Relationships Between Wheelchair-Provision Time for Hospital Inpatients and Their Lengths of Stay and Costs of Hospitalization: A Cohort Study
Bibliographic record
Abstract
OBJECTIVES: To test the hypotheses that wheelchair-provision time (WPT) (from when a loaner wheelchair was ordered to when the wheelchair arrived at the hospital site) has a significant relationship with length of stay (LOS) and total cost of hospitalization (COH). DESIGN: Cohort study. SETTING: Hospital inpatient units. PARTICIPANTS: Hospital inpatients (N=97). INTERVENTION: Order for loaner wheelchair placed during their admissions. MAIN OUTCOME MEASURES: Demographic, clinical, and process data from 4 available databases, from which we derived WPT, LOS, and COH. To test the hypotheses, we used Spearman correlation coefficients, negative binomial regression for LOS (n=90), and linear regression for COH (n=69). RESULTS: The median values for WPT, LOS, and total COH were 3.8 days, 51.0 days, and $43,062 Canadian dollars. Multivariable regression revealed that WPT was associated to a statistically significant extent with LOS (P=.0049) (a 18% increase in LOS for each additional day in WPT), but not with COH. However, LOS was associated to a statistically significant extent with COH (P<.0001). The Spearman correlation between LOS and COH was 0.8915 (P<.0001). CONCLUSIONS: Statistically significant associations exist between WPT and LOS and between LOS and COH. Although this study does not establish causality and further research is needed, our findings suggest that more rapid provision of loaner wheelchairs to hospital inpatients could have a positive effect on the health care system.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".