资源有限环境下改善SARS-CoV-2即时检验诊断服务供应链管理的新方法

包含COVID-19即时检验服务地理分布、供应链管理合规评分及改进策略优先级的混合方法数据集。

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2023-08-16 更新
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多模态COVID-19Point-of-care testing servicesPrimary healthcare clinics auditSupply chain managementSpatial distributionNominal Group Technique (NGT)Mopani districtSDG 3 Good health and well-being
A novel approach for improving supply chain management for SARS-CoV-2 point-of-care diagnostic services in resource-limited settings

基本信息

模态
多模态
大小
0.005654104 GB
许可
CC BY 4.0
创建/更新时间
2023-08-16
版本
v1

资源简介

资源有限环境下改善SARS-CoV-2即时检验诊断服务供应链管理的新方法

【数据集背景】

本数据集源站标题为《A novel approach for improving supply chain management for SARS-CoV-2 point-of-care diagnostic services in resource-limited settings》。项目资助方:National Research Foundation (NRF)。源站首次发布:2023-08-16。

【数据内容】

源站原始描述:This was a multiphase mixed methods study consisted of three phases, starting with a geospatial analysis to assess the spatial distribution of COVID-19 point of care (POC) testing services in the Mopani District. Phase 2 involved an audit of primary healthcare (PHC) clinics providing COVID-19 POC diagnostic services to evaluate the impact of supply chain management (SCM) on accessibility and identify barriers and enablers. Based on the findings from the initial phases, Phase 3 employed a nominal…

【数据结构与技术规格】

文件数 1 个,合计 5.65 MB。数据集 DOI:10.25403/UPresearchdata.23956923.v1。

【主题与分类】

源站学科分类:Primary health care、Health geography、Health equity。主题标签:COVID-19、Point-of-care testing services、Primary healthcare clinics audit、Supply chain management、Spatial distribution、Nominal Group Technique (NGT)、Mopani district、SDG 3 Good health and well-being。

【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://researchdata.up.ac.za/articles/dataset/A_novel_approach_for_improving_supply_chain_management_for_SARS-CoV-2_point-of-care_diagnostic_services_in_resource-limited_settings/23956923

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

规范引用:Maluleke, Kuhlula (2023). A novel approach for improving supply chain management for SARS-CoV-2 point-of-care diagnostic services in resource-limited settings. University of Pretoria. Dataset

【使用注意】

· 源站最后修改于 2023-08-17,引用时请注意版本时效。

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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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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 "Maluleke_Data for Improving SCM for POC_2023.docx" "https://ndownloader.figshare.com/files/42008628"

文件清单

  • Maluleke_Data for Improving SCM for POC_2023.docx(5.65 MB)

文件总体积 5.65 MB(源站 API 实测)。

数据说明

This was a multiphase mixed methods study consisted of three phases, starting with a geospatial analysis to assess the spatial distribution of COVID-19 point of care (POC) testing services in the Mopani District. Phase 2 involved an audit of primary healthcare (PHC) clinics providing COVID-19 POC diagnostic services to evaluate the impact of supply chain management (SCM) on accessibility and identify barriers and enablers. Based on the findings from the initial phases, Phase 3 employed a nominal group technique (NGT) to collaborate with key stakeholders in co-creating a novel approach for improving SCM systems for COVID-19 POC diagnostic services.

For geospatial analysis, ArcGIS 10.8.2 software was employed to determine the following:

i) the physical location of PHC clinics and district hospitals (areas of supply)

ii) the population distribution (areas of demand)

iii) calculated the travel distances from areas of demand to areas of supply

iv) examined variations of spatial accessibility in different areas and 

v) identified areas with a paucity of COVID-19 diagnostic services.

For the audit, we utilised an audit tool and the dataset contains the supply chain management compliance score for all the audited facilities. For the NGT, we used a qualitative data analysis approach (involving key stakeholders) in the co-creation of a novel approach for improving SCM. The dataset contains barriers and strategies that the key stakeholders identified. The barriers and strategies are ranked according to priority.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.25403/UPresearchdata.23956923.v1(source: https://researchdata.up.ac.za/articles/dataset/A_novel_approach_for_improving_supply_chain_management_for_SARS-CoV-2_point-of-care_diagnostic_services_in_resource-limited_settings/23956923)。

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