Hospital in the home nurses’ assessment decision making: an integrative review of the literature
Bibliographic record
Abstract
AIM: To describe what is currently known about nurses' assessment decisions when providing care to patients at home or in their usual place of residence. METHODS: In August 2018, an integrative literature review using a systematic approach was conducted using specific search terms to search Informit, MEDLINE and Cumulative Index of Nursing and Allied Health Literature (CINAHL). The literature search was not limited by date, and included published papers or unpublished dissertations written between 1980 and 2018. RESULTS: In total 25 full papers were assessed for inclusion in this review; seven met the inclusion criteria. Three themes were identified from this review: i) nurse education and experience; ii) assessment informing decision-making and iii) knowing the patient. CONCLUSION: Nurses' education, experience, abilities, prior learning, beliefs, attitudes and values are key factors in the delivery of home-based nursing care, and strongly influence how assessments, clinical judgements and decisions are made. Impact Statement: An understanding of home based nurses' decisions and response to clinical deterioration is needed to inform Hospital in the Home nursing-specific curricula.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".