Physiotherapists' Perceptions of and Experiences with the Discharge Planning Process in Acute-Care General Internal Medicine Units in Ontario
Bibliographic record
Abstract
PURPOSE: To examine discharge planning of patients in general internal medicine units in Ontario acute-care hospitals from the perspective of physiotherapists. METHODS: A cross-sectional study using an online questionnaire was sent to participants in November 2011. Respondents' demographic characteristics and ranking of factors were analyzed using descriptive statistics; t-tests were performed to determine between-group differences (based on demographic characteristics). Responses to open-ended questions were coded to identify themes. RESULTS: Mobility status was identified as the key factor in determining discharge readiness; other factors included the availability of social support and community resources. While inter-professional communication was identified as important, processes were often informal. Discharge policies, timely availability of other discharge options, and pressure for early discharge were identified as affecting discharge planning. Respondents also noted a lack of training in discharge planning; accounts of ethical dilemmas experienced by respondents supported these themes. CONCLUSIONS: Physiotherapists consider many factors beyond the patient's physical function during the discharge planning process. The improvement of team communication and resource allocation should be considered to deal with the realities of discharge planning.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".