Iranian hospital efficiency: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: The purpose of this paper (systematic review and meta-analysis) is to synthesize and analyze studies that assessed Iranian hospital efficiency. DESIGN/METHODOLOGY/APPROACH: A systematic literature search was conducted using both international (the Institute for Scientific Information, Scopus and PubMed) and Iranian scientific (Magiran, IranMedex and Scientific Information Database) databases. The review included original studies that used the Pabon Lasso Model to examine Iranian hospital performance, published in Persian or English. A self-administered checklist was used to collect data. In total, 12 questions were used for quality assessment. FINDINGS: In total, 34 studies met our inclusion criteria. The fixed-effects meta-analysis indicated that 19.2 percent (95% confidence interval (CI): 15.6-23.2 percent) of hospitals were in Zone 1 (poor performance: low bed turnover rate (BTR) and bed occupancy rate (BOR) and high average hospital stay (ALoS)), 23.7 percent (95% CI: 20.1-27.8 percent) were in Zone 2, 31.7 percent (95% CI: 27.7-36 percent) in Zone 3 (good performance: high BTR and BOR and low ALoS) and 25.4 percent (95% CI: 21.7-29.5 percent) in Zone 4. PRACTICAL IMPLICATIONS: Results help Iranian health policymakers to understand hospital performance, which, in turn, may lead to promoting greater awareness and policy attention to improve Iranian hospital efficiency. ORIGINALITY/VALUE: This study indicated that most Iranian hospitals had sub-optimal performance. Further studies are required to understand factors that explain the country's hospital inefficiency.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".