实践内和实践间变异统计

数据集获取（Figshare）

• 源站标题：Between and within practice variation statistics.
• DOI：10.1371/journal.pone.0294061.t003
• 发布日期：2024-05-08
• 文件数：1 个
• 文件总体积：5.63 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Between_and_within_practice_variation_statistics_/25776207

命令行下载

curl -L -o "Table 3.xls" "https://ndownloader.figshare.com/files/46184391"

文件清单

• Table 3.xls（5.63 KB）

文件总体积 5.63 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

Introduction
Reducing waiting times is a major policy objective in publicly-funded healthcare systems. However, reductions in waiting times can produce a demand response, which may offset increases in capacity. Early detection and diagnosis of cancer is a policy focus in many OECD countries, but prolonged waiting periods for specialist confirmation of diagnosis could impede this goal. We examine whether urgent GP referrals for suspected cancer patients are responsive to local hospital waiting times.
Method
We used annual counts of referrals from all 6,667 general practices to all 185 hospital Trusts in England between April 2012 and March 2018. Using a practice-level measure of local hospital waiting times based on breaches of the two-week maximum waiting time target, we examined the relationship between waiting times and urgent GP referrals for suspected cancer. To identify whether the relationship is driven by differences between practices or changes over time, we estimated three regression models: pooled linear regression, a between-practice estimator, and a within-practice estimator.
Results
Ten percent higher rates of patients breaching the two-week wait target in local hospitals were associated with higher volumes of referrals in the pooled linear model (4.4%; CI 2.4% to 6.4%) and the between-practice estimator (12.0%; CI 5.5% to 18.5%). The relationship was not statistically significant using the within-practice estimator (1.0%; CI -0.4% to 2.5%).
Conclusion
The positive association between local hospital waiting times and GP demand for specialist diagnosis was caused by practices with higher levels of referrals facing longer local waiting times. Temporal changes in waiting times faced by individual practices were not related to changes in their referral volumes. GP referrals for diagnostic cancer services were not found to respond to waiting times in the short-term. In this setting, it may therefore be possible to reduce waiting times by increasing supply without consequently increasing demand.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0294061.t003（source: https://plos.figshare.com/articles/dataset/Between_and_within_practice_variation_statistics_/25776207）。