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Record W2074392928 · doi:10.1186/1472-6963-12-218

Analysis of the Status of Chinese clinical practice guidelines development

2012· article· en· W2074392928 on OpenAlexaff
Zhi-hong Zheng, Xiaoqin Lu, David Zakus, Wannian Liang, Fang Huang, Xiaona Cao, Yali Zhao, Xiaoxia Peng, Keqin Rao, Jing Wu

Bibliographic record

VenueBMC Health Services Research · 2012
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsCanadian Public Health AssociationUniversity of Toronto
Fundersnot available
KeywordsMedicineGuidelineNursing researchClinical PracticeHealth administrationPopulationFamily medicineChinaPublic healthNursingEnvironmental healthPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The work of developing clinical practice guidelines began just a little more than ten years ago in China. Up to now, there have been few studies about them. OBJECTIVES: To review and analyze the status of Chinese clinical practice guidelines in 1997-2007. METHODS: All Chinese guidelines from 1997-2007 were collected, and made a regression analysis, and a citation analysis for evaluating the impact of guidelines. To analyze the developing quality, the most influential guidelines were evaluated with AGREE instrument, and each guideline was evaluated to check for any updating. In order to analyze the objective and target population, all guidelines were classified and counted separately according to disease/symptom center, and whether towards specialists or general practitioners. RESULTS: 143 guidelines were collected. An exponential function equation was established for the trend in the number of guidelines. The immediacy index in every year was very low while the average citation rate was not. Both the percentages of highly cited and never cited were high. For the evaluation with AGREE, only the average score of clarity and presentation was high (89.9%); the remaining were much lower. Editorial independence scored 0. Only 27 (18.9%) of 143 guidelines, were found to be evidence-based. Only a few had ever been updated, with an average updating interval of 5.2 years. Only 2.1% were symptom-centered, and only 4.2% were aimed at general practitioners. CONCLUSION: Much progress has been obtained for Chinese guidelines development. However, there were still defects, and greater efforts should be made in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.545
GPT teacher head0.692
Teacher spread0.147 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2012
Admission routes1
Has abstractyes

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