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Record W2356018353

Study on the development strategy and tactics of the family doctors system in Shanghai city based on the community health management

2012· article· en· W2356018353 on OpenAlexaboutno aff
Xu Ting

Bibliographic record

VenueShanghai Medical & Pharmaceutical Journal · 2012
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFistService (business)Family medicineCommunity healthQuarter (Canadian coin)Systematic samplingCommunity hospitalService systemNursingPublic health
DOInot available

Abstract

fetched live from OpenAlex

Objective: To further understand the cognition and vision of resident in Shanghai for family medical system, to deeply analyze the factors and status of family medical system and bring up the policy suggestion for Shanghai medicine reform. Method: With random sampling and whole sampling and layering sampling, 2082 samples (86.75%) were taken from Xu Hui, Min Hang and Jin Shan districts. Results: 1) The situation of community first diagnosis in Shanghai residents was that 65.40% outpatients chose the community hospital and 20.8% the third class hospital, 57.4% inpatients chose the community hospital as their first diagnosis and 27.8% the third class hospital. 2) Analysis of the factors of community first diagnosis in Shanghai residents: the reasons for choosing community hospital as fist diagnosis were cheaper price and traffic convenience for outpatients, and cheaper price and better service attitude for inpatients. 3) The residents have higher need in health management and family care . 4) The residents have poor cognition to family medical system in Shanghai. Conclusion: The situation of the development of family medical system in Shanghai is better. It is important to establish policy and guarantee the realization of family doctor system in Shanghai. Community health management is also an urgent matter of the moment。

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)0.017
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.006
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 head0.218
GPT teacher head0.474
Teacher spread0.256 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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