如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/The_impact_of_provider_payment_reforms_and_associated_care_delivery_models_on_cost_and_quality_in_cancer_care_A_systematic_literature_review/7959941
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Nejati, Mina; Razavi, Moaven; Harirchi, Iraj; Zendehdel, Kazem; Nejati, Parisa (2019). The impact of provider payment reforms and associated care delivery models on cost and quality in cancer care: A systematic literature review. PLOS ONE. Dataset
【使用注意】
· 源站最后修改于 2023-06-06,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 impact of provider payment reforms and associated care delivery models on cost and quality in cancer care: A systematic literature review
- DOI:10.1371/journal.pone.0214382
- 发布日期:2019-04-05
- 文件数:5 个
- 文件总体积:95.34 KB
- 源站页面:https://plos.figshare.com/articles/dataset/The_impact_of_provider_payment_reforms_and_associated_care_delivery_models_on_cost_and_quality_in_cancer_care_A_systematic_literature_review/7959941
命令行下载
curl -L -o "pone.0214382.s001.docx" "https://ndownloader.figshare.com/files/14815526"
curl -L -o "pone.0214382.s002.docx" "https://ndownloader.figshare.com/files/14815529"
curl -L -o "pone.0214382.s003.docx" "https://ndownloader.figshare.com/files/14815532"
curl -L -o "pone.0214382.s004.docx" "https://ndownloader.figshare.com/files/14815538"
curl -L -o "pone.0214382.s005.docx" "https://ndownloader.figshare.com/files/14815544"
文件清单
pone.0214382.s001.docx(23.84 KB)pone.0214382.s002.docx(16.64 KB)pone.0214382.s003.docx(15.90 KB)pone.0214382.s004.docx(17.96 KB)pone.0214382.s005.docx(21.00 KB)
文件总体积 95.34 KB(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
Objectives
To investigate the impact of provider payment reforms and associated care delivery models on cost and quality in cancer care.
Methods
Data sources/study setting: Review of English-language literature published in PubMed, Embase and Cochrane library (2007–2019).
Study design: We performed a systematic literature review (SLR) to identify the impact of cancer care reforms. Primary endpoints were resource use, cost, quality of care, and clinical outcomes.
Data collection/extraction methods: For each study, we extracted and categorized comparative data on the impact of policy reforms. Given the heterogeneity in patients, interventions and outcome measures, we did a qualitative synthesis rather than a meta-analysis.
Results
Of the 26 included studies, seven evaluations were in fact qualified as quasi experimental designs in retrospect. Alternative payment models were significantly associated with reduction in resource use and cost in cancer care. Across the seventeen studies reporting data on the implicit payment reforms through care coordination, the adoption of clinical pathways was found effective in reduction of unnecessary use of low value services and associated costs. The estimates of all measures in ACO models varied considerably across participating providers, and our review found a rather mixed impact on cancer care outcomes.
Conclusion
The findings suggest promising improvement in resource utilization and cost control after transition to prospective payment models, but, further primary research is needed to apply robust measures of performance and quality to better ensure that providers are delivering high-value care to their patients, while reducing the cost of care.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0214382(source: https://plos.figshare.com/articles/dataset/The_impact_of_provider_payment_reforms_and_associated_care_delivery_models_on_cost_and_quality_in_cancer_care_A_systematic_literature_review/7959941)。
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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