优化镰状细胞病护理模型以改善古吉拉特部落地区医院患者临床结局数据集

镰状细胞病护理模型优化的混合方法研究数据,含定量临床指标和定性访谈,用于改善古吉拉特部落地区医院患者结局。

Nirgude, Abhay Subashrao; Dave, Kapilkumar; Desai, Shrey; Desai, Gayatri; devare, sumeetNirgude, Abhay Subashrao; Dave, Kapilkumar; Desai, Shrey; Desai, Gayatri; devare, sumeet
Figshare
2024-08-16 更新
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多模态sickle cell diseasetribeprogram evaluation
Optimizing the sickle cell disease care model to improve clinical outcomes among patients registered at a secondary care hospital in a tribal area of Gujarat

基本信息

模态
多模态
大小
0.002966606 GB
许可
CC BY 4.0
创建/更新时间
2024-08-16
版本
v1

资源简介

优化镰状细胞病护理模型以改善古吉拉特部落地区医院患者临床结局数据集

【数据集背景】

本数据集源站标题为《Optimizing the sickle cell disease care model to improve clinical outcomes among patients registered at a secondary care hospital in a tribal area of Gujarat》。源站首次发布:2024-08-16。

【数据内容】

源站原始描述:To improve the clinical outcomes among SCD populations, a comprehensive hospital-based intervention is in place at Kasturba hospital, SEWA rural, Jhagadia. The recent results of a quasi-experimental study suggested that the coverage of proven interventions improved due to current comprehensive SCD program, although there was no improvement in clinical outcomes including pain crisis, hospitalization and haemoglobin level. In this paper we present the process of refinement of the current care mode…

【数据结构与技术规格】

文件数 1 个,合计 2.97 MB。hospi.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,2.97 MB。数据集 DOI:10.6084/m9.figshare.26763388.v1。

【主题与分类】

源站学科分类:Health systems、Health management、Implementation science and evaluation、Rural and remote health services。主题标签:sickle cell disease、tribe、program evaluation。

【适用方向】

多模态数据适合跨模态对齐、融合建模与联合表征学习方向的研究。

【获取与许可】

源站页面:https://figshare.com/articles/dataset/Optimizing_the_sickle_cell_disease_care_model_to_improve_clinical_outcomes_among_patients_registered_at_a_secondary_care_hospital_in_a_tribal_area_of_Gujarat/26763388

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Dave, Kapilkumar; Nirgude, Abhay Subashrao; Desai, Shrey; devare, sumeet; Desai, Gayatri (2024). Optimizing the sickle cell disease care model to improve clinical outcomes among patients registered at a secondary care hospital in a tribal area of Gujarat. figshare. Dataset

官方服务

专家保障全链路合规授权与标注交付

陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

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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。

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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。

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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)

命令行下载

curl -L -o "hospi.xlsx" "https://ndownloader.figshare.com/files/48619288"

文件清单

  • hospi.xlsx(2.97 MB)

文件总体积 2.97 MB(源站 API 实测)。

数据说明

To improve the clinical outcomes among SCD populations, a comprehensive hospital-based intervention is in place at Kasturba hospital, SEWA rural, Jhagadia. The recent results of a quasi-experimental study suggested that the coverage of proven interventions improved due to current comprehensive SCD program, although there was no improvement in clinical outcomes including pain crisis, hospitalization and haemoglobin level. In this paper we present the process of refinement of the current care model for optimization of improved clinical outcomes. Study design- Explanatory mixed method study. It has five steps Step 1: Literature review, Step 2: Secondary data analysis (Quantitative), Step 3: Exploratory qualitative data collection to understand gap in the system, Step 4: Drafting and refining the intervention, Step 5: Optimizing the intervention. Grounded in the MRC framework, this approach not only contributes to the conversation about improving patient outcomes but also fosters a more thoughtful, patient-centred perspective within the broader healthcare context.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.26763388.v1(source: https://figshare.com/articles/dataset/Optimizing_the_sickle_cell_disease_care_model_to_improve_clinical_outcomes_among_patients_registered_at_a_secondary_care_hospital_in_a_tribal_area_of_Gujarat/26763388)。

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。

⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。

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