Unplanned readmission for older persons: A concept analysis
Bibliographic record
Abstract
AIM: The purpose of this concept analysis is to define and analyse the concept of unplanned readmission to hospital for older persons. DESIGN: Review the literature and analyse the concept of unplanned readmission. METHOD: Guided by Walker and Avant's eight-stage method of concept analysis, four databases (Ovid MEDLINE, Scopus, CINAHL, and Embase) were searched between 1946 and 2020 for empirical studies focused on older persons with multiple chronic conditions, experiences or perspectives and unplanned readmission. A total of 34 articles (10 quantitative, 17 qualitative, three mixed methods), one concept analysis and three historical articles were included. RESULTS: An unplanned readmission is an experience, process and event. The proposed definition of unplanned readmission is an older person's need for acute care treatment for an urgent or emergent health crisis that has occurred after a previous hospitalization(s). Unplanned readmission is characterized by the attributes of older persons' previous hospitalization(s), the urgent or emergent nature of the older persons' health and the older persons' need for acute care hospital services to resolve their health crisis. CONCLUSION: Unplanned readmission is a complex concept that is different from planned and emergency visits/admissions and readiness for discharge. These findings provide a link for understanding unplanned readmission as a consequence of discharge readiness. Analysing this concept supports the need for older persons to seek unplanned readmission for acute care treatment of urgent and emergent health crisis, reduces the blame that older persons may feel from questions related to preventability, and stresses the need to include older persons' experiences in the development and expansion of nursing theory, interventions and current understandings of unplanned readmission.
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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 | 0.040 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.018 | 0.012 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".