five

Table_1_No Two Workforces Are the Same: A Systematic Review of Enumerations and Definitions of Public Health Workforces.docx

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/Table_1_No_Two_Workforces_Are_the_Same_A_Systematic_Review_of_Enumerations_and_Definitions_of_Public_Health_Workforces_docx/13258355
下载链接
链接失效反馈
官方服务:
资源简介:
The delivery and coordination of public health functions is essential to national and global health, however, there are considerable problems in defining the people who work in public health, as well as estimating their number. Therefore, the aim of this systematic review was to identify and explore research which has defined and enumerated public health workforces. In particular, how were such workforces defined? Who was included in these workforces? And how did researchers make judgments about the size of a workforce? In this systematic review, we identified 82 publications which enumerated a public health workforce between 2000 and November 2018. Most workforce definitions were unique and study-specific and included workers based on their occupation or their place of work. Common occupations included public health nurses and physicians, epidemiologists, and community health workers. National workforces varied by size, with the United States and Switzerland having the largest public health workforces per-capita, although definitions used varied substantially. Normative assessments (e.g., assessments of ideal workforce size) were informed through opinion, benchmarks or “service-target” models. There are very few regular, consistent enumerations within countries, and fewer still which capture a substantial proportion of the public heath workforce. Assessing the size of the public health workforce is often overlooked and would be aided by fit-for-purpose data, alignment of occupations and functions to international standards, and transparency in normative methods.
创建时间:
2020-11-19
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作