Evidence map›Paper›PMID 39220428›Full record

ArticleHealth care science2024

Formulation of a CITE metric for evaluating the clinical implications of medical studies and their originating hospitals in China.

Gao Jianchao, Chen Xiaoyuan, Gao Chenyan

Abstract read
In one paragraph

Article in Health care science, 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

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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

3 authors.

Gao JianchaoCenter for Drug Evaluation, National Medical Products Administration Beijing China.ORCID 0000-0001-8754-8316
Chen XiaoyuanTsinghua Clinical Research Institute (TCRI), School of Medicine Tsinghua University Beijing China.
Gao ChenyanChangping Laboratory Beijing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The number of medical research publications by Chinese clinical investigators has risen substantially, contributing to 14.63% of the global total in 2019; however, their tangible impact on clinical decision-making remains limited. Various evaluation methods have been developed to measure hospital research competence in China, such as Fudan University's China hospital ranking and Science and Technology Evaluation Metrics (STEM) ranking, which predominantly focuses on factors such as academic reputation, volume of publications and patents, and research resources. However, composite indices may not fully capture the actual clinical value generated by medical research. To address this gap, we introduced the "Clinical Influence and Timeliness Evaluation (CITE)" metric to assess both the clinical importance of a given medical research study and the clinical influence of the hospital where it originated. The methodology used relies on the premise that influential medical research would be referenced in clinical guidelines, which serve as critical resources for clinicians. Methods: The CITE metric was applied for 78,636 medical studies concerning chronic obstructive pulmonary disease (COPD) published between 2000 and 2020 and referenced in both Chinese and international clinical guidelines for COPD. Specific indexes and formulas were derived to quantify the clinical weight of a medical research study (W) and its timeliness (T), enabling a dynamic assessment of the clinical value of each study and the overall contribution of a particular hospital. Results: In this analysis, we incorporated 499 hospitals in China and quantitatively identified their dynamic clinical influence in COPD from 2000 to 2020. Our findings offer objective and targeted evaluation metrics by focusing on clinical relevance and recognizing the collaborative nature of medical research. Conclusion: The CITE metric provides an innovative method to gauge the true impact of medical research in China, with potential applications across different medical specialties. CITE can serve as a useful tool for understanding the relationship between research input and practical clinical outcomes, ultimately promoting more clinically relevant research endeavors.

Indexed as

Chinese clinical investigationsClinical Influence and Timeliness Evaluation (CITE)hospital research competence

Identifiers

PMID39220428
PMCPMC11362660

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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.