An investigation on implementation of clinical governance: A case study of an Iranian hospital
Bibliographic record
Abstract
Clinical Governance (CG) generally aims to enhance the quality of clinical services, increases the accountability of those who are responsible for health affairs. This study examines the quality of presenting medical services in Dr. Shariati hospital in Tehran after executing the CG project. To attain the aforesaid goal, this research also surveys the implementation rate of CG in Dr. Shariati hospital based on the CG seven-pillar model. The study is a descriptive and crosssectional research fulfilled in summer 2013. Statistical population contains the employees of Dr. Shariati hospital in Tehran and the research sample includes 80 people of the mentioned population who were selected, randomly. Data was gathered through a questionnaire and the experts confirmed its validity and the reliability was approved via Cronbach's alpha of 0.947 and then, the analysis was carried out by the SPSS software and T-test. The findings for each CG pillar in Dr. Shariati hospital have placed less than the medium amount and they are not in desirable level. The CG at the above-mentioned hospital places in a medium rank so that the efforts by the managers will create successful changes at the hospital; meanwhile, the managers will be able to utilize the CG method in systematic prediction of changeable priorities to present the best strategies for achievable performance of managerial techniques and processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".