Bibliometric Analysis of Hospital Bed Management Study
Bibliographic record
Abstract
Healthcare and hospital services continue to evolve. This has led to hospital managers being faced with high demand for health services, shortages of hospital beds resulting in delayed inpatient admissions in emergency rooms, improper use of beds, and failure of transfer flows among care units that could reduce the quality of health care. This study aims to provide information on hospital bed management in the bibliometric data. Bibliometric analysis is used to look at research trends, including the most-published journals, the most-cited publishers, author agencies, and collaborations among authors, in visualization using the VOSViewer application. A total of nine English-language articles obtained from the Scopus database from 2018 to 2022 were used in the bibliometric analysis of hospital bed management. The most cited publisher's journal is the Journal of General Internal Medicine, with 12 citations. The results show that studies related to hospital bed management have not been done much but show an increasing trend from year to year. The author's contributions are dominated by developed countries such as the United States and Canada. Studies on hospital bed management are still needed as decision support tools to help professionals develop more assertive hospital bed management planning.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.188 | 0.412 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".