Evidence map›Paper›PMID 38762652›Full record

ArticleScientific reports2024

Social network analysis of a decade-long collaborative innovation network between hospitals and the biomedical industry in China.

Xiang Liu, Hong Chen, Yue Liu, Jie Zou, Jiahe Tian, Tenzin Tsomo, Meina Li, Wenya Yu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xiang Liu *Affiliated Xihu Hospital, Hangzhou Medical College, Hangzhou, 310000, China.
Hong Chen *Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Yue Liu *School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Jie ZouDepartment of Pharmacy, The 903Rd Hospital of PLA, Hangzhou, 310000, China.
Jiahe TianSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Tenzin TsomoSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Meina LiDepartment of Military Medical Service, Faculty of Military Health Service, Naval Medical University, Shanghai, 200433, China. meinali53@sina.cn.
Wenya YuSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. jsjyyuwenya@sina.cn.

Funding

Hangzhou Health Science and Technology Program B20220431Shanghai Municipal Health Commission Program 20234Y0070Shanghai Pujiang Program 21PJC083Soft Science Project of Shanghai Science and Technology Innovation Action Plan 23692113200Soft Science Project of Shanghai Science and Technology Innovation Action Plan 23692115000the National Natural Science Foundation of China 72104140the National Natural Science Foundation of China 72274209the National Natural Science Foundation of China 82101870Zhejiang Provincial Natural Science Foundation of China LQ21H100001
6 · The paper itself

Abstract

Collaborative innovation between hospitals and biomedical enterprises is crucial for ensuring breakthroughs in their development. This study explores the structural characteristics and examines the main roles of associated key actors of collaborative innovation between hospitals and biomedical enterprises in China. Using the jointly owned patent data within the country's healthcare industry, a decade-long collaborative innovation network between hospitals and biomedical enterprises in China was established and analyzed through social network analysis. The results revealed that the overall levels of collaborative innovation network density, collaborative frequency, and network connectivity were significantly low, especially in less-developed regions. In terms of actors with higher degree centrality, hospitals accounted for the majority, whereas a biomedical enterprise in Shenzhen had the highest degree centrality. Organizations in underdeveloped and northwest regions and small players were more likely to implement collaborative innovation. In conclusion, a collaborative innovation network between hospitals and biomedical enterprises in China demonstrated high dispersion and poor development levels. Stimulating organizations' initiatives for collaborative innovation may enhance quality and quantity of such innovation. Policy support and economic investments, strategic collaborative help, and resource and partnership optimization, especially for small players and in less-developed and northwest regions, should be encouraged to enhance collaborative innovation between hospitals and the biomedical industry in China and other similar countries or regions.

Indexed as

Cooperative BehaviorHospitalsSocial Network AnalysisChinaHealth Care SectorHumansBiomedicineCollaborative innovationHospitalIndustryNetworkSocial network analysis

Identifiers

PMID38762652
PMCPMC11102486

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.