评估跨医疗部门界面的结直肠癌护理质量

数据集获取（Figshare）

• 源站标题：Evaluating the Quality of Colorectal Cancer Care across the Interface of Healthcare Sectors
• DOI：10.1371/journal.pone.0060947
• 发布日期：2013-05-01
• 文件数：7 个
• 文件总体积：235.65 KB
• 源站页面：https://plos.figshare.com/articles/dataset/_Evaluating_the_Quality_of_Colorectal_Cancer_Care_across_the_Interface_of_Healthcare_Sectors_/695234

命令行下载

curl -L -o "Table_S1.docx" "https://ndownloader.figshare.com/files/1050277"
curl -L -o "Table_S2.docx" "https://ndownloader.figshare.com/files/1050280"
curl -L -o "Table_S3.docx" "https://ndownloader.figshare.com/files/1050283"
curl -L -o "Table_S4.docx" "https://ndownloader.figshare.com/files/1050287"
curl -L -o "Table_S5.docx" "https://ndownloader.figshare.com/files/1050288"
curl -L -o "Table_S6.docx" "https://ndownloader.figshare.com/files/1050290"
curl -L -o "Table_S7.docx" "https://ndownloader.figshare.com/files/1050291"

文件清单

• Table_S1.docx（47.78 KB）
• Table_S2.docx（40.24 KB）
• Table_S3.docx（30.14 KB）
• Table_S4.docx（23.56 KB）
• Table_S5.docx（25.15 KB）
• Table_S6.docx（36.53 KB）
• Table_S7.docx（32.25 KB）

文件总体积 235.65 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

Background
Colorectal cancer (CRC) has a high prevalence in western countries. Diagnosis and treatment of CRC is complex and requires multidisciplinary collaboration across the interface of health care sectors. In Germany, a new nationwide established program aims to provide quality information of healthcare delivery across different sectors. Within this context, this study describes the development of a set of quality indicators charting the whole pathway of CRC-care including data specifications that are necessary to operationalize these indicators before practice testing.
Methods
Indicators were developed following a systematic 10 step modified ‘RAND/UCLA Appropriateness Method’ which involved a multidisciplinary panel of thirteen participants. For each indicator in the final set, data specifications relating to sources of quality information, data collection procedures, analysis and feedback were described.
Results
The final indicator set included 52 indicators covering diagnostic procedures (11 indicators), therapeutic management (28 indicators) and follow-up (6 indicators). In addition, 7 indicators represented patient perspectives. Primary surgical tumor resection and pre-operative radiation (rectum carcinoma only) were perceived as most useful tracer procedures initiating quality data collection. To assess the quality of CRC care across sectors, various data sources were identified: medical records, administrative inpatient and outpatient data, sickness-funds billing code systems and patient survey.
Conclusion
In Germany, a set of 52 quality indicators, covering necessary aspects across the interfaces and pathways relevant to CRC-care has been developed. Combining different sectors and sources of health care in quality assessment is an innovative and challenging approach but reflects better the reality of the patient pathway and experience of CRC-care.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0060947（source: https://plos.figshare.com/articles/dataset/_Evaluating_the_Quality_of_Colorectal_Cancer_Care_across_the_Interface_of_Healthcare_Sectors_/695234）。