Calculation of Bed Occupancy Rate, Length of Stay, Turn Over Interval, Bed Turn Over On The Utilization of Beds In Fakhrudin Ward PKU Muhammadiyah Sruweng
Bibliographic record
Abstract
This study aim to determine the results of the calculation of Bed Occupany Rate (BOR), Length Of Stay (LOS), Turn Over Interval (TOI), Bed Turn Over (BTO) on the use of beds in the Fakhrudin ward PKU Muhammadiyah Sruweg in 2018.The research method used was descriptive research with qualitative approach. The sampling technique used was saturated sampling, with inpatient recapitulation data sample of Fakhrudin ward in 2018.The results of the calculation of BOR, LOS, TOI and BTO on the Fakhrudin ward in the first quarter of 2018 shows the values of BOR in the coverage of 74-88%, the values of LOS and TOI in 3-4 days and 0.5-1 days respectively,, and the values of BTO in 19-21 times. So it was concluded that the use of beds was quite high. Therefore, it is required to add or relocate beds / rooms to the ward so that the demand for beds for inpatients is fulfilled without patient care system.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".