青少年关节炎登记册中种族和民族数据缺失的差异评估数据集
来自青少年关节炎登记册的缺失种族和民族数据及其对疾病活动评分影响的评估数据集。

基本信息
资源简介
青少年关节炎登记册中种族和民族数据缺失的差异评估数据集
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 493.39 KB,主题涵盖 health equity、data quality、juvenile idiopathic arthritis、learning health system、registry,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《Datasheet3_Assessing disparities through missing race and ethnicity data: results from a juvenile arthritis registry.pdf》。配套论文《Improving Patient Race and Ethnicity Data Capture to Address Health Disparities: A Case Study From a Large Urban Health System》发表于 Cureus(2022),DOI:10.7759/cureus.20973。源站首次发布:2024-07-24。
【数据内容】
源站原始描述:IntroductionEnsuring high-quality race and ethnicity data within the electronic health record (EHR) and across linked systems, such as patient registries, is necessary to achieving the goal of inclusion of racial and ethnic minorities in scientific research and detecting disparities associated with race and ethnicity. The project goal was to improve race and ethnicity data completion within the Pediatric Rheumatology Care Outcomes Improvement Network and assess impact of improved data completion…
【数据结构与技术规格】
文件数 1 个,合计 493.39 KB。Datasheet3_Assessing disparities through missing race and ethnicity data: results from a juvenile arthritis registry.pdf:application/pdf,493.39 KB。数据集 DOI:10.3389/fped.2024.1430981.s003。
【主题与分类】
源站学科分类:Foetal Development and Medicine、Obstetrics and Gynaecology、Paediatrics、Paediatrics and Reproductive Medicine not elsewhere classified。主题标签:health equity、data quality、juvenile idiopathic arthritis、learning health system、registry、electronic health record data。
【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://frontiersin.figshare.com/articles/dataset/Datasheet3_Assessing_disparities_through_missing_race_and_ethnicity_data_results_from_a_juvenile_arthritis_registry_pdf/26361619
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Banschbach, Katelyn M.; Singleton, Jade; Wang, Xing; Vora, Sheetal S.; Harris, Julia G.; Lytch, Ashley; et al. (2024). Datasheet3_Assessing disparities through missing race and ethnicity data: results from a juvenile arthritis registry.pdf. Frontiers. Dataset
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:Datasheet3_Assessing disparities through missing race and ethnicity data: results from a juvenile arthritis registry.pdf
- DOI:10.3389/fped.2024.1430981.s003
- 发布日期:2024-07-24
- 文件数:1 个
- 文件总体积:493.39 KB
- 源站页面:https://frontiersin.figshare.com/articles/dataset/Datasheet3_Assessing_disparities_through_missing_race_and_ethnicity_data_results_from_a_juvenile_arthritis_registry_pdf/26361619
命令行下载
curl -L -o "Datasheet3_Assessing disparities through missing race and ethnicity data: results from a juvenile arthritis registry.pdf" "https://ndownloader.figshare.com/files/47886307"
文件清单
Datasheet3_Assessing disparities through missing race and ethnicity data: results from a juvenile arthritis registry.pdf(493.39 KB)
文件总体积 493.39 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
IntroductionEnsuring high-quality race and ethnicity data within the electronic health record (EHR) and across linked systems, such as patient registries, is necessary to achieving the goal of inclusion of racial and ethnic minorities in scientific research and detecting disparities associated with race and ethnicity. The project goal was to improve race and ethnicity data completion within the Pediatric Rheumatology Care Outcomes Improvement Network and assess impact of improved data completion on conclusions drawn from the registry.
MethodsThis is a mixed-methods quality improvement study that consisted of five parts, as follows: (1) Identifying baseline missing race and ethnicity data, (2) Surveying current collection and entry, (3) Completing data through audit and feedback cycles, (4) Assessing the impact on outcome measures, and (5) Conducting participant interviews and thematic analysis.
ResultsAcross six participating centers, 29% of the patients were missing data on race and 31% were missing data on ethnicity. Of patients missing data, most patients were missing both race and ethnicity. Rates of missingness varied by data entry method (electronic vs. manual). Recovered data had a higher percentage of patients with Other race or Hispanic/Latino ethnicity compared with patients with non-missing race and ethnicity data at baseline. Black patients had a significantly higher odds ratio of having a clinical juvenile arthritis disease activity score (cJADAS10) of ≥5 at first follow-up compared with White patients. There was no significant change in odds ratio of cJADAS10 ≥5 for race and ethnicity after data completion. Patients missing race and ethnicity were more likely to be missing cJADAS values, which may affect the ability to detect changes in odds ratio of cJADAS ≥5 after completion.
ConclusionsAbout one-third of the patients in a pediatric rheumatology registry were missing race and ethnicity data. After three audit and feedback cycles, centers decreased missing data by 94%, primarily via data recovery from the EHR. In this sample, completion of missing data did not change the findings related to differential outcomes by race. Recovered data were not un
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fped.2024.1430981.s003(source: https://frontiersin.figshare.com/articles/dataset/Datasheet3_Assessing_disparities_through_missing_race_and_ethnicity_data_results_from_a_juvenile_arthritis_registry_pdf/26361619)。
需要用于商业化训练或医疗器械注册(NMPA/FDA)?
公开数据往往缺乏完整的病理回证与专家标注。千方医数集依托陕川双基地与超十家三甲医院直连,提供完全合规、去标识化、支持注册级质控的专病数据集交易服务。




