Experiences of Older Adult Trauma Patients Discharged Home From a Level I Trauma Center
Bibliographic record
Abstract
The number of patients 65 years and older has been rising steadily every year at our Level I trauma center. Our clinical experience demonstrated that once discharged, some of these patients were not managing well. Postdischarge portrait is difficult to ascertain because this information is not captured in the trauma registry database. The purpose of this study was to describe the experiences of hospitalized trauma patients 65 years and older who are discharged home. A descriptive cross-sectional study of hospitalized trauma patients was conducted 1 month postdischarge using PREPARED Patient and 36-item Short Form Health Survey questionnaires. Data were analyzed with SPSS and NVivo. A convenience sample of 33 participants was recruited from four surgical inpatient trauma units of an urban, downtown hospital in Eastern Canada. Participants scored below 50% on most categories related to discharge preparedness and reported not having received enough information about their medication, available community resources, and permitted activities. They had worries about managing at home and 40% experienced unexpected problems. Participants reported feeling confident (80%) to be discharged home mostly because of support or previous experience with illness and 53% felt very prepared to return home. Health status scores were lowest for the domain "role limitation due to physical health" at 16% and highest around 70% for "emotional well-being" and "general health." Patients did not receive enough information; some experienced unexpected problems once home but having support and previous experience with illness seems to help participants be confident with discharge home. There is room for improvement on specific aspects of discharge planning and preparedness.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".