严重精神疾病患者健康指标激励效果研究数据集
基于QOF框架,使用混合效应逻辑回归分析2006-2020年伦敦南部严重精神疾病患者健康指标记录的激励效果,数据为统计结果表格。

基本信息
资源简介
严重精神疾病患者健康指标激励效果研究数据集
【数据集背景】
本数据集源站标题为《Mixed effects logistic regression (whole sample).》。源站首次发布:2025-05-30。
【数据内容】
源站原始描述:The Quality-of-Care Framework (QOF) aims to improve patient care for at risk groups through financial incentivisation. This study assesses the effect of changes in incentivisation of four health indicators for people with severe mental illness (SMI) on their recording versus controls. 9,250 patients with SMI aged >18 from South London and 12,729 controls were included using linked primary and mental healthcare records between 2006–2020. Mixed effect logistic regression controlling for age, gende…
【数据结构与技术规格】
文件数 1 个,合计 5.63 KB。Table 1.xls:application/vnd.ms-excel,5.63 KB。数据集 DOI:10.1371/journal.pmen.0000185.t001。
【主题与分类】
源站学科分类:Biotechnology、Environmental Sciences not elsewhere classified、Sociology、Biological Sciences not elsewhere classified、Developmental Biology、Science Policy。主题标签:severe mental illness、mental healthcare records、2006 – 2020、without incentivisation within、recording versus controls、likelihood dropped significantly、improved health screening、improve patient care、four health indicators、div >< p。
【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://plos.figshare.com/articles/dataset/Mixed_effects_logistic_regression_whole_sample_/29200156
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Romano, Eugenia; Ma, Ruimin; Sala, Giovanni; Ashworth, Mark; Perera, Gayan; Stewart, Robert; et al. (2025). Mixed effects logistic regression (whole sample).. PLOS Mental Health. 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:Mixed effects logistic regression (whole sample).
- DOI:10.1371/journal.pmen.0000185.t001
- 发布日期:2025-05-30
- 文件数:1 个
- 文件总体积:5.63 KB
- 源站页面:https://plos.figshare.com/articles/dataset/Mixed_effects_logistic_regression_whole_sample_/29200156
命令行下载
curl -L -o "Table 1.xls" "https://ndownloader.figshare.com/files/54999256"
文件清单
Table 1.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
The Quality-of-Care Framework (QOF) aims to improve patient care for at risk groups through financial incentivisation. This study assesses the effect of changes in incentivisation of four health indicators for people with severe mental illness (SMI) on their recording versus controls. 9,250 patients with SMI aged >18 from South London and 12,729 controls were included using linked primary and mental healthcare records between 2006–2020. Mixed effect logistic regression controlling for age, gender, and neighbourhood deprivation estimated effects of incentivisation on health indicators in SMI and controls, and compared periods with/without incentivisation within the SMI sample and between SMI diagnostic groups. SMI patients overall were more likely than controls to be checked for all health indicators, and incentivisation was associated with increases in all screening measures in SMI compared to controls. In SMI patients, compared to pre-incentivisation, the likelihood of being checked increased overall (ranging from OR = 1.48 p p p < .001). Impacts were similar across SMI categories. While primary care financial incentivisation is associated with improved health screening in adults with SMI, its duration can impact quality of care, raising concerns over health inequalities in people with SMI and on the effectiveness of incentivised performance in healthcare.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pmen.0000185.t001(source: https://plos.figshare.com/articles/dataset/Mixed_effects_logistic_regression_whole_sample_/29200156)。
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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