Nursing-Sensitive Outcomes Data Collection in Acute Care and Long-Term-Care Settings
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Most administrative databases do not contain good information about nursing-sensitive outcomes. OBJECTIVES: To determine (a) the reliability of the instruments measuring nursing-sensitive outcomes, (b) whether the outcome measures are sensitive to changes in patients' health, and (c) whether the outcome measures are associated with nursing interventions. METHODS: The sample consisted of 890 patients from acute care hospitals and long-term-care facilities. A repeated measures design was used. Functional status was assessed on admission and discharge using Minimum Data Set 2.0 items. Symptom (pain, nausea, dyspnea, fatigue) frequency and severity were assessed with 4-point and 11-point numeric scales, respectively. Therapeutic self-care was assessed on discharge from acute care. Nursing interventions were assessed by documentation review. RESULTS: The outcome measures demonstrated very good interrater reliability with weighted Kappa ranging from .64 to .93. The internal consistency reliability was high for functional status and therapeutic self-care. The outcome tools were sensitive to change in patient condition. Select nursing interventions were related to functional status, therapeutic self-care, and symptom outcomes. DISCUSSION: The findings suggest that nurses are able to collect data on nursing-sensitive patient outcomes in a reliable and valid way.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it