The Impact of Hospital Nursing Characteristics on 30-Day Mortality
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Bibliographic record
Abstract
BACKGROUND: Evidence indicates that hospital nursing characteristics such as staffing contribute to patient outcomes. Less attention has been given to other hospital nursing characteristics central to optimal professional practice, namely nurse education and skill mix, continuity of care, and quality of the work environment. OBJECTIVE: To assess the relative effects and importance of nurse education and skill mix, continuity of care, and quality of work environment in predicting 30-day mortality after adjusting for institutional factors and individual patients characteristics. METHOD: A cross-sectional analysis of outcome data for 18,142 patients discharged from 49 acute care hospitals in Alberta, Canada, for diagnoses of acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, pneumonia, or stroke between April 1, 1998, and March 31, 1999, was done. Mortality data were linked to patient demographic and comorbidity factors, institutional characteristics, and hospital nursing characteristics derived from a survey of all registered nurses working in acute care hospitals. RESULTS: Using multilevel analysis, it was determined that the log-odds for 30-day mortality varied significantly across hospitals (variance = .044, p < .001). Patient comorbidities and age explained 44.2% of the variance in 30-day mortality. After adjustment for patient comorbidities and demographic factors, and the size, teaching, and urban status of the study hospitals in a fixed-effects model, the odds ratios (95% confidence interval) of the significant hospital nursing characteristics that predict 30-day mortality were as follows: 0.81 (0.68-0.96) for higher nurse education level, 0.83 (0.73-0.96) for richer nurse skill mix, 1.26 (1.09-1.47) for higher proportion of casual or temporary positions, and 0.74 (0.60-0.91) for greater nurse-physician relationships. The institutional and hospital nursing characteristics explained an additional 36.9%. DISCUSSION: Hospital nursing characteristics are an important consideration in efforts to reduce the risk of 30-day mortality of patients.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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