4.6 Article

Coauthorship and Institutional Collaborations on Cost-Effectiveness Analyses: A Systematic Network Analysis

期刊

PLOS ONE
卷 7, 期 5, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0038012

关键词

-

向作者/读者索取更多资源

Background: Cost-Effectiveness Analysis (CEA) has been promoted as an important research methodology for determining the efficiency of healthcare technology and guiding medical decision-making. Our aim was to characterize the collaborative patterns of CEA conducted over the past two decades in Spain. Methods and Findings: A systematic analysis was carried out with the information obtained through an updated comprehensive literature review and from reports of health technology assessment agencies. We identified CEAs with outcomes expressed as a time-based summary measure of population health (e.g. quality-adjusted life-years or disability-adjusted life-years), conducted in Spain and published between 1989 and 2011. Networks of coauthorship and institutional collaboration were produced using PAJEK software. One-hundred and thirty-one papers were analyzed, in which 526 authors and 230 institutions participated. The overall signatures per paper index was 5.4. Six major groups (one with 14 members, three with 7 members and two with 6 members) were identified. The most prolific authors were generally affiliated with the private-for-profit sector (e.g. consulting firms and the pharmaceutical industry). The private-for-profit sector mantains profuse collaborative networks including public hospitals and academia. Collaboration within the public sector (e.g. healthcare administration and primary care) was weak and fragmented. Conclusions: This empirical analysis reflects critical practices among collaborative networks that contributed substantially to the production of CEA, raises challenges for redesigning future policies and provides a framework for similar analyses in other regions.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据