From Hospital to Home After Cardiac Surgery
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: This quasi-experimental research aims to (1) evaluate the implementation process of a community nursing care management model and (2) assess the effects of this model on patients followed at home. PRIMARY PRACTICE SETTING: Two community healthcare centers had introduced a community nursing care management model in their practice (experimental groups), whereas another health community care center with no experience with such a model served as a control group. The community nursing care management model included clinical pathways designed for a clientele who had been hospitalized for cardiac surgery. FINDINGS/CONCLUSIONS: Even though the implementation process was challenging, the community nursing care management model was found useful enough to be integrated into routine nursing home care practice after cardiac surgery. Although the effects produced by this systematic home care program on the clientele did not differ significantly from those produced by usual nursing care, there was a positive effect for the clientele recorded on all measurement indicators used. IMPLICATIONS FOR CASE MANAGEMENT PRACTICE: The introduction of the nursing care management model enabled nurses to structure the care provided and reduced interindividual variation. The application of this program also proved to be an opportunity to initiate and assimilate new professional roles. Additional studies should be conducted to assess its effectiveness in home care for other health problems.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".