Evidence map›Paper›PMID 37483948›Full record

ArticleFrontiers in public health2023

Evaluation of Chinese healthcare organizations' innovative performance in the digital health era.

Wenjun Gu, Luchengchen Shu, Wanning Chen, Jinhua Wang, Dingfeng Wu, Zisheng Ai, Jiyu Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.9field-weighted citation impact, top 7% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

4 citing papers in PubMed, 5 citations in OpenAlex.

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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

7 authors at 4 institutions in 1 country.

Wenjun Gu *School of Medicine, Tongji University, Shanghai, China.
Luchengchen Shu *Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai, China.
Wanning ChenSchool of Life Sciences and Technology, Tongji University, Shanghai, China.
Jinhua WangShanghai Institute of Medical Innovation Technology Transfer, Shanghai, China.
Dingfeng WuNational Clinical Research Center for Child Health, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Zisheng AiSchool of Medicine, Tongji University, Shanghai, China.
Jiyu LiHuadong Hospital, Fudan University, Shanghai, China.
Tongji University · CNCenter for Excellence in Brain Science and Intelligence Technology · CNChildren's Hospital of Zhejiang University · CNFudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Healthcare workers' relationship with industry is not merely an agent mediating between consumer and vendor, but they are also inventors of the interventions they exist to deliver. Driven by the background of the digital health era, scientific research and technological (Sci-tech) innovation in the medical field are becoming more and more closely integrated. However, scholars shed little light on Sci-tech relevance to evaluate the innovation performance of healthcare organizations, a distinctive feature of healthcare organizations' innovation in the digital health era. Methods: Academic publications and patents are the manifestations of scientific research outputs and technological innovation outcomes, respectively. The study extracted data from publications and patents of 159 hospitals in China to evaluate their innovation performance. A total of 18 indicators were constructed, four of which were based on text similarity match and represented the Sci-tech relevance. We then applied factor analyses, analytical hierarchy process, and logistic regression to construct an evaluation model. We also examined the relationship between hospitals' innovation performance and their geographical locations. Finally, we implemented a mediation analysis to show the influence of digital health on hospital innovation performance. Results: A total of 16 indicators were involved, four of which represented the Sci-tech including the number of articles matched per patent (NAMP), the number of patents matched per article (NPMA), the proportion of highly matched patents (HMP), and the proportion of highly matched articles (HMA). Indicators of HMP ( Conclusion: This study constructed an assessment model with four invented indicators focusing on Sci-tech relevance to provide a novel tool for researchers to evaluate the innovation performance of healthcare organizations in the digital health era. The regions with high RIP were concentrated on the eastern coastal areas with a higher level of economic development. Therefore, the promotion of scientific and technological innovation policies could be carried out in advance in areas with better economic development. The innovations in the digital health field by healthcare workers enhance the Sci-tech relevance in hospitals and boost their innovation performance. The development of digital health in hospitals depends on the input of medical personnel.

Indexed as

Delivery of Health CareDigital TechnologyHospitalsChinaInventionsTechnologyanalytical hierarchy process (AHP)Chinese hospitalsdigital health eraevaluation modelfactor analyses (FA)innovation performancelogistic regression (LG)Science-technology relevance

Identifiers

PMID37483948
PMCPMC10359909
OpenAlexW4383314807

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.