Time Allocated to Nursing Tasks on Hospital Units Caring for Older Patients
Bibliographic record
Abstract
INTRODUCTION: Hospitals need objective data about the time allocated to nursing tasks, particularly for older inpatients who often need assistance with activities of daily living (ADLs), such as toileting and mobility. METHODS: This descriptive time-motion study objectively measured the time registered nurses (RNs) and nursing assistants (NAs) spent on clinical and ADL care and made comparisons by staff type. Research staff completed 277 standardized observation hours on three hospital units caring for older patients. RESULTS: Registered nurses and NAs spent 38% and 34% of their time, respectively, on indirect care tasks, with medical record documentation being most common. Both staff types spent an additional 34% of their time on direct care tasks. Medication pass consumed the most RN direct care time, and ADL care consumed the most NA direct care time. Activities of daily living care was observed in fewer than 25% of patient encounters, despite 73%-89% of patients across the three units requiring ADL care assistance. Overall, staff spent less than 10% of their time idle. CONCLUSIONS: Objective data related to the time allocated to nursing tasks are necessary to inform skill mix adjustments or other staffing strategies to meet older inpatients' care needs.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".